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Overview

SenseLab is set up in stages. Each step unlocks more visibility — start with sign up and lineage, then layer in Review and Release as your team grows into them.

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Step 1 — Sign up

Create your SenseLab account via the CLI or directly through the dashboard.

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Step 2 — Enable AI Lineage

Navigate to the directory where your code lives (cloned from git) and run: 
sense-cli lineage enable
That’s it. SenseLab starts sending telemetry to your dashboard immediately. Head to the Dashboard to see your first data — AI attribution, model usage, team coverage, and session activity.
AI Lineage is free forever. No connectors or agents required. See the AI Lineage page for a full breakdown of what’s tracked.

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Step 3 — Connect your systems

To unlock Review and Release agents, you need to connect SenseLab to your source systems. Go to Settings → Connectors in the dashboard.

GitHub

Required for Review agents. Connects SenseLab to your repositories so it can analyze pull requests, track AI contribution, and generate AIBOM at review time.

AWS

Required for Release agents. Connects SenseLab to your AWS environment to track deployments, correlate releases to infrastructure events, and monitor runtime impact.

Google Cloud

Required for Release agents. Connects SenseLab to GCP to track deployments and trace production incidents back to the AI-generated code that caused them.

Additional Connectors

GitLab, Jira, Slack, Kubernetes, Datadog, and more are on the connectors page. You can also join the Discord to request additional integrations.
To add a connector:
  1. Go to Settings → Connectors in the dashboard
  2. Select the system you want to connect
  3. Follow the OAuth or API key flow to authorize access
  4. SenseLab confirms the connection

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Step 4 — Create Review agents

Review agents require the Review plan ($29/user/month) and a GitHub connector configured in Step 3.
Review agents attach to your repositories and automatically analyze every pull request — surfacing code improvements and fixes required, AI contribution, risk score, dependency changes, and AIBOM before anything merges. To create a Review agent:

Review Agent

Requires: GitHub connector, Review plan
  1. Go to Agents → New Agent in the dashboard
  2. Select Review as the agent type
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  3. Choose the tool and repositories the agent should watch.
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  4. Set policies — which type of reviews you want the agent to perform, notification rules, and more.
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  5. Click Create Agent
  6. Head to the Github Marketplace, install the SenseLab app, and connect it to the same repo you assigned to the Review agent you just created. The agent runs automatically on every new PR from this point on
What Review agents surface on every PR:
  • Complete code review
  • Which lines were written by AI vs. the developer
  • Risk score: blast radius + AI contribution rate + incident history
  • Every package and dependency the AI silently added
  • AIBOM generated at review time — before merge, not after an incident
  • Full AI provenance: model, session, developer, timestamp

Learn more about Review

See the full breakdown of what’s included in the Review plan.

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Step 5 — Create Release agents

Release Agent

Monitors your deployments end-to-end — from build artifact to runtime. Generates SBOMs and AIBOMs at every release, tracks deployment health, and traces production incidents back to their source.
Release agents require the Release plan ($149/month), at least one cloud connector (AWS or GCP) configured in Step 3, and a GitHub connector.
To create a Release agent:
  1. Go to Agents → New Agent in the dashboard
  2. Select Release as the agent type
  3. Choose the repositories and cloud environments to monitor
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  4. Select the functions you want your agent to perform
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  5. Select a communication channel where you want your agent to interact with your team
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  6. Click Create Agent — the agent begins executing the selected functions and tracking from your next deployments

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Step 5.1 — AIBOM and Evidence Pack

Once your Release agent is running, SenseLab assembles a complete evidence pack at every release — automatically, with no manual work required. The evidence pack spans the full SDLC:
SourceWhat’s captured
Local DevAI session, model used, files touched, lines written
PR ReviewRisk score, AI provenance, dependency scan, AIBOM at review time
Build & ArtifactEvidence bound to the specific build artifact
DeploymentDeployment record correlated to PRs, commits, and AI sessions
RuntimeHealth checks, anomalies, production impact events
Evidence PackFull AIBOM + SBOM export, approval history, audit trail
When an auditor, enterprise customer, or legal team asks:
  • “What shipped in release 3.1.2 and who approved it?”
  • “Can you provide an AIBOM for this release?”
  • “Which parts of our codebase were generated by AI?”
The answer is already assembled. You’re not scrambling — you’re exporting.

Learn more about Release

See the full breakdown of what’s included in the Release plan.

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You’re set up

AI Lineage

Free. Live AI attribution, team adoption, and model usage.

Review

$29/user/month. Risk-scored, AI-attributed PR review before merge.

Release

$149/month. Full deployment tracking, AIBOM, and evidence packs.
Need help getting set up? Join our Discord — the team is active and happy to walk you through it.