Decision Traceability
When an agent gets it wrong, can you reconstruct the source events, context, policy checks and tool calls behind its action?
Free Architecture Score
Can you trace what your agents saw when they got it wrong?
Score how well your Kafka setup lets you reconstruct an agent decision from source event to action. You also see where data movement and storage add cost.
The score checks decision traceability first, then your event backbone, data movement and retained data footprint.
What the diagnostic tests
The Streaming Backbone
Is your current infrastructure ready to support live AI workloads?
Data Movement
How many copies, ETL handoffs, and cloud boundaries sit between your data and your AI?
The Storage Scale
How much event data do you retain, and is it enough to compare storage and movement costs?
Architecture diagnostic questions
What does the diagnostic measure?
It measures how well you can trace an agent decision back to its source events, then your event backbone, data movement and retained data footprint.
Who is this diagnostic for?
It is designed for platform, data, AI, and operations leaders running or planning AI on live operational data.
Are my answers sent to an AI model?
No. The application uses a transparent rules-based model and reviewed report content. It does not use an LLM at runtime.
What is included in the full report?
The full report includes your architecture breakdown, binding constraint, evidence gaps, and a practical 90-day validation plan.
Why is a work email requested?
A work email unlocks the complete report and receives a reusable report link valid for seven days. Marketing updates require separate optional consent.