AI is writing your code.SenseLab keeps the record.
The trust layer for AI-assisted software delivery — lineage, provenance, and accountability from your developer's IDE to production.
AI attribution
Know which model wrote which line, and what it did in production.
Merge-to-incident
The only tool connecting PR review to runtime impact.
SBOM + AIBOM
CycloneDX with AI provenance. Compliance ready at every release.
Market position
The gap nobody fills.
Nobody gives you the complete trust record. SenseLab does.
AI Code Review
PR Review Tools
Analyze pull requests, flag issues, suggest improvements. But they create no lineage. No record of who wrote what, which model contributed, or how a change was really made. Reviewers see the diff — not the story behind it.
Merge-to-Incident
Lineage Layer
← The gap nobody fills →
AIOps / SRE
Incident Response
Monitor production, fire alerts, surface anomalies. Purely reactive — they only fire after something breaks. Meanwhile, the risky change, the security hole, the AI-generated code that will take down the app — it was already merged.
The problem today
Every stage knows something.
Nobody knows the whole story.
IDE captures the session
GitHub knows the PR
CI knows the build
Registry holds the artifact
Cloud knows the deploy
Datadog sees the symptom
Incident lives in PagerDuty
Discussion in Slack
Tickets in Jira
When something breaks, nobody can prove what changed — or what AI wrote it.
One continuous trail
SenseLab connects all of it.
From the developer’s IDE to production impact and back.
Local Dev
AI + human activity captured
Pull Request
Linked to session + AI attribution
Review + AIBOM
Risk, provenance, SBOM generated
Build & Artifact
Evidence bound at build time
Deploy
Resource & availability tracked
Runtime Impact
Regressions traced to code
Evidence Pack
Audit trail assembled
SenseLab turns disconnected events into one continuous trail.
Know what changed, how it was built, what AI contributed, and what happened next — with proof at every step.
The continuous trail
From creation to consequence.
SenseLab connects every stage of the change lifecycle into one traceable, verifiable story.
Local Dev
AI + human
Pull Request
Linked session
Review
Risk + AIBOM
Build & Artifact
Evidence bound
Deploy
Health tracked
Runtime
Impact traced
Evidence
Pack assembled
Action
Loop closed
What SenseLab leaves behind
Change trail
Every commit linked from developer session to production — including AI tool, model, and contribution %.
Release evidence
SBOM + AIBOM + policy results assembled automatically at every artifact, before deploy.
AI attribution
Which tools wrote which lines, which model, how much human review covered them — per release.
Incident trace
Runtime regressions traced back to the exact code change, artifact, and AI-generated block.
Audit trail
Structured, exportable proof for compliance auditors, security teams, and post-mortems.
Not another point tool. A connected decision layer for shipping and running software.
Works with your existing stack
Follow the trail
From IDE to incident.
Every step AI-attributed.
Sarah Chen opened Cursor at 5:02 PM. Six AI-assisted code blocks, one merged PR, and one production incident later — SenseLab has the complete trail. Every change sourced. Every risk flagged. Every anomaly explained.
Local Dev Session — sarah.chen
The story starts before the PR.
SenseLab captures how the change was created — including AI-assisted work — from the developer's environment.
Tool
Cursor
AI model
Claude Sonnet
Session
47 min
Files touched
2
Contribution attribution
Session timeline
checkout-service / feat/retry-handler
Retry handler scaffold — 12 lines
Modified timeout constant: 5000 → 15000
Error boundary + MAX_RETRIES logic
retryCheckout() function — 8 lines
PR #247 — checkout-service
Lineage begins at creation. Before the PR exists, SenseLab knows which AI tools contributed, how much was accepted vs modified, and which files were touched.
The story starts before the PR. SenseLab captures the developer session — which AI tools were used, how many suggestions were accepted vs modified, and which files were touched. This is where lineage begins.
Ask the guide
Use Cases
What are you trying to prevent?
The same continuous trail — four different buyer problems.
By Role
The same trail. Different lens.
SenseLab serves every role in the software delivery loop.
Understand AI-assisted changes before and after merge.
Know what AI contributed
SenseLab tracks which AI tools wrote which lines in your session — and follows that attribution through the PR, artifact, and into production.
Catch risky patterns before review
Get a pre-merge signal on whether your change touches timeout behavior, retry logic, or other historically incident-prone patterns.
See your release outcome
After deploy, SenseLab shows whether your change correlated with any runtime anomaly — without waiting for SRE to ping you.
Plans
Unlock the trail, stage by stage.
Start free with AI Lineage — add Review and Release as your team needs them.
Free
no credit card required
Understand where your code came from.
Covers
$29
per user / month
Ship with confidence before merge.
Covers
$149
per month · requires Review
Connect deploy to production impact.
Covers
$499/mo add-on · requires Review + Release
Start tracking before something breaks.
Install the CLI, enable lineage, and every release from that moment has a full trail — from developer session to production impact.
Free plan available. No credit card required.
