Bryq vs. Maki People
Which Pre-Employment Assessment Fits Your Hiring Process?
Bryq vs. Maki People
Which Pre-Employment Assessment Fits Your Hiring Process?
Bryq vs. Maki People
Which Pre-Employment Assessment Fits Your Hiring Process?
Bryq vs. Maki People: Which Pre-Employment Assessment Fits Your Hiring Process?
Bryq vs. Maki People: Which Pre-Employment Assessment Fits Your Hiring Process?
There's a question underneath every assessment platform purchase that rarely gets asked out loud: how much of the hiring process do you actually want to hand over to AI?
That question used to be theoretical. Well, it's not anymore. Maki People, a Paris-founded startup backed by $35 million in venture capital, is betting that the answer is "almost everything." Their pitch is an "AI Tier" of autonomous agents that screen, interview, schedule, and assess candidates with minimal human involvement. Five separate agents, each handling a different stage of the funnel. The goal is a streamlined early-stage recruiting so recruiters focus on high-touch interactions instead of administrative overhead.
Bryq takes a different position. One integrated candidate assessment. One profile. Five dimensions measured in a single session. The AI does the heavy analytical work, but the hiring team makes the decisions. It's a different philosophy about where intelligence should sit in the hiring process, and choosing between them tells you something about what kind of organization you're building.
This comparison walks through both assessment platforms across the things that actually matter: how they work, what candidates experience, how the science holds up, and where each one fits best.
There's a question underneath every assessment platform purchase that rarely gets asked out loud: how much of the hiring process do you actually want to hand over to AI?
That question used to be theoretical. Well, it's not anymore. Maki People, a Paris-founded startup backed by $35 million in venture capital, is betting that the answer is "almost everything." Their pitch is an "AI Tier" of autonomous agents that screen, interview, schedule, and assess candidates with minimal human involvement. Five separate agents, each handling a different stage of the funnel. The goal is a streamlined early-stage recruiting so recruiters focus on high-touch interactions instead of administrative overhead.
Bryq takes a different position. One integrated candidate assessment. One profile. Five dimensions measured in a single session. The AI does the heavy analytical work, but the hiring team makes the decisions. It's a different philosophy about where intelligence should sit in the hiring process, and choosing between them tells you something about what kind of organization you're building.
This comparison walks through both assessment platforms across the things that actually matter: how they work, what candidates experience, how the science holds up, and where each one fits best.
There's a question underneath every assessment platform purchase that rarely gets asked out loud: how much of the hiring process do you actually want to hand over to AI?
That question used to be theoretical. Well, it's not anymore. Maki People, a Paris-founded startup backed by $35 million in venture capital, is betting that the answer is "almost everything." Their pitch is an "AI Tier" of autonomous agents that screen, interview, schedule, and assess candidates with minimal human involvement. Five separate agents, each handling a different stage of the funnel. The goal is a streamlined early-stage recruiting so recruiters focus on high-touch interactions instead of administrative overhead.
Bryq takes a different position. One integrated candidate assessment. One profile. Five dimensions measured in a single session. The AI does the heavy analytical work, but the hiring team makes the decisions. It's a different philosophy about where intelligence should sit in the hiring process, and choosing between them tells you something about what kind of organization you're building.
This comparison walks through both assessment platforms across the things that actually matter: how they work, what candidates experience, how the science holds up, and where each one fits best.
Side-by-Side Comparison at a Glance
Side-by-Side Comparison at a Glance
Bryq
Bryq
Maki People
Maki People
What it measures
What it measures
Cognitive ability + behavioral traits + hard skills (incl. AI proficiency) in one integrated candidate assessment
Cognitive ability + behavioral traits + hard skills (incl. AI proficiency) in one integrated candidate assessment
Cognitive ability + behavioral traits + hard skills (incl. AI proficiency) in one integrated candidate assessment
300+ skills across cognitive assessments, personality tests, coding tests, and aptitude tests via modular agent-led evaluations
300+ skills across cognitive assessments, personality tests, coding tests, and aptitude tests via modular agent-led evaluations
300+ skills across cognitive assessments, personality tests, coding tests, and aptitude tests via modular agent-led evaluations
Core approach
Core approach
AI builds an Ideal Candidate Profile for each specific job; every applicant scored on predicted fit
AI builds an Ideal Candidate Profile for each specific job; every applicant scored on predicted fit
AI builds an Ideal Candidate Profile for each specific job; every applicant scored on predicted fit
Five autonomous AI agents (Shiro, Mochi, Ken, Kumi, Riku) each handle a different funnel stage using algorithms and real-time data
Five autonomous AI agents (Shiro, Mochi, Ken, Kumi, Riku) each handle a different funnel stage using algorithms and real-time data
Five autonomous AI agents (Shiro, Mochi, Ken, Kumi, Riku) each handle a different funnel stage using algorithms and real-time data
Best for
Best for
Mid-market, enterprises, and hiring teams focused on finding the right candidates and reducing turnover
Mid-market, enterprises, and hiring teams focused on finding the right candidates and reducing turnover
Mid-market, enterprises, and hiring teams focused on finding the right candidates and reducing turnover
High-volume frontline hiring needs, enterprises wanting end-to-end automation of early-funnel screening
High-volume frontline hiring needs, enterprises wanting end-to-end automation of early-funnel screening
High-volume frontline hiring needs, enterprises wanting end-to-end automation of early-funnel screening
Candidate experience
Candidate experience
One cohesive assessment; respectful, structured, no heavy surveillance
One cohesive assessment; respectful, structured, no heavy surveillance
One cohesive assessment; respectful, structured, no heavy surveillance
Multimodal (text, voice, video interview); webcam snapshots every 30 seconds, device fingerprinting
Multimodal (text, voice, video interview); webcam snapshots every 30 seconds, device fingerprinting
Multimodal (text, voice, video interview); webcam snapshots every 30 seconds, device fingerprinting
AI proficiency
AI proficiency
Built-in: ~15 min, scenario-based, 5 scored dimensions, 6 peer-reviewed frameworks (UNESCO, SFIA, OECD)
Built-in: ~15 min, scenario-based, 5 scored dimensions, 6 peer-reviewed frameworks (UNESCO, SFIA, OECD)
Built-in: ~15 min, scenario-based, 5 scored dimensions, 6 peer-reviewed frameworks (UNESCO, SFIA, OECD)
No dedicated AI proficiency module; AI powers the agents, doesn't measure candidate's abilities with AI tools
No dedicated AI proficiency module; AI powers the agents, doesn't measure candidate's abilities with AI tools
No dedicated AI proficiency module; AI powers the agents, doesn't measure candidate's abilities with AI tools
Pricing plans
Pricing plans
Flat-rate subscription, unlimited assessments
Flat-rate subscription, unlimited assessments
Flat-rate subscription, unlimited assessments
Usage-based credit model; enterprise quotes required
Usage-based credit model; enterprise quotes required
Usage-based credit model; enterprise quotes required
ATS integrations
ATS integrations
Greenhouse, Lever, Workable, Workday, iCIMS + many more
Greenhouse, Lever, Workable, Workday, iCIMS + many more
Greenhouse, Lever, Workable, Workday, iCIMS + many more
Ashby, Workable, Greenhouse, Workday, SmartRecruiters + more
Ashby, Workable, Greenhouse, Workday, SmartRecruiters + more
Ashby, Workable, Greenhouse, Workday, SmartRecruiters + more
Customization
Customization
Role-specific profiles built by AI; assessment adapts to each role
Role-specific profiles built by AI; assessment adapts to each role
Role-specific profiles built by AI; assessment adapts to each role
Custom branding, custom questions, white-label landing pages, custom agent stacks
Custom branding, custom questions, white-label landing pages, custom agent stacks
Custom branding, custom questions, white-label landing pages, custom agent stacks
Compliance
Compliance
GDPR compliant, ISO 27001 certified, built on I-O psychology principles
GDPR compliant, ISO 27001 certified, built on I-O psychology principles
GDPR compliant, ISO 27001 certified, built on I-O psychology principles
GDPR compliant, ISO 27001 certified
GDPR compliant, ISO 27001 certified
GDPR compliant, ISO 27001 certified
What Is Maki People?
What Is Maki People?
Maki People is a Paris-based assessment platform founded in 2021 by a team with roots in logistics and management consulting. The CEO previously built a digital freight company, the COO is a former McKinsey Partner, and the CPO led product at Uber. That operational DNA shows up in the product: it's built for speed and volume, with less emphasis on depth of measurement.
The central idea is what Maki People calls an "AI Tier" that sits above your existing ATS. Instead of one tool, you get five autonomous agents.
1. Shiro handles skills assessment and TOF screening with custom questions and knock-out logic.
Mochi runs conversational interviews across multiple languages.
Ken administers deeper evaluation with coding tests, aptitude tests, and problem-solving simulations for technical or leadership roles.
Kumi schedules interviews automatically.
Riku (still in early access) manages internal mobility using a unified skills framework.
Each agent operates with real-time autonomy. They don't just flag candidates for teams to review. They move candidates through pipeline stages, score responses against models, and coordinate calendars. Their language around this is deliberate. These are "teammates, not tools." In regulated industries, that level of autonomous authority can raise governance questions.
The company has raised $35.3 million, including a $28.6 million Series A in January 2025. Their client list includes H&M, PwC, Deloitte, and IKEA. The company reports a 3x reduction in time-to-hire and 80% automation of screening, though those figures come from vendor case studies rather than independent research. They use a credit-based model, meaning you pay per candidate interaction and per agent activated. The enterprise tier requires a custom quote, and costs aren't publicly listed.
For customization options, they offer custom branding on landing pages, welcome videos, and email templates. Recruiters can build custom agent stacks using different combinations of Shiro, Mochi, and Ken based on their hiring needs. It also generates AI-powered job descriptions from role-specific templates, which can save time when you're posting across multiple boards.
Maki People is a Paris-based assessment platform founded in 2021 by a team with roots in logistics and management consulting. The CEO previously built a digital freight company, the COO is a former McKinsey Partner, and the CPO led product at Uber. That operational DNA shows up in the product: it's built for speed and volume, with less emphasis on depth of measurement.
The central idea is what Maki People calls an "AI Tier" that sits above your existing ATS. Instead of one tool, you get five autonomous agents.
1. Shiro handles skills assessment and TOF screening with custom questions and knock-out logic.
Mochi runs conversational interviews across multiple languages.
Ken administers deeper evaluation with coding tests, aptitude tests, and problem-solving simulations for technical or leadership roles.
Kumi schedules interviews automatically.
Riku (still in early access) manages internal mobility using a unified skills framework.
Each agent operates with real-time autonomy. They don't just flag candidates for teams to review. They move candidates through pipeline stages, score responses against models, and coordinate calendars. Their language around this is deliberate. These are "teammates, not tools." In regulated industries, that level of autonomous authority can raise governance questions.
The company has raised $35.3 million, including a $28.6 million Series A in January 2025. Their client list includes H&M, PwC, Deloitte, and IKEA. The company reports a 3x reduction in time-to-hire and 80% automation of screening, though those figures come from vendor case studies rather than independent research. They use a credit-based model, meaning you pay per candidate interaction and per agent activated. The enterprise tier requires a custom quote, and costs aren't publicly listed.
For customization options, they offer custom branding on landing pages, welcome videos, and email templates. Recruiters can build custom agent stacks using different combinations of Shiro, Mochi, and Ken based on their hiring needs. It also generates AI-powered job descriptions from role-specific templates, which can save time when you're posting across multiple boards.
Maki People is a Paris-based assessment platform founded in 2021 by a team with roots in logistics and management consulting. The CEO previously built a digital freight company, the COO is a former McKinsey Partner, and the CPO led product at Uber. That operational DNA shows up in the product: it's built for speed and volume, with less emphasis on depth of measurement.
The central idea is what Maki People calls an "AI Tier" that sits above your existing ATS. Instead of one tool, you get five autonomous agents.
1. Shiro handles skills assessment and TOF screening with custom questions and knock-out logic.
Mochi runs conversational interviews across multiple languages.
Ken administers deeper evaluation with coding tests, aptitude tests, and problem-solving simulations for technical or leadership roles.
Kumi schedules interviews automatically.
Riku (still in early access) manages internal mobility using a unified skills framework.
Each agent operates with real-time autonomy. They don't just flag candidates for teams to review. They move candidates through pipeline stages, score responses against models, and coordinate calendars. Their language around this is deliberate. These are "teammates, not tools." In regulated industries, that level of autonomous authority can raise governance questions.
The company has raised $35.3 million, including a $28.6 million Series A in January 2025. Their client list includes H&M, PwC, Deloitte, and IKEA. The company reports a 3x reduction in time-to-hire and 80% automation of screening, though those figures come from vendor case studies rather than independent research. They use a credit-based model, meaning you pay per candidate interaction and per agent activated. The enterprise tier requires a custom quote, and costs aren't publicly listed.
For customization options, they offer custom branding on landing pages, welcome videos, and email templates. Recruiters can build custom agent stacks using different combinations of Shiro, Mochi, and Ken based on their hiring needs. It also generates AI-powered job descriptions from role-specific templates, which can save time when you're posting across multiple boards.
What Is Bryq?
What Is Bryq?
Bryq is an assessment platform built around one core idea: you shouldn't need five separate assessment tools to understand whether someone will succeed in a role. The platform measures reasoning aptitude, personality traits, role-specific hard skills, and AI proficiency in a single integrated evaluation. One session. One profile that captures every dimension of candidates' skills and potential.
The AI engine starts by building an Ideal Candidate Profile for each specific job. It evaluates the job descriptions and requirements, then scores every applicant against that profile. Talent acquisition teams get a ranked list of the best candidates with composite fit scores, not separate test results to reconcile by hand. That means fewer wrong-fit interviews and more time spent with the right candidates.
One thing worth flagging: the AI Proficiency Assessment. It measures how candidates actually work with AI in realistic, practical scenarios. Tool-agnostic. Role-universal. Built on six peer-reviewed research frameworks including UNESCO, SFIA, and OECD. Five scored dimensions, 0 to 100 per dimension, no pass/fail binary. Takes roughly 15 minutes. It's included in all plans, not sold as an add-on.
On the science side, the assessments are grounded in I-O psychology principles and validated for predictive validity. The platform integrates with Greenhouse, Lever, Workday, iCIMS, and custom setups. Reactions to the experience skew positive because the format feels like solving real-world challenges rather than sitting through a personality assessment battery.
Proof points from the customer base: 80% reduction in screening time, 3x improvement in quality of hire, 40% drop in early turnover. Those results come from measuring actual job fit, including soft skills and behavioral dimensions, rather than checking individual skill boxes one at a time.
Bryq is an assessment platform built around one core idea: you shouldn't need five separate assessment tools to understand whether someone will succeed in a role. The platform measures reasoning aptitude, personality traits, role-specific hard skills, and AI proficiency in a single integrated evaluation. One session. One profile that captures every dimension of candidates' skills and potential.
The AI engine starts by building an Ideal Candidate Profile for each specific job. It evaluates the job descriptions and requirements, then scores every applicant against that profile. Talent acquisition teams get a ranked list of the best candidates with composite fit scores, not separate test results to reconcile by hand. That means fewer wrong-fit interviews and more time spent with the right candidates.
One thing worth flagging: the AI Proficiency Assessment. It measures how candidates actually work with AI in realistic, practical scenarios. Tool-agnostic. Role-universal. Built on six peer-reviewed research frameworks including UNESCO, SFIA, and OECD. Five scored dimensions, 0 to 100 per dimension, no pass/fail binary. Takes roughly 15 minutes. It's included in all plans, not sold as an add-on.
On the science side, the assessments are grounded in I-O psychology principles and validated for predictive validity. The platform integrates with Greenhouse, Lever, Workday, iCIMS, and custom setups. Reactions to the experience skew positive because the format feels like solving real-world challenges rather than sitting through a personality assessment battery.
Proof points from the customer base: 80% reduction in screening time, 3x improvement in quality of hire, 40% drop in early turnover. Those results come from measuring actual job fit, including soft skills and behavioral dimensions, rather than checking individual skill boxes one at a time.
Bryq is an assessment platform built around one core idea: you shouldn't need five separate assessment tools to understand whether someone will succeed in a role. The platform measures reasoning aptitude, personality traits, role-specific hard skills, and AI proficiency in a single integrated evaluation. One session. One profile that captures every dimension of candidates' skills and potential.
The AI engine starts by building an Ideal Candidate Profile for each specific job. It evaluates the job descriptions and requirements, then scores every applicant against that profile. Talent acquisition teams get a ranked list of the best candidates with composite fit scores, not separate test results to reconcile by hand. That means fewer wrong-fit interviews and more time spent with the right candidates.
One thing worth flagging: the AI Proficiency Assessment. It measures how candidates actually work with AI in realistic, practical scenarios. Tool-agnostic. Role-universal. Built on six peer-reviewed research frameworks including UNESCO, SFIA, and OECD. Five scored dimensions, 0 to 100 per dimension, no pass/fail binary. Takes roughly 15 minutes. It's included in all plans, not sold as an add-on.
On the science side, the assessments are grounded in I-O psychology principles and validated for predictive validity. The platform integrates with Greenhouse, Lever, Workday, iCIMS, and custom setups. Reactions to the experience skew positive because the format feels like solving real-world challenges rather than sitting through a personality assessment battery.
Proof points from the customer base: 80% reduction in screening time, 3x improvement in quality of hire, 40% drop in early turnover. Those results come from measuring actual job fit, including soft skills and behavioral dimensions, rather than checking individual skill boxes one at a time.
Detailed Comparison: Where They Diverge
Detailed Comparison: Where They Diverge
Philosophy: Autonomous Agents vs. Integrated Assessment Platform
Philosophy: Autonomous Agents vs. Integrated Assessment Platform
This is the fork in the road. Everything else follows from it.
Maki People believes the early hiring process should be largely automated. Their agents don't just assist recruiters. They act. Shiro screens candidates' skills. Mochi interviews. Ken evaluates the candidate's abilities in depth. Kumi schedules. The recruiter enters the process after the system has already made significant decisions about who advances.
That's appealing if your primary problem is volume. If you're processing thousands of job applications for frontline roles and your managers are drowning in screening work, handing that workflow to autonomous agents is a real time-saver. Their case studies support this: Foundever processed 200,000 candidates in six months, and The Restaurant Group eliminated manual screening as a bottleneck entirely. Speed metrics, though. Not quality-of-hire metrics. Nobody's publishing retention data from fully autonomous screening yet.
But there's a tradeoff. When AI agents make autonomous calls about who moves forward, you're trusting the system's judgment at a point where the stakes are high and the signal is thin. Who's accountable when an agent screens out the best talent based on a knock-out question? Auditing a decision made by a conversational AI that adapts its custom questions on the fly is harder than most teams realize.
The approach here is different. The AI does the analytical heavy lifting: building the role profile, running the evaluation, scoring the fit. But the decisions stay with your team. That's not a limitation; it's the point. You see the ranked list. You see the dimension scores. You decide who to interview. For organizations that want AI-powered intelligence without surrendering control of who gets hired, that's a meaningful distinction, especially in industries where hiring decisions carry regulatory weight.
This is the fork in the road. Everything else follows from it.
Maki People believes the early hiring process should be largely automated. Their agents don't just assist recruiters. They act. Shiro screens candidates' skills. Mochi interviews. Ken evaluates the candidate's abilities in depth. Kumi schedules. The recruiter enters the process after the system has already made significant decisions about who advances.
That's appealing if your primary problem is volume. If you're processing thousands of job applications for frontline roles and your managers are drowning in screening work, handing that workflow to autonomous agents is a real time-saver. Their case studies support this: Foundever processed 200,000 candidates in six months, and The Restaurant Group eliminated manual screening as a bottleneck entirely. Speed metrics, though. Not quality-of-hire metrics. Nobody's publishing retention data from fully autonomous screening yet.
But there's a tradeoff. When AI agents make autonomous calls about who moves forward, you're trusting the system's judgment at a point where the stakes are high and the signal is thin. Who's accountable when an agent screens out the best talent based on a knock-out question? Auditing a decision made by a conversational AI that adapts its custom questions on the fly is harder than most teams realize.
The approach here is different. The AI does the analytical heavy lifting: building the role profile, running the evaluation, scoring the fit. But the decisions stay with your team. That's not a limitation; it's the point. You see the ranked list. You see the dimension scores. You decide who to interview. For organizations that want AI-powered intelligence without surrendering control of who gets hired, that's a meaningful distinction, especially in industries where hiring decisions carry regulatory weight.
This is the fork in the road. Everything else follows from it.
Maki People believes the early hiring process should be largely automated. Their agents don't just assist recruiters. They act. Shiro screens candidates' skills. Mochi interviews. Ken evaluates the candidate's abilities in depth. Kumi schedules. The recruiter enters the process after the system has already made significant decisions about who advances.
That's appealing if your primary problem is volume. If you're processing thousands of job applications for frontline roles and your managers are drowning in screening work, handing that workflow to autonomous agents is a real time-saver. Their case studies support this: Foundever processed 200,000 candidates in six months, and The Restaurant Group eliminated manual screening as a bottleneck entirely. Speed metrics, though. Not quality-of-hire metrics. Nobody's publishing retention data from fully autonomous screening yet.
But there's a tradeoff. When AI agents make autonomous calls about who moves forward, you're trusting the system's judgment at a point where the stakes are high and the signal is thin. Who's accountable when an agent screens out the best talent based on a knock-out question? Auditing a decision made by a conversational AI that adapts its custom questions on the fly is harder than most teams realize.
The approach here is different. The AI does the analytical heavy lifting: building the role profile, running the evaluation, scoring the fit. But the decisions stay with your team. That's not a limitation; it's the point. You see the ranked list. You see the dimension scores. You decide who to interview. For organizations that want AI-powered intelligence without surrendering control of who gets hired, that's a meaningful distinction, especially in industries where hiring decisions carry regulatory weight.
Candidate Assessment: Breadth vs. Depth
Candidate Assessment: Breadth vs. Depth
Maki People's assessment library spans 300+ skills evaluated through its test library of modular assessments. That includes personality tests, cognitive assessments, aptitude tests, coding tests, and situational judgment tests. Teams can build custom tests using the platform's configurator, tailoring the battery to their specific hiring needs. That breadth pays off when you're hiring across dozens of different role types.
But breadth creates complexity. Which assessment tools do you combine, and how do you weight cognitive assessments against personality tests against code challenges? The test library doesn't interpret itself, and reconciling scores across different agents and modules adds exactly the kind of overhead the "autonomous" promise was supposed to eliminate. You traded one bottleneck for another.
The platform collapses all of that into one evaluation. Cognitive ability, personality traits, hard skills, cultural fit, and AI proficiency, all measured in a single session and scored against an Ideal Candidate Profile built for that specific job. Teams spend less time configuring testing modules and more time interviewing the right candidates. The integrated approach also means you're comparing candidates on the same scale, not piecing together results from different agents with different scoring logic.
Maki People's assessment library spans 300+ skills evaluated through its test library of modular assessments. That includes personality tests, cognitive assessments, aptitude tests, coding tests, and situational judgment tests. Teams can build custom tests using the platform's configurator, tailoring the battery to their specific hiring needs. That breadth pays off when you're hiring across dozens of different role types.
But breadth creates complexity. Which assessment tools do you combine, and how do you weight cognitive assessments against personality tests against code challenges? The test library doesn't interpret itself, and reconciling scores across different agents and modules adds exactly the kind of overhead the "autonomous" promise was supposed to eliminate. You traded one bottleneck for another.
The platform collapses all of that into one evaluation. Cognitive ability, personality traits, hard skills, cultural fit, and AI proficiency, all measured in a single session and scored against an Ideal Candidate Profile built for that specific job. Teams spend less time configuring testing modules and more time interviewing the right candidates. The integrated approach also means you're comparing candidates on the same scale, not piecing together results from different agents with different scoring logic.
Maki People's assessment library spans 300+ skills evaluated through its test library of modular assessments. That includes personality tests, cognitive assessments, aptitude tests, coding tests, and situational judgment tests. Teams can build custom tests using the platform's configurator, tailoring the battery to their specific hiring needs. That breadth pays off when you're hiring across dozens of different role types.
But breadth creates complexity. Which assessment tools do you combine, and how do you weight cognitive assessments against personality tests against code challenges? The test library doesn't interpret itself, and reconciling scores across different agents and modules adds exactly the kind of overhead the "autonomous" promise was supposed to eliminate. You traded one bottleneck for another.
The platform collapses all of that into one evaluation. Cognitive ability, personality traits, hard skills, cultural fit, and AI proficiency, all measured in a single session and scored against an Ideal Candidate Profile built for that specific job. Teams spend less time configuring testing modules and more time interviewing the right candidates. The integrated approach also means you're comparing candidates on the same scale, not piecing together results from different agents with different scoring logic.
Candidate Experience: Surveilled vs. Structured
Candidate Experience: Surveilled vs. Structured
The proctoring suite is extensive. Webcam snapshots every 30 seconds. Device fingerprinting across 70+ technical factors. IP geolocation tracking. Focus-out detection. AI-powered answer detection that flags ChatGPT usage. CNN-based object detection for phones and tablets. For compliance-heavy contexts or roles where cheating risk is high, that level of webcam monitoring has a logic to it.
For most professional roles, it doesn't. A candidate with options will notice they're being surveilled like a test-taker, not evaluated like a professional. That hits completion rates and employer brand, especially when top talent in competitive markets already has three other offers on the table.
The candidate experience in Bryq is designed around a different principle: respect the candidate's time and intelligence. One cohesive assessment. Structured, scenario-based, and responsive across devices. No webcam snapshots every half-minute. No device fingerprinting. Candidate feedback is consistently positive because the format feels closer to actual problem-solving than sitting for a proctored exam.
The proctoring suite is extensive. Webcam snapshots every 30 seconds. Device fingerprinting across 70+ technical factors. IP geolocation tracking. Focus-out detection. AI-powered answer detection that flags ChatGPT usage. CNN-based object detection for phones and tablets. For compliance-heavy contexts or roles where cheating risk is high, that level of webcam monitoring has a logic to it.
For most professional roles, it doesn't. A candidate with options will notice they're being surveilled like a test-taker, not evaluated like a professional. That hits completion rates and employer brand, especially when top talent in competitive markets already has three other offers on the table.
The candidate experience in Bryq is designed around a different principle: respect the candidate's time and intelligence. One cohesive assessment. Structured, scenario-based, and responsive across devices. No webcam snapshots every half-minute. No device fingerprinting. Candidate feedback is consistently positive because the format feels closer to actual problem-solving than sitting for a proctored exam.
The proctoring suite is extensive. Webcam snapshots every 30 seconds. Device fingerprinting across 70+ technical factors. IP geolocation tracking. Focus-out detection. AI-powered answer detection that flags ChatGPT usage. CNN-based object detection for phones and tablets. For compliance-heavy contexts or roles where cheating risk is high, that level of webcam monitoring has a logic to it.
For most professional roles, it doesn't. A candidate with options will notice they're being surveilled like a test-taker, not evaluated like a professional. That hits completion rates and employer brand, especially when top talent in competitive markets already has three other offers on the table.
The candidate experience in Bryq is designed around a different principle: respect the candidate's time and intelligence. One cohesive assessment. Structured, scenario-based, and responsive across devices. No webcam snapshots every half-minute. No device fingerprinting. Candidate feedback is consistently positive because the format feels closer to actual problem-solving than sitting for a proctored exam.
AI Proficiency: Measured vs. Missing
AI Proficiency: Measured vs. Missing
Here's where the gap is widest. Maki People uses artificial intelligence to power its agents. That's AI as infrastructure. But the platform has no validated skills assessment for measuring whether candidates themselves can work effectively with AI.
That's a blind spot. 75% of knowledge workers already use AI at work, yet most organizations can't tell the difference between someone who uses AI as a force multiplier and someone who pastes everything into ChatGPT and hits send. For TA leaders and CHROs, that's a growing gap in skills-based hiring.
Bryq's AI Proficiency Assessment fills it. Scenario-based. Tool-agnostic. Grounded in six peer-reviewed frameworks. Five scored dimensions covering AI task strategy, prompting, critical evaluation, ethical use, and workflow integration. Scores run 0 to 100 per dimension. It's included in every plan, and it measures something no amount of autonomous screening agents can tell you: whether this person will make AI work for them, not the other way around.
Here's where the gap is widest. Maki People uses artificial intelligence to power its agents. That's AI as infrastructure. But the platform has no validated skills assessment for measuring whether candidates themselves can work effectively with AI.
That's a blind spot. 75% of knowledge workers already use AI at work, yet most organizations can't tell the difference between someone who uses AI as a force multiplier and someone who pastes everything into ChatGPT and hits send. For TA leaders and CHROs, that's a growing gap in skills-based hiring.
Bryq's AI Proficiency Assessment fills it. Scenario-based. Tool-agnostic. Grounded in six peer-reviewed frameworks. Five scored dimensions covering AI task strategy, prompting, critical evaluation, ethical use, and workflow integration. Scores run 0 to 100 per dimension. It's included in every plan, and it measures something no amount of autonomous screening agents can tell you: whether this person will make AI work for them, not the other way around.
Here's where the gap is widest. Maki People uses artificial intelligence to power its agents. That's AI as infrastructure. But the platform has no validated skills assessment for measuring whether candidates themselves can work effectively with AI.
That's a blind spot. 75% of knowledge workers already use AI at work, yet most organizations can't tell the difference between someone who uses AI as a force multiplier and someone who pastes everything into ChatGPT and hits send. For TA leaders and CHROs, that's a growing gap in skills-based hiring.
Bryq's AI Proficiency Assessment fills it. Scenario-based. Tool-agnostic. Grounded in six peer-reviewed frameworks. Five scored dimensions covering AI task strategy, prompting, critical evaluation, ethical use, and workflow integration. Scores run 0 to 100 per dimension. It's included in every plan, and it measures something no amount of autonomous screening agents can tell you: whether this person will make AI work for them, not the other way around.
Pricing Plans: Credits vs. Flat Rate
Pricing Plans: Credits vs. Flat Rate
The platform runs on a usage-based credit model. You pay per candidate interaction and per agent activated. No public pricing. Enterprise plan quotes require a conversation with sales. The company describes its model as "partnership-first" with dedicated Customer Success Managers and guided onboarding.
That works for steady-state hiring. But it introduces variability. A seasonal hiring spike means a cost spike. Activating five agents for a role costs more than activating two. And because costs are opaque, it's harder to benchmark during procurement.
The flat-rate subscription covers unlimited assessments. Your per-candidate cost goes down as volume goes up. Not the reverse. For teams that need to budget around fluctuating hiring needs, especially during growth phases or seasonal surges, that predictability matters. You're paying for insight, not for agent activations.
The platform runs on a usage-based credit model. You pay per candidate interaction and per agent activated. No public pricing. Enterprise plan quotes require a conversation with sales. The company describes its model as "partnership-first" with dedicated Customer Success Managers and guided onboarding.
That works for steady-state hiring. But it introduces variability. A seasonal hiring spike means a cost spike. Activating five agents for a role costs more than activating two. And because costs are opaque, it's harder to benchmark during procurement.
The flat-rate subscription covers unlimited assessments. Your per-candidate cost goes down as volume goes up. Not the reverse. For teams that need to budget around fluctuating hiring needs, especially during growth phases or seasonal surges, that predictability matters. You're paying for insight, not for agent activations.
The platform runs on a usage-based credit model. You pay per candidate interaction and per agent activated. No public pricing. Enterprise plan quotes require a conversation with sales. The company describes its model as "partnership-first" with dedicated Customer Success Managers and guided onboarding.
That works for steady-state hiring. But it introduces variability. A seasonal hiring spike means a cost spike. Activating five agents for a role costs more than activating two. And because costs are opaque, it's harder to benchmark during procurement.
The flat-rate subscription covers unlimited assessments. Your per-candidate cost goes down as volume goes up. Not the reverse. For teams that need to budget around fluctuating hiring needs, especially during growth phases or seasonal surges, that predictability matters. You're paying for insight, not for agent activations.
ATS Integrations and Job Descriptions
ATS Integrations and Job Descriptions
It positions itself as a layer above your ATS, the "system of intelligence" sitting on top of the "system of record." They offer 30+ ATS integrations including Ashby, Workable, Greenhouse, and SmartRecruiters. Evaluations trigger automatically when someone reaches a specific pipeline stage. It also generates AI-powered job descriptions from templates, which helps when you're posting for multiple roles.
Bryq connects directly with Greenhouse, Lever, Workday, iCIMS, and custom systems. The integration philosophy is different: it works inside your existing workflow rather than adding a new architectural layer on top. For mid-market and enterprise teams with established ATS setups, the ATS integrations are less disruptive. You pull job descriptions from your existing roles, and the AI builds the Ideal Candidate Profile from there.
It positions itself as a layer above your ATS, the "system of intelligence" sitting on top of the "system of record." They offer 30+ ATS integrations including Ashby, Workable, Greenhouse, and SmartRecruiters. Evaluations trigger automatically when someone reaches a specific pipeline stage. It also generates AI-powered job descriptions from templates, which helps when you're posting for multiple roles.
Bryq connects directly with Greenhouse, Lever, Workday, iCIMS, and custom systems. The integration philosophy is different: it works inside your existing workflow rather than adding a new architectural layer on top. For mid-market and enterprise teams with established ATS setups, the ATS integrations are less disruptive. You pull job descriptions from your existing roles, and the AI builds the Ideal Candidate Profile from there.
It positions itself as a layer above your ATS, the "system of intelligence" sitting on top of the "system of record." They offer 30+ ATS integrations including Ashby, Workable, Greenhouse, and SmartRecruiters. Evaluations trigger automatically when someone reaches a specific pipeline stage. It also generates AI-powered job descriptions from templates, which helps when you're posting for multiple roles.
Bryq connects directly with Greenhouse, Lever, Workday, iCIMS, and custom systems. The integration philosophy is different: it works inside your existing workflow rather than adding a new architectural layer on top. For mid-market and enterprise teams with established ATS setups, the ATS integrations are less disruptive. You pull job descriptions from your existing roles, and the AI builds the Ideal Candidate Profile from there.
Science and Decision-Making
Science and Decision-Making
Both platforms take science seriously, but the approaches differ.
Maki People follows a 12-step development process, from skill definition through AI-based item generation, pilot testing, and ongoing review. Their science team leans toward situational judgment tests and structured interviews over personality assessment methods, using Behaviorally Anchored Rating Scales for scoring and Differential Item Functioning for bias mitigation. The algorithms behind their LLMs go through a 10-step calibration loop comparing outputs against expert human ratings. It's a thorough process, though one that's only as durable as the underlying models, and those models change.
On the other side, the assessments are built on I-O psychology principles and validated for predictive validity. Cognitive ability, behavioral tendencies, and hard skills all feed into a single integrated profile. The AI Proficiency Assessment draws on six peer-reviewed frameworks. The proof points: 80% reduction in screening time, 3x improvement in quality of hire, and 40% drop in early turnover. Those numbers track actual hiring outcomes, not just processing speed.
The difference isn't rigor. It's what each platform is optimizing for. Their science backs autonomous agent decision-making. Bryq's science backs a single, interpretable candidate profile that your team uses to make better hiring decisions themselves.
Both platforms take science seriously, but the approaches differ.
Maki People follows a 12-step development process, from skill definition through AI-based item generation, pilot testing, and ongoing review. Their science team leans toward situational judgment tests and structured interviews over personality assessment methods, using Behaviorally Anchored Rating Scales for scoring and Differential Item Functioning for bias mitigation. The algorithms behind their LLMs go through a 10-step calibration loop comparing outputs against expert human ratings. It's a thorough process, though one that's only as durable as the underlying models, and those models change.
On the other side, the assessments are built on I-O psychology principles and validated for predictive validity. Cognitive ability, behavioral tendencies, and hard skills all feed into a single integrated profile. The AI Proficiency Assessment draws on six peer-reviewed frameworks. The proof points: 80% reduction in screening time, 3x improvement in quality of hire, and 40% drop in early turnover. Those numbers track actual hiring outcomes, not just processing speed.
The difference isn't rigor. It's what each platform is optimizing for. Their science backs autonomous agent decision-making. Bryq's science backs a single, interpretable candidate profile that your team uses to make better hiring decisions themselves.
Both platforms take science seriously, but the approaches differ.
Maki People follows a 12-step development process, from skill definition through AI-based item generation, pilot testing, and ongoing review. Their science team leans toward situational judgment tests and structured interviews over personality assessment methods, using Behaviorally Anchored Rating Scales for scoring and Differential Item Functioning for bias mitigation. The algorithms behind their LLMs go through a 10-step calibration loop comparing outputs against expert human ratings. It's a thorough process, though one that's only as durable as the underlying models, and those models change.
On the other side, the assessments are built on I-O psychology principles and validated for predictive validity. Cognitive ability, behavioral tendencies, and hard skills all feed into a single integrated profile. The AI Proficiency Assessment draws on six peer-reviewed frameworks. The proof points: 80% reduction in screening time, 3x improvement in quality of hire, and 40% drop in early turnover. Those numbers track actual hiring outcomes, not just processing speed.
The difference isn't rigor. It's what each platform is optimizing for. Their science backs autonomous agent decision-making. Bryq's science backs a single, interpretable candidate profile that your team uses to make better hiring decisions themselves.
Who Should Choose Bryq?
Who Should Choose Bryq?
Bryq fits best when the goal is quality of hire and retention, not just screening speed. Mid-market companies, enterprises, and recruiters who've felt the cost of early turnover tend to find the integrated talent assessment approach more useful than a suite of autonomous agents. It also makes more sense when your hiring process needs to scale without your costs scaling with it, and when finding the right candidates matters more than processing the most resumes.
If you're evaluating AI readiness across candidates or building a competency-first hiring strategy for the future of work, Bryq is the only assessment platform in this comparison with a validated, research-grounded AI Proficiency Assessment. That alone is worth the evaluation if your organization is serious about hiring people who can actually work with AI.
Bryq fits best when the goal is quality of hire and retention, not just screening speed. Mid-market companies, enterprises, and recruiters who've felt the cost of early turnover tend to find the integrated talent assessment approach more useful than a suite of autonomous agents. It also makes more sense when your hiring process needs to scale without your costs scaling with it, and when finding the right candidates matters more than processing the most resumes.
If you're evaluating AI readiness across candidates or building a competency-first hiring strategy for the future of work, Bryq is the only assessment platform in this comparison with a validated, research-grounded AI Proficiency Assessment. That alone is worth the evaluation if your organization is serious about hiring people who can actually work with AI.
Bryq fits best when the goal is quality of hire and retention, not just screening speed. Mid-market companies, enterprises, and recruiters who've felt the cost of early turnover tend to find the integrated talent assessment approach more useful than a suite of autonomous agents. It also makes more sense when your hiring process needs to scale without your costs scaling with it, and when finding the right candidates matters more than processing the most resumes.
If you're evaluating AI readiness across candidates or building a competency-first hiring strategy for the future of work, Bryq is the only assessment platform in this comparison with a validated, research-grounded AI Proficiency Assessment. That alone is worth the evaluation if your organization is serious about hiring people who can actually work with AI.
Who Should Choose Maki People?
Who Should Choose Maki People?
Maki People works best for high-volume frontline hiring needs where the bottleneck is recruiter bandwidth, not assessment depth. If you're processing tens of thousands of job applications per month across multiple markets and your primary goal is automating the early funnel, the agent-based model was designed for exactly that problem. The customization options, including branded landing pages and configurable agent stacks, give enterprise teams flexibility.
It's a fit for organizations comfortable with giving AI agents significant autonomous authority, and where throughput matters more than individual measurement depth. The 30+ ATS integrations, multilingual conversational capabilities, real-world scenario-based assessments, and automatic scheduling remove real friction from high-volume operations. The assessment library and test library of 300+ evaluations cover most role-specific requirements, though breadth of options doesn't always translate to depth of insight.
Maki People works best for high-volume frontline hiring needs where the bottleneck is recruiter bandwidth, not assessment depth. If you're processing tens of thousands of job applications per month across multiple markets and your primary goal is automating the early funnel, the agent-based model was designed for exactly that problem. The customization options, including branded landing pages and configurable agent stacks, give enterprise teams flexibility.
It's a fit for organizations comfortable with giving AI agents significant autonomous authority, and where throughput matters more than individual measurement depth. The 30+ ATS integrations, multilingual conversational capabilities, real-world scenario-based assessments, and automatic scheduling remove real friction from high-volume operations. The assessment library and test library of 300+ evaluations cover most role-specific requirements, though breadth of options doesn't always translate to depth of insight.
Maki People works best for high-volume frontline hiring needs where the bottleneck is recruiter bandwidth, not assessment depth. If you're processing tens of thousands of job applications per month across multiple markets and your primary goal is automating the early funnel, the agent-based model was designed for exactly that problem. The customization options, including branded landing pages and configurable agent stacks, give enterprise teams flexibility.
It's a fit for organizations comfortable with giving AI agents significant autonomous authority, and where throughput matters more than individual measurement depth. The 30+ ATS integrations, multilingual conversational capabilities, real-world scenario-based assessments, and automatic scheduling remove real friction from high-volume operations. The assessment library and test library of 300+ evaluations cover most role-specific requirements, though breadth of options doesn't always translate to depth of insight.
How Bryq Compares to Other Assessment Platforms
How Bryq Compares to Other Assessment Platforms
If you're doing a broader market evaluation, it's worth looking at how these assessment platforms compare to others. TestGorilla and Testlify take a test-library approach with credit-based cost structures. The Predictive Index focuses more narrowly on behavioral and personality assessment methods. Each has a different theory about how you identify the best candidates. The right choice depends on what your current approach is missing and what your actual requirements look like. For a broader overview of how pre-employment assessment tools work, SHRM's guide to selection assessments is a useful starting point.
If you're doing a broader market evaluation, it's worth looking at how these assessment platforms compare to others. TestGorilla and Testlify take a test-library approach with credit-based cost structures. The Predictive Index focuses more narrowly on behavioral and personality assessment methods. Each has a different theory about how you identify the best candidates. The right choice depends on what your current approach is missing and what your actual requirements look like. For a broader overview of how pre-employment assessment tools work, SHRM's guide to selection assessments is a useful starting point.
If you're doing a broader market evaluation, it's worth looking at how these assessment platforms compare to others. TestGorilla and Testlify take a test-library approach with credit-based cost structures. The Predictive Index focuses more narrowly on behavioral and personality assessment methods. Each has a different theory about how you identify the best candidates. The right choice depends on what your current approach is missing and what your actual requirements look like. For a broader overview of how pre-employment assessment tools work, SHRM's guide to selection assessments is a useful starting point.
Frequently Asked Questions
Frequently Asked Questions
What's the biggest difference between Bryq and Maki People?
Philosophy. Maki People deploys autonomous AI agents that make screening calls and final decisions on your behalf. Bryq gives your team an integrated candidate assessment built by AI, but the decisions stay with humans. If you want AI to do the work, Maki People leans that direction. If you want AI to inform better human decision-making, that's where Bryq sits.
Does Maki People have an AI Proficiency Assessment?
No. Maki People uses AI to power its agents, but it doesn't have a validated assessment for measuring candidates' skills with AI. Bryq's AI Proficiency Assessment is built on six peer-reviewed frameworks, covers five scored dimensions, and is included in all plans. For organizations trying to hire the best talent who can actually use AI effectively in real-world scenarios, that's a gap worth noting.
How do the pricing plans compare?
Maki People uses a credit-based model where you pay per candidate interaction and per agent activated. The enterprise tier requires a custom quote. Bryq runs a flat-rate subscription with unlimited evaluations. If your hiring volume fluctuates or you want predictable costs, the flat-rate model tends to be easier to manage and budget around.
Which assessment platform is better for high-volume hiring?
Depends on what "better" means for you. If the goal is automating as much of the early funnel as possible to handle large volumes of job applications, Maki People's five-agent architecture was built for that. If the goal is identifying which high-volume candidates will actually perform and stay, the integrated evaluation and quality-of-hire focus tends to deliver more value downstream, even if it requires more human involvement in screening.
Can Bryq evaluate soft skills and cultural fit?
Yes. Yes, all of it. The integrated assessment measures personality traits and behavioral dimensions alongside reasoning aptitude and hard skills, with cultural fit, problem-solving approach, and soft skills captured in the single candidate profile. There's no need for a separate behavioral evaluation or additional testing modules layered on top.
What about candidate feedback and experience?
On their side, reported satisfaction scores run 95-99%, though surveys taken during a hiring process carry inherent selection bias. Bryq's candidate experience is designed to be respectful and cohesive: one assessment, no heavy proctoring, mobile-friendly access. Completion rates stay high because the scenario-based format feels closer to real-world work than a proctored exam with webcam monitoring every 30 seconds.
What's the biggest difference between Bryq and Maki People?
Philosophy. Maki People deploys autonomous AI agents that make screening calls and final decisions on your behalf. Bryq gives your team an integrated candidate assessment built by AI, but the decisions stay with humans. If you want AI to do the work, Maki People leans that direction. If you want AI to inform better human decision-making, that's where Bryq sits.
Does Maki People have an AI Proficiency Assessment?
No. Maki People uses AI to power its agents, but it doesn't have a validated assessment for measuring candidates' skills with AI. Bryq's AI Proficiency Assessment is built on six peer-reviewed frameworks, covers five scored dimensions, and is included in all plans. For organizations trying to hire the best talent who can actually use AI effectively in real-world scenarios, that's a gap worth noting.
How do the pricing plans compare?
Maki People uses a credit-based model where you pay per candidate interaction and per agent activated. The enterprise tier requires a custom quote. Bryq runs a flat-rate subscription with unlimited evaluations. If your hiring volume fluctuates or you want predictable costs, the flat-rate model tends to be easier to manage and budget around.
Which assessment platform is better for high-volume hiring?
Depends on what "better" means for you. If the goal is automating as much of the early funnel as possible to handle large volumes of job applications, Maki People's five-agent architecture was built for that. If the goal is identifying which high-volume candidates will actually perform and stay, the integrated evaluation and quality-of-hire focus tends to deliver more value downstream, even if it requires more human involvement in screening.
Can Bryq evaluate soft skills and cultural fit?
Yes. Yes, all of it. The integrated assessment measures personality traits and behavioral dimensions alongside reasoning aptitude and hard skills, with cultural fit, problem-solving approach, and soft skills captured in the single candidate profile. There's no need for a separate behavioral evaluation or additional testing modules layered on top.
What about candidate feedback and experience?
On their side, reported satisfaction scores run 95-99%, though surveys taken during a hiring process carry inherent selection bias. Bryq's candidate experience is designed to be respectful and cohesive: one assessment, no heavy proctoring, mobile-friendly access. Completion rates stay high because the scenario-based format feels closer to real-world work than a proctored exam with webcam monitoring every 30 seconds.
What's the biggest difference between Bryq and Maki People?
Philosophy. Maki People deploys autonomous AI agents that make screening calls and final decisions on your behalf. Bryq gives your team an integrated candidate assessment built by AI, but the decisions stay with humans. If you want AI to do the work, Maki People leans that direction. If you want AI to inform better human decision-making, that's where Bryq sits.
Does Maki People have an AI Proficiency Assessment?
No. Maki People uses AI to power its agents, but it doesn't have a validated assessment for measuring candidates' skills with AI. Bryq's AI Proficiency Assessment is built on six peer-reviewed frameworks, covers five scored dimensions, and is included in all plans. For organizations trying to hire the best talent who can actually use AI effectively in real-world scenarios, that's a gap worth noting.
How do the pricing plans compare?
Maki People uses a credit-based model where you pay per candidate interaction and per agent activated. The enterprise tier requires a custom quote. Bryq runs a flat-rate subscription with unlimited evaluations. If your hiring volume fluctuates or you want predictable costs, the flat-rate model tends to be easier to manage and budget around.
Which assessment platform is better for high-volume hiring?
Depends on what "better" means for you. If the goal is automating as much of the early funnel as possible to handle large volumes of job applications, Maki People's five-agent architecture was built for that. If the goal is identifying which high-volume candidates will actually perform and stay, the integrated evaluation and quality-of-hire focus tends to deliver more value downstream, even if it requires more human involvement in screening.
Can Bryq evaluate soft skills and cultural fit?
Yes. Yes, all of it. The integrated assessment measures personality traits and behavioral dimensions alongside reasoning aptitude and hard skills, with cultural fit, problem-solving approach, and soft skills captured in the single candidate profile. There's no need for a separate behavioral evaluation or additional testing modules layered on top.
What about candidate feedback and experience?
On their side, reported satisfaction scores run 95-99%, though surveys taken during a hiring process carry inherent selection bias. Bryq's candidate experience is designed to be respectful and cohesive: one assessment, no heavy proctoring, mobile-friendly access. Completion rates stay high because the scenario-based format feels closer to real-world work than a proctored exam with webcam monitoring every 30 seconds.
See How Bryq Assesses Your Candidates
See How Bryq Assesses Your Candidates
If you're evaluating assessment platforms and want to see what an integrated, AI-powered candidate profile looks like in practice, Bryq's team can walk you through a live demo built around your actual roles and hiring needs.
If you're evaluating assessment platforms and want to see what an integrated, AI-powered candidate profile looks like in practice, Bryq's team can walk you through a live demo built around your actual roles and hiring needs.
If you're evaluating assessment platforms and want to see what an integrated, AI-powered candidate profile looks like in practice, Bryq's team can walk you through a live demo built around your actual roles and hiring needs.
Ready to see Bryq in action?
Start hiring based on real data.
Ready to see Bryq in action?
Start hiring based on real data.
Ready to see Bryq in action?
Start hiring based on
real data.