How I made a UiPath AI agent 15๐ฑ ๐๐๐ฌ๐ญ๐๐ซ and cut decision costs to $0.00003. โก
TypeSafe's Jev cannot write a single word of text. ๐
Yet it might be the most important model for enterprise automation.
Here is what happened when we plugged it into a UiPath Coded Agent: โก
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THE PROBLEM โ
Traditional LLMs like GPT are great writers, but terrible judges:
โข They take 6+ seconds per decision
โข They cost a fortune at enterprise scale
โข They cannot give you calibrated mathematical confidence
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THE FIX: "THE SPLIT ARCHITECTURE" ๐งฉ
We built an Anti-Money Laundering (AML) triage agent with a clean division of labor:
1๏ธโฃ UiPath LLM Gateway reads the alert and pulls out facts.
2๏ธโฃ
@typesafeai AI Jev judges 7 compliance questions in 398 ms for $0.00003.
3๏ธโฃ UiPath LLM Gateway writes an audit rationale with real evidence quotes.
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THE REAL CLOUD RUN NUMBERS ๐
On actual UiPath Orchestrator serverless runs:
โข ๐๐๐ฏ Decider: 591 ms | $0.000034
โข LLM Decider: 5,299 ms | 0.2 platform units
-> Jev was 9.13x faster on live cloud runs (15.5x median in benchmarks).
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THE REAL MAGIC: THE CONFIDENCE GATE ๐ก
When Jev is right, confidence is 0.89 to 1.00.
When Jev is unsure on ambiguous alerts, confidence drops to 0.31.
By setting a threshold at 0.50:
๐ข Greater than or equal to 0.50 -> Auto-Dispose: Handled instantly with zero touch.
๐ก Below 0.50 -> Human Review: Routed safely to compliance analysts.
100% of correct decisions pass through, and zero errors slip by. ๐ก๏ธ
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The complete agent code:
The Youtube Video:
Are you still asking generative LLMs to make your business decisions? ๐
@UiPath
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