SignalBreak

AI resilience visibility
Launching soon
Early access opening shortly

Know what breaks when AI does.

SignalBreak shows your AI dependencies, blast radius, and single points of failure — in plain English, with professional reports you can share with leadership.

Sound familiar?

  • Model updates silently change outputs — you find out when customers complain
  • No visibility into what your AI is actually telling customers — until something goes wrong
  • Calculations and scoring drift over time — your reports look fine but the logic shifted
  • Leadership asks "how do we know the AI is behaving?" — you have no answer

What you'll get

  • Dependency map
    Which workflows rely on which providers, models, and services.
  • Blast radius view
    What breaks (and how badly) when things degrade or go down.
  • Fallback readiness
    Where your "multi-model strategy" is real — and where it isn't.

Snapshot preview

OpenAI
73% • 8 workflows
Anthropic
18% • 2 workflows
Google / Other
9% • 1 workflow
If OpenAI has an outage, 73% of your AI capability stops. Most teams don't realise this until it happens.
Customer Support Chatbot No fallback
Document Processing No fallback
Lead Qualification No fallback
Content Generation No fallback
4 business-critical workflows have zero redundancy. When the provider fails, your team manually handles the load — or customers wait.
Coverage 2 of 9 workflows protected
✓ Email Triage
GPT-4 → Claude fallback
✓ Code Review
Claude → GPT-4 fallback
7 workflows have no backup plan. "Multi-model strategy" on paper doesn't mean resilience in practice.

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