Every call,
measured.
Recordings, transcripts, sentiment, outcomes — captured automatically. Spot drift, prove ROI, ship improvements in days not quarters.
Observability primitives
See what happened.
Fix what didn't.
Voice ops without observability is hope-driven engineering. Finn ships the entire instrumentation layer with the platform.
Auto-transcribed calls
Every conversation captured, indexed, and searchable. Speaker diarisation, timestamps, redactions for PII.
Post-call analysis (PCA)
Outcome tags, intent extraction, sentiment, dispute flags — generated automatically per call. No human in the loop.
Built-in eval suite
Score every call against your custom rubric. Adherence, tone, accuracy, compliance — track them call-over-call.
Drift detection
Catch the silent regression. We alert when model behaviour shifts, vocabulary changes, or outcomes slide.
Live conversation playback
Audio sync'd with transcript and PCA highlights. Replay any moment, share with one click.
Real-time dashboards
Today's outcomes, sentiment heatmap, agent-level performance — live, not yesterday's.
every call, instrumented
Auto-transcribed. Speaker-diarised. Searchable.
The first job of observability is full coverage. Finn captures every audio call, generates a speaker-aware transcript, redacts PII, and indexes the lot — usable in under sixty seconds from call hang-up.
- 100% transcript coverage, no manual upload
- Speaker diarisation + timestamp anchors
- Auto-PII redaction (card, SSN, custom regex)
- Full-text search across all transcripts
post-call analysis
Outcomes, sentiment, and intent — auto-tagged.
Every call ships with a structured outcome record. Sentiment delta, intent classification, dispute flags, hand-off reasons — generated by the model, not by human QA. Wire it into your CRM and act tomorrow.
- Outcome taxonomy you define, model-enforced
- Sentiment scored per turn + per call
- Auto-flagged exceptions for human review
- PCA payload pushed via webhook to your stack
evals + drift
Score the agent against your rubric. Continuously.
Build a custom eval suite — adherence, tone, accuracy, compliance — and Finn scores every call. Drift detection alerts when behaviour shifts. Closed-loop feedback into prompt + workflow updates.
- Custom rubrics, LLM-judge backed
- Adversarial pre-deployment tests
- Production drift detection + alerts
- Human feedback feeds back into the system
Outcome-first
You can't improve
what you can't see.
Finn doesn't just run the calls. It tells you which ones converted, which ones leaked, and what to change tomorrow.
Audited + compliant
More platform