01
Candidate Works
Candidates complete a real-world engineering task using their usual development tools, including AI.
CodeGitHubAITests
Engineering Talent Evaluation
See How Engineers
Actually Work.
Go beyond the final submission. See how candidates think, build, and work with AI backed by evidence from their development process.
How It Works
From Development Activity
to Hiring Evidence.
Dipin captures how candidates approach real engineering tasks and turns their development process into evidence your team can evaluate.
02
Dipin Analyzes
Dipin analyzes how candidates build from code changes and iterations to technical decisions and AI usage.
DecisionsIterationsAI Usage
03
You Get the Evidence
Get an evidence-backed report showing each candidate's strengths, risks, and engineering competencies and the evidence behind them.
CompetenciesEvidenceReport
Assessments
Assess Candidates in the Way
They Actually Work.
See how candidates solve realistic work with AI—not what they memorized for a test.
Dipin AI Workspace
01:24:32
Churn by Plan
Last 90 days · 7,900 users
3 sources joined
SegmentUsersChurnAvg. Usage
Free4,8208.2%3.1
Starter2,14014.7%5.8
Pro9405.1%12.4
Candidate Note
Starter churn is 2.9× higher than Pro. Check signup cohort and usage frequency before concluding why.What We Evaluate
More Than Code Quality.
Understand the engineering judgment behind the final submission across six core dimensions.
Engineering Competency Framework
Spec Compliance
Does the solution actually solve the problem?
Data Modeling
Is data structured with intention and integrity?
Reliability & Safety
How does the engineer handle failure and edge cases?
Maintainability
Can others understand, maintain, and extend the work?
Efficiency
Are technical trade-offs made appropriately?
AI Collaboration
Does the engineer use AI with independent judgment?
Evidence-Backed Reports
Every Score Comes
With Evidence.
Don't just see the score. Understand what happened during development and why it matters.
D
Engineering Insight Report
Candidate assessment · Completed
Overall Engineering Score
80/ 100
Core Competencies/ 5
Spec Compliance4.4
Data Modeling3.9
Reliability & Safety4.1
Maintainability3.8
Efficiency3.7
AI Collaboration4.2
AI Collaboration
Independent4.2 / 5
Reviews and verifies AI-generated solutions before adoption.
Reliability & Safety
Handles failures before they become bugs.
Evidence
Candidate identified an unhandled collision case in the AI-generated implementation and revised the solution before submission.
AI Session #18routes.tsCommit a82f1c
Why It Matters
Demonstrates proactive edge-case reasoning and independent verification rather than accepting generated code as-is.
Key Strength
Independent verification
Area to Explore
Limited performance validation
See How Your Candidates
Actually Work.
Turn development activity into evidence your hiring team can trust.