Level the playing field with processes rooted in science and driven by data

Close the opportunity gap for underrepresented talent with an inclusive, scalable, and efficient automated behavioral skills assessment.

Reducing human bias in the hiring process is no easy feat. Knockri can get you there.

Implement performance-predicting structured candidate selection practices that scale and improve diversity. Knockri operates on principles of transparency, careful data selection, bias reduction, verification, and validation.

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Validated by I/O Psychology

Every question on every assessment is verified and validated by our Science Team for the most accurate results.

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No historical data

Our AI is trained on objective data that predicts performance, not on historical data that has bias baked-in.

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Evidence-based scoring

Candidates are transparently evaluated based on the content of their answers.

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Assessments are equitable and optimized for blind and low-vision candidates using assistive technologies.

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Bias filter for recruiters

Further mitigate bias by viewing candidate results by ID, not by names.

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Objective AI

Our AI improves the efficiency and consistency of shortlisting without bias or human error.

Having the right candidate selection procedure matters

Many selection procedures are flawed when it comes to finding a balance between assessment validity and candidate diversity

Use an auto-populated assessment

Build your assessment around one of our more-than 45,000 pre-created job personas in just a few clicks.

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How SBIs compare to other evaluation methods:


More predictive than looking at previous experience


More predictive than personality tests or unstructured interviews


Better at achieving diversity than cognitive ability tests

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Making structured behavioral interviews scalable & affordable

Structured behavioral interviews are the most accurate in predicting performance while mitigating adverse impact, but are traditionally very costly and time-intensive.

Knockri takes all the benefits of structured behavioral interviews and makes them accessible at scale. Our platform automates interviews and scoring so you can deploy a well-designed and accurate evaluation process at a fraction of the cost.

Equal opportunity for all applicants no matter your use case

Enterprise Hiring
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Campus Recruitment
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Talent Management
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How Knockri helped the Department of National Defence increase racial & gender diversity by XX%

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Want to dive deeper into equitable hiring? We've got you covered:

The Science of Knockri’s AI-Based Selection Procedures

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The Knockri Approach to Legal Defensibility

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Inclusive Hiring etc.

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Yes! Knockri can integrate with any ATS. You will build your assessment in our dashboard and link it to your own internal requisitions. From there, you can continue working with your ATS like you normally would.  

No problem! Knockri’s Recruiter Dashboard can fully function as a stand-alone product, meaning you don’t need an ATS to use it. 

We help reduce unconscious bias during the hiring process in three specific ways: 

  1. Our magic quadrant research methodology shows that behavioural assessments increase diversity without sacrificing performance prediction in comparison to other assessment types, such as cognitive ability assessments. Although behavioural assessments can be expensive and time-consuming, we’ve automated the process which allows you to use them earlier on in the recruitment process instead of other selection procedures known to negatively impact diversity.  
  2. We reduce recruiter bias by ensuring every candidate gets exactly the same assessment. We found that unstructured interviews allow for human bias to creep its way into the selection process. By using a structured behavioural interview process, we use this automation to ensure that none of your typical bias is present, which gives every candidate a fair chance in the selection process. 
  3. We train our machine learning to score candidates through objective data that has not been subject to human biases. In data science, there is a general understanding of what happens when the data used to train models is biased — garbage in, garbage out.  Since machine learning models learn from data that we feed to them, any bias that exists in that data will translate through the use of machine learning. This is why we ensure our machine learning is only taught objective data that hasn’t been subject to human biases, and does not include historical hiring patterns. 

We provide support 24 hours a day, 7 days a week to all candidates. For inquiries submitted between 9am – 9pm (EST) Monday to Friday, technical issues are resolved within the hour. Outside of those hours, our team will resolve the issue within 3 hours. This includes weekends (Saturday & Sunday).