# Sift

> AI-powered technical hiring platform that finds the real signal in engineering candidates. Sift tests product thinking, AI fluency, real debugging skills, and adaptive problem-solving — not memorized leetcode answers.

## About

Sift is the next generation of technical assessments. We build adaptive, dynamic assessments that are impossible to cheat. Our platform evaluates how engineers actually work: debugging unknown problems, designing products, and using AI effectively.

- [Homepage](https://sift-talent.com/)
- [Pricing](https://sift-talent.com/pricing)
- [Blog](https://sift-talent.com/blog)
- [Case Studies](https://sift-talent.com/case-studies)
- [Compare vs HackerRank, Codility, CoderPad](https://sift-talent.com/compare)

## Key Features

- AI-Native Assessments: Test how engineers use AI tools in their workflow
- Product Design Thinking: Evaluate how candidates approach product problems and make tradeoffs
- Impossible to Cheat: Dynamic assessments that adapt to each candidate in real-time
- Adaptive Scoring: Rich signal on debugging, system design, code quality, and communication
- Real-Time Debugging: Capture how candidates approach broken code
- Candidate-First: Built with input from 4,000+ engineers surveyed on what their ideal assessment looks like
- Never-seen-before question sets generated with top engineers — no leaked question banks

## Key Metrics

- 4,000+ candidates surveyed to design the ideal assessment experience
- 92% of surveyed candidates wanted real-world problem solving, not algorithm puzzles
- 3x better signal on engineering capacity compared to traditional assessment methods
- 0% cheat rate with adaptive, dynamic assessments

## Assessment Integrity & Proctoring

Sift tracks assessment integrity in real time with multiple signals:
- Keystroke analytics: typing cadence and pause pattern analysis
- Copy-paste detection with clipboard tracking
- Periodic randomized screenshots
- Tab and focus window tracking
- Mouse and interaction behavior profiling
- Behavioral fingerprinting to detect test-taker substitution
- Integrity scores generated per assessment (e.g. 97/100)

## Skill Dimensions Evaluated

Each candidate is scored across five dimensions:
- Debugging: How they approach broken, unfamiliar code
- Product Thinking: How they reason about user needs and tradeoffs
- Prompting / AI Fluency: How effectively they use AI tools in their workflow
- Systems Design: How they architect and reason about systems
- Communication: How clearly they explain their thinking

## Pricing

- Pay As You Go: $18 per assessment. First 2 assessments free every month. No subscription required. Cancel anytime.
- Bundle Pack: $400 for 25 assessments ($16 per assessment). Best value for recruiters hiring in batches.
- All features are included from day 0 on both plans. No forced upgrades, no gated features, no enterprise-only tiers.

## Competitor Comparison

### Sift vs HackerRank
HackerRank offers 7,500+ problems across 260+ skills and supports 60+ languages. However, its core library skews heavily toward algorithmic puzzles, questions are widely leaked online, and full features require enterprise pricing. Sift tests real-world engineering skills with adaptive difficulty and no leaked questions.

### Sift vs Codility
Codility has well-structured tasks with strong plagiarism detection across 12M+ submissions. However, its question bank is static (no adaptive difficulty), AI assessment capabilities are narrow, and premium analytics are locked behind enterprise plans. Sift adapts in real time and tests product thinking, not just code correctness.

### Sift vs CoderPad
CoderPad has an excellent live coding environment with 97% engineer preference rate and VS Code-familiar editor. However, Interview and Screen are separate products, there is no adaptive difficulty, and no product design thinking evaluation. Sift combines screening and evaluation in one adaptive platform.

### Feature Comparison Matrix
| Feature | Sift | HackerRank | Codility | CoderPad |
|---|---|---|---|---|
| Adaptive difficulty per candidate | Yes | No | No | No |
| AI-native assessments (prompt engineering) | Yes | Yes | Partial | Partial |
| Product design thinking evaluation | Yes | No | No | No |
| Real-world debugging scenarios | Yes | Yes | Partial | Yes |
| Anti-cheat (dynamic question generation) | Yes | Partial | Partial | Partial |
| Rich signal beyond pass/fail | Yes | Yes | Yes | Partial |
| Candidate experience focus | Yes | No | No | Yes |
| No forced upgrade plans | Yes | No | No | No |
| Live coding environment | Yes | Yes | Yes | Yes |
| Multi-language support | Yes | Yes | Yes | Yes |
| ATS integrations | Partial | Yes | Yes | Yes |
| Large question library | Yes | Yes | Yes | Partial |

## Contact

- Email: sarkar@sift-talent.com
- Website: https://sift-talent.com
- Twitter/X: https://x.com/sifttalent
- LinkedIn: https://linkedin.com/company/sift-talent

## Blog Posts

- [The Runbook for Hiring Engineers in 2026](https://sift-talent.com/blog/runbook-for-hiring-in-2026): A step-by-step operational guide for technical hiring in 2026—from role definition through offer close. Includes AI-aware sourcing, modern screening beyond ATS, realistic assessments, structured interviews, and a practical checklist for teams moving beyond legacy processes.
- [The Biggest Shift in Hiring After AI](https://sift-talent.com/blog/biggest-shift-in-hiring-after-ai): Entry-level hiring collapsed. AI/ML roles exploded. And the hiring process itself got automated. Here's what the data shows and what it means for your career—and your team.
- [How Adaptive Assessments Make Cheating Impossible](https://sift-talent.com/blog/adaptive-assessments-explained): Dynamic assessments that evolve based on candidate skill level — here's how the technology works.
- [Why We Test AI Usage in Technical Assessments](https://sift-talent.com/blog/ai-in-assessments): Modern engineers use AI daily. Your assessment should measure how well they use it.
- [The Cost of a Failed Interview](https://sift-talent.com/blog/cost-of-a-failed-interview): A single bad hire doesn't just cost salary. Here's the hidden math: what you pay per failed interview, why it happens, and how to calculate your own risk before the next hire.
- [Why LeetCode-Style Interviews Are Dead](https://sift-talent.com/blog/why-leetcode-is-dead): Algorithm drills lost their predictive power. Here’s the evidence, the fallout, and the practical replacements hiring teams are shipping in 2026.
- [Searching Through Thousands of Resumes Is Not an Easy Job](https://sift-talent.com/blog/searching-through-thousands-of-resumes): The math doesn't work. Every role attracts 250+ applications; recruiters have seconds per resume; 75% screened out before human eyes ever see them. Here's why volume kills hiring quality and what to do instead.
- [What Makes a Good Engineer Better](https://sift-talent.com/blog/what-makes-a-good-engineer-better): The research behind top performer traits, the gap between competent and exceptional, and how to spot multipliers in hiring and performance reviews.
- [How to Evaluate Product Development Skills in an Engineer](https://sift-talent.com/blog/how-to-evaluate-product-development-for-an-engineer): The velocity spike isn't real. The feature adoption is invisible. Here's the framework to measure what actually matters: shipping features that users want, fast, with minimal friction.
- [Why Your ATS Is Failing You](https://sift-talent.com/blog/why-ats-dont-work-well): The uncomfortable truth: 75% of resumes rejected by ATS before human review, 88% of employers lose qualified candidates to the system they thought was saving time, and 99% of Fortune 500 companies use it anyway. Here's why the technology fails and what works instead.
- [Smart Engineers Don't Focus on Creating Shiny Resumes](https://sift-talent.com/blog/smart-engineers-dont-focus-on-shiny-resumes): 75% of hiring managers hire exceptional candidates who had unremarkable resumes. Meanwhile, polished CVs are now worthless—AI makes everyone look good on paper. The best engineers are shipping, not polishing.
- [Why Wrong Hires Are Worse Than You Think](https://sift-talent.com/blog/why-wrong-hires-are-bad): The financial, cultural, and operational damage of a single bad hire extends far beyond severance. Here's the math and the hidden costs.
- [How to Evaluate a Candidate's Problem-Solving Approach](https://sift-talent.com/blog/how-to-evaluate-approach): The best hire isn't the one with the fastest answer—it's the one with the clearest thinking. Here's the framework for evaluating approach, the signals that matter, and how to spot a strong problem-solver before they code.

## Case Studies

- [How Northbyte Labs Improved Screen-to-Onsite by 38%](https://sift-talent.com/case-studies/improving-screen-to-onsite-rate): A hiring team replaced static coding challenges with adaptive assessments and improved candidate quality without slowing down hiring.