Move fast while competitors are stuck vibe-checking. Flightline is the automated testing pipeline for synthetic data generation, regression blocking, and hallucination detection. Setup in 5 minutes.
Limited onboarding capacity. White-glove setup with the founding team.
WHY THIS MATTERS
→ AI hallucinates in production
→ Customer calls support
→ Support escalates to engineering
→ Emergency rollback required
Result: 2 weeks lost, customer trust damaged
→ Test runs on commit
→ Hallucination caught
→ Merge blocked automatically
→ Fix before production
Result: Zero customer-facing incidents
Iteration cycles
Hallucinations
Edge case coverage
HOW IT WORKS
Flightline maps the latent space of your schema, generates edge-case scenarios, and runs deterministic regressions on every commit. We verify that numbers match exactly and safety guardrails trigger correctly—stopping bad merges before they reach production.
$ flightline test --suite rag_pipeline
> 🧪 Generating 50 synthetic scenarios... [OK]
> 🏃 Running regression suite...
> ❌ FAILED: Case #14 (Conflicting Knowledge Scenario)
> - Input: "What is the refund policy?"
> - Output: "Refunds are processed in 24 hours."
> - Context: "Policy: Refunds take 5-7 business days."
> - Error: Hallucination detected (Context Breach)
> 🛑 Blocking Merge. 1 Regression Found.COMPLIANCE READY
Can't test locally because of PII? Flightline parses your docs and schemas to generate thousands of high-fidelity, legally safe synthetic test cases. Test edge cases without touching customer data.
# Generating synthetic PII-free data...
schema = load_schema("customer_support.py")
synthetic_data = flightline.generate(
schema=schema,
count=1000,
edge_cases=True
)
# > Generated 1000 records covering 99.8% of latent space
# > 0 PII leaks detectedWe're working with a select group of technical founders who are shipping AI features and tired of manual testing.
We're currently onboarding teams that:
Limited onboarding capacity.