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Technical hiring,
finally intelligent

AI that screens and interviews engineers — probing real experience, adapting in real time, and generating a scored report before you even open your calendar.

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15 min
to screen a candidate
3 rounds
DSA, design, projects
0
repeated questions ever
100%
calibrated to your JD
Trusted by
Live demo

Watch it think in real time

Sharingan AI doesn't just ask questions. It listens, evaluates the answer, and decides whether to probe deeper or move on — just like a seasoned interviewer would.

sharingan-ai — screening interview · project discussion · 15 min
SYSTEM   JD parsed · Founding Engineer, B2B SaaS · must-haves: end-to-end ownership, zero-to-one experience
AI       Tell me about a product or feature you built entirely from scratch. What was the problem, and how did you decide on the approach?
CANDIDATEI built a real-time notifications system at my last startup. We were getting complaints about missed alerts, so I designed a WebSocket-based push system.
AI       Why WebSockets specifically — what alternatives did you consider, and what made you rule them out?
CANDIDATEWe looked at polling and SSE. Polling felt too heavy on our infra. SSE is one-directional. WebSockets gave us bidirectional, lower latency.
AI       You mentioned "heavy on infra" — what did that actually mean in your context? What were the constraints?
SYSTEM   Adaptive probe triggered · verifying ownership depth, not surface-level knowledge
Interview rounds

Three rounds.
One system.

Each round surfaces a different kind of signal. Pick the ones that matter for the role you're hiring.

ROUND 01

Screening

15 minutes of focused project discussion. Validates whether candidates actually did what their resume says — ownership, end-to-end thinking, and real decisions made under pressure.

15 min fixed project discussion adaptive probing JD-grounded
// SCREENING PROBE EXAMPLE
"Walk me through a product you owned end-to-end. What were the hardest trade-offs you made?"
→ opening question · grounded in JD responsibility: "end-to-end ownership"
"You said you 'owned' the backend — did that include deployment and on-call? What broke first?"
→ probe triggered · verifying actual ownership vs stated ownership
✦ 2 targeted probes generated from a single answer
ROUND 02

Data structures
& algorithms

Calibrated to experience level and complexity tier. Not just "did they solve it" — but why this approach, what are the trade-offs, how does it scale under real load.

entry → expert easy → super hard fresh questions reasoning probes
// DSA PROBE EXAMPLE
"Given a stream of events, find the top K most frequent in the last N seconds. How would you approach this?"
→ main question · hard · senior level
"You chose a sliding window — what's the memory complexity and how does it behave at 100K events/sec?"
→ trade-off probe · triggered by candidate's approach
✦ Probes generated from candidate's specific solution path
ROUND 03

System design

Open-ended design matched to your company stage and tech stack. Probes failure modes, scale bottlenecks, and real architectural decisions — not just the happy path everyone rehearses.

stage-calibrated tech stack aware failure mode probing scalability focus
// SYSTEM DESIGN PROBE EXAMPLE
"Design a notification system for 10 million users. Walk me through your architecture."
→ main question · enterprise stage · system design
"Your queue falls 5 minutes behind during peak — what's your degraded mode and how do users find out?"
→ failure probe · triggered by mention of message queue
✦ Adapts based on company stage selected by recruiter
What makes it different

Built for signal,
not just screening.

Most AI interview tools ask questions. Sharingan AI listens to the answers and decides what to ask next.

ADAPTIVE PROBING
Follows the thread
When a candidate says something interesting — or evasive — Sharingan AI digs deeper. Every answer shapes the next question.
"Why that approach specifically? What did you try before landing on it?"
"You mentioned scale — what does that mean in numbers for your context?"
ANTI-GAMING
Never the same question twice
Pulls from a repository, external sources, and AI-generated questions. Candidates can't prep for it. Your bar stays honest.
∞
unique question paths
JD-GROUNDED
Every question ties to a responsibility
Skills can be faked. Lived experience can't. Sharingan AI grounds questions in the actual responsibilities from your job description.
CONTEXT MEMORY
Rounds build on each other
Screening context flows into the full interview. No repetition, no starting over — just deeper evaluation every step.
AI SETUP GUIDANCE
Guided config at every step
Not sure which complexity tier to pick? Sharingan AI suggests the right settings based on the JD and explains why — with full recruiter control.
SCORED REPORTS
Signal, not noise
Every session generates a scored evaluation with per-question ratings, strengths, weaknesses, and a hire / maybe / reject recommendation.
100
point evaluation score
VOICE-FIRST
Feels like a real interview
Candidates speak their answers. AI questions are read aloud. The experience is conversational — not a typed form — which surfaces how people actually think under pressure.
How it works

Set up in minutes.
Insights that last.

01

Upload your JD

Paste your job description. AI extracts must-have responsibilities, key skills, and role expectations — then suggests your interview settings.

02

Configure the round

Choose screening or full interview. Pick round type, experience level, and complexity. AI guides every choice with reasoning based on your JD.

03

Send to candidates

Share a link. Candidates take the interview at their own pace. Adaptive probing runs automatically — no recruiter involvement needed.

04

Review the report

Get a scored evaluation with a full transcript, per-question ratings, strengths, weaknesses, and a final recommendation to download.

JD PARSING
Must-haves extracted
End-to-end ownership · Zero-to-one experience · System design at scale
AI SUGGESTION
Recommended: Screening first
Founding role → validate ownership before deep technical rounds
REPORT PREVIEW
Score: 84/100 · Recommendation: Hire
Strong end-to-end ownership demonstrated across 3 examples. System thinking evident. Weak on distributed systems trade-offs — flag for SD round.
Early feedback

What teams are saying

"We cut first-round screening time from 3 hours to 20 minutes per candidate. The probing questions caught things we'd have missed in a normal screen."

SR
Shruti R.
Engineering Lead, Series B startup

"The system design questions adapt to the candidate's answers — it's the closest thing I've seen to an AI actually interviewing instead of just quizzing."

MK
Marcus K.
CTO, B2B SaaS company

"Finally something that checks if candidates actually built what they claim. The ownership probes are spot-on for finding founding engineers."

AP
Ananya P.
Recruiter, early-stage fund portfolio
FAQ

Common questions

How does the AI avoid asking repeated questions to different candidates?
Sharingan AI uses a three-source question strategy: a curated repository, dynamically fetched questions from external sources, and AI-generated questions unique to each session. Even if two candidates get the same base topic, the follow-up probes branch based on their specific answers — making every path unique.
Can candidates game it by practicing with AI tools?
The adaptive probing makes gaming extremely hard. Even if a candidate memorises an answer, the AI immediately follows up with "why that approach specifically?" or "what would break first at scale?" — questions that require genuine experience to answer credibly. Surface-level rehearsed answers get exposed quickly.
How does the AI calibrate question difficulty to my role?
When you set up an interview, Sharingan AI reads your JD and suggests the right configuration — company stage, role seniority, experience level, and complexity tier. Each setting adjusts what questions are asked and how deeply the AI probes. A founding engineer interview at a 5-person startup looks very different from a staff engineer interview at FAANG.
Does screening context actually carry forward to the full interview?
Yes — when a candidate moves from screening to a full interview round, Sharingan AI loads the screening report and uses it to calibrate. If the candidate showed strong system thinking in screening, the full round pushes harder. If there were gaps, those areas get revisited with more targeted questions.
Is the interview voice-based or text?
Voice-first. AI questions are read aloud using natural text-to-speech. Candidates speak their answers, which are transcribed in real time. This creates a more natural interview feel — and often surfaces how candidates think under actual conversational pressure, which typed forms don't capture.

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