Strong grasp of DDD and subdomain boundaries.
“identifying boundaries by subdomain”
Decide with evidence,
not memory.
interview-companion · live
You: Can you walk me through how you'd approach a monolith-to-microservices migration?
Candidate: I'd start by identifying boundaries by subdomain — domain-driven design.
Candidate: First service extracted is usually the least-coupled one, not the most critical.
You: How would you handle data consistency across services?
Candidate: Outbox pattern + eventual consistency. Saga when orchestration is needed.
Familiar with outbox pattern and saga for cross-service coordination.
Ask for concrete saga examples in production.
How it works
Three steps. Zero friction on the call.
Start recording with a shortcut. What appears on your screen while the interview runs is information — not notes you'll have to rewrite later.
01 · Capture
Mic + system audio, no invisible bots.
The native app captures your microphone and system audio (ScreenCaptureKit on macOS, WASAPI loopback on Windows). The candidate sees a normal call. Zero plugins, zero extensions.
02 · Transcribe
Live streaming with failover between providers.
Deepgram Nova-3 by default, with automatic failover to AssemblyAI and RevAI. Per-channel diarization — you know who said what without training voice profiles. Sub-second latency.
03 · Evaluate
Insights on the fly, scorecard when you close.
As you speak, the AI flags signals (red flags, green flags, follow-ups) and builds a structured scorecard. When the interview ends, you export the full report to your ATS.
SCORECARD
Hiring decisions,
backed by evidence.
When the interview ends we generate a structured scorecard by dimension — every score comes with verbatim candidate quotes. It's not an opinion: it's what they said, in context.
- Per-role configurable dimensions (not a generic template)
- Strengths and weaknesses with literal quotes
- Recommendation: strong_hire · hire · maybe · no_hire
- Direct export to Greenhouse, Lever, or your ATS
Senior Backend · Mid-level
Lautaro M.
Technical8/10
Communication7/10
Strategic9/10
Leadership6/10
Attitude9/10
English8/10
Strengths
- Fluid grasp of DDD for decomposing monoliths.
“identifying boundaries by subdomain — domain-driven design”
- Familiar with outbox pattern and saga for distributed coordination.
Privacy
Native means your data doesn't wander.
PII redacted before the LLM
Emails, phone numbers, IDs — all of it passes through a sanitizer before reaching the model.
Audio is never persisted
Stream → STT → discard. We do not store audio on disk or in the cloud. Only the final transcript, scoped per org.
Per-organization isolation
Every DB query is filtered by org_id at the app layer. Real multi-tenant, not shared schemas.
AI structures the evidence. Your team decides.
Pricing
Simple. No "contact sales".
Solo
Freeduring the beta
So you can try the app in your own interviews.
- Native macOS + Windows app
- Up to 20 interviews / month
- Live transcription + insights
- Structured scorecards
- Email support
Team
USD 24/mo per seat
For hiring teams with shared workflows.
- Everything in Solo, no limits
- Shared per-org workspaces
- Per-role scorecard templates
- Greenhouse / Lever integration (soon)
- Priority support
Frequently asked
The questions you're about to have.
Clear evidence for
better hiring.
Download, sign in, done. No credit card during the beta.