Observability for LLM Reasoning
Debug single models. Profile multi-agent pipelines. Ship stable systems. NCF Audit gives you visibility into what your LLMs are actually doing.
Microservices Had the Same Problem
A request failed somewhere in the pipeline. Which service? Which call? Teams debugged blind until distributed tracing gave them observability.
Microservices (Before Tracing)
"Request failed. Check logs for each service. Good luck."
LLM Pipelines (Today)
"Output is wrong. Re-run with different prompts. Good luck."
Debug With Precision
Stop guessing why your model produced bad output. Get token-level visibility into reasoning stability.
Reasoning Chain Debugging
Token-level visibility into WHERE reasoning went wrong, not just THAT it went wrong.
Version Comparison
Quantifiable stability metrics across fine-tuning iterations. Did v2 improve or degrade?
Prompt Engineering Validation
A/B test prompts by stability profile. Which prompts produce turbulent reasoning?
Regression Testing
Automated stability checks in CI/CD. Catch reasoning degradation before deployment.
Visibility Across the Pipeline
Multi-agent = multiple black boxes chained together. Debugging is exponentially harder. NCF Audit traces stability through every boundary.
🔗 Agent Handoff Integrity
Did semantic coherence survive when Agent A passed to Agent B? Track stability ACROSS boundaries.
⚡ Cascade Failure Detection
One agent's instability propagates downstream. NCF identifies WHERE the chain broke.
📈 Agent-by-Agent Profiling
Which agent is the weak link? Compare stability profiles under identical inputs.
🛡️ Adversarial Propagation
If injection enters at Agent 1, does it destabilize Agent 5? Trace the "infection" through the pipeline.
🎯 Orchestrator Auditing
When the router chose Agent B over Agent C, was the orchestrator in a stable state?
🔄 Cross-Model Comparison
Pipeline uses GPT-4 → Claude → Llama? Profile each leg independently.
✗ Without NCF Audit
- 1 Output is wrong
- 2 Check each agent's logs manually
- 3 Re-run with print statements
- 4 Guess which agent broke
- 5 Trial and error until fixed
✓ With NCF Audit
- 1 Output is wrong
- 2 Open stability heatmap
- 3 "Agent 3 collapsed at token 847"
- 4 Drill into Agent 3's reasoning trace
- 5 Fix the specific failure point
Zero Friction Adoption
No SDK. No hooks. No model changes. Pass output text, get diagnostics.
Zero Instrumentation
Pass output text. Get diagnostics. No SDK, no hooks, no model changes required.
CI/CD Ready
Add stability gates to your pipeline. Fail builds on reasoning regression.
Any Model, Any Vendor
GPT, Claude, Gemini, Llama, Mistral, fine-tuned, custom. All work identically.
See inside your pipeline
Request a demo audit on your multi-agent system. We'll show you which agents are stable and which are one prompt away from collapse.
Request Developer Demo →