Ship AI changes without crossing your fingers.

Canarylane tests new models, prompts and agents against real workloads before they reach all of your users.
Compare quality, latency and cost. Canary what works.
Roll back what doesn’t.

Join the waitlistSee how it works

Built for teams shipping AI to production.

PR #1842Switch reasoning modelOpen

Traditional CI

  • Unit tests12s
  • Integration tests18s
  • Build21s
  • Type check8s

Canarylane evaluation

  • Task success−6.2%
  • Cost / request+31%
  • P95 latency+840ms
  • Tool errors+2.4%

DO NOT PROMOTE

Performance degraded on real workloads.

example pull request · illustrative numbers

01Change

Your tests pass.
Your AI can still get worse.

Traditional CI knows whether your software runs.
It doesn’t know whether your agent got less accurate, more expensive or slower.

Observability tells you what broke.Canarylane tells you whether to ship.

What happened? is a dashboard question. Should we ship it? is a release decision.

02Shadow

Every release
earns production.

Canarylane runs your candidate against real production workloads, compares what actually matters, and progressively deploys changes when they perform well.

  1. 01passed

    Shadow

    Run your candidate against representative production workloads.

  2. 02passed

    Compare

    Measure quality, cost, latency and application-specific outcomes.

  3. 03passed

    Canary

    Expose the candidate to a controlled percentage of live traffic.

  4. 04promoted

    Promote

    Increase traffic when metrics remain healthy, or roll back automatically.

03Evaluate

Optimize what
actually matters.

Compare your candidate against production across quality, latency, cost and the business metrics your application lives on.

Candidate v43vsProduction v42

example run · sampled traffic

MetricProductionCandidateChangePolicy
Task success91.6%91.6% → 94.8%+3.2%regression < 1%
Cost / request$0.106$0.106 → $0.084−21%increase < 10%
P95 latency2.08s2.08s → 1.84s−240msp95 < 2.5s
Tool success98.4%98.4% → 99.1%+0.7%no regression
Agent steps5.05.0 → 4.2−0.8informational
RecommendationPROMOTEAll metrics within the release policy.next: canary 5% → 25%

04Canary

Define what
“safe to ship” means.

Turn your evaluation criteria into an executable release policy.

Your release policy becomes executable.

Canarylane continuously evaluates the candidate and controls rollout based on the metrics your team cares about.

canarylane.yamlevaluating candidate v43
release:
  quality_regression: < 1%+3.2% quality
  cost_increase: < 10%−21% cost
  p95_latency: < 2.5s1.84s

strategy:
  canary: 5%live on 5% of traffic
  promote: automaticarmed
  rollback: automaticarmed

Designed for the stack you already use.

  • models
    • OpenAI
    • Anthropic
    • Google
    • Mistral
  • delivery
    • GitHub
    • OpenTelemetry

Built for production AI teams.

  • Voice agents
  • Support agents
  • Coding agents
  • Security agents
  • AI SaaS

05Promote

Software is becoming probabilistic. Deployment infrastructure has to change with it.

AI applications are no longer single model calls. They’re systems of models, prompts, tools, memory, retrieval and agents. Canarylane is building the release control plane for those systems.

Development
  • Model swap
  • Prompt edit
  • Agent change
  • New tool
  • Retrieval config
Canarylane
  1. shadow
  2. evaluate
  3. canary
  4. promote
rollback
Production
  • Models
  • Agents
  • Tools
  • Infrastructure
  1. TodayAI release testing.
  2. TomorrowThe control plane for production AI.

06Production

Ship your next AI release
through Canarylane.

We’re working with a small group of teams running AI systems in production. Join the waitlist for early access.

Email first. Two optional questions after.

  • Early access
  • Direct feedback with the team
  • Help shape the roadmap

Running an AI agent in production?

We’re looking for teams shipping model, prompt or agent changes every week. Work directly with us and help shape Canarylane.

Become a design partner