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ICSO — AI Model & Token Cost Diagnostic

Find where your AI spend is leaking.

ICSO analyzes historical AI usage logs to identify unnecessary model spend, token waste, oversized context, retry loops, tool-call waste, and cache opportunities.

Request a Replay Diagnostic

Historical logs only. No production access required.

Tested replay engine
The ICSO replay engine has been validated on external usage-log data, demonstrating stable and deterministic processing across repeated runs.

PROBLEM

AI teams often know total AI spend.
They do not always know why it happened.

Which requests were unnecessarily expensive?
Where was a premium model used for a simple task?
Where did context size, retries, failed tools, or missed cache opportunities increase cost?

ICSO helps teams inspect the spend behind the usage.
 

Common cost leaks
 

Expensive models used for simple tasks
Premium models may be used where a lower-cost route could potentially preserve quality and reduce cost.
 

Too many tokens and oversized context
Large prompts, long context, and unnecessary history can quietly increase cost.
 

Retry and regeneration loops
Repeated attempts can multiply spend without improving the final result.
 

Failed or repeated tool calls
Agentic workflows can waste cost through failed tools, repeated calls, and unnecessary execution steps.

What ICSO analyzes

ICSO works from historical AI usage logs.

For a first diagnostic, we do not require production access, live traffic access, or changes to your AI system.


Typical log fields

  • Model used

  • Input and output tokens

  • Estimated request cost

  • Context size

  • Retry and regeneration counts

  • Tool calls and failed tools

  • Cache hits and misses

  • Latency and errors
     

ICSO reviews these signals to identify where AI cost may be avoidable, inefficient, or worth testing under a controlled optimization pilot.

Team Analyzing Data

What you receive

A replay diagnostic gives your team a clear view of where AI spend may be leaking.

Deliverables

  • Usage log validation

  • Baseline cost comparison

  • Model usage and token-pressure analysis

  • ​Top candidates for avoidable spend

  • Conservative savings scenarios built on transparent assumptions

  • Recommendations for a limited production test
     

ICSO estimates potential savings from historical logs. Actual production savings require a later controlled pilot or before/after measurement.

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