Your AI passed every test. Then it failed silently in production.
We find the silent failures standard evaluations miss: a guardrail quietly dropped mid-conversation, a fabricated tool call, a memory that compressed away what mattered. We engineer them out. Our fixes already ship in LangChain and Microsoft Semantic Kernel.
The guardrail that quietly disappears
The instruction is still in context, but a truncation or summary step silently dropped it turns ago. The agent stops following the rule, and nothing logs that it lapsed.
We named this failure in our taxonomy, then fixed a live instance of it in Microsoft Semantic Kernel (merged).
The tool call that never happened
Under pressure, an agent writes a plausible tool result from memory instead of calling the tool. It passes the demo. You find the fabrication in front of a customer.
Our open-source agent-gorgon blocks fabricated tool output when a real tool exists.
The memory that rewrote itself
Your summary or memory layer compresses context to save tokens and quietly changes what it meant: a dropped qualifier, a paraphrase that is not what you wrote.
Our open-source fidelis returns your context verbatim instead of paraphrasing it.
The incident you cannot reconstruct
Something went wrong in an autonomous run, and you cannot show what the agent actually did, in what order, or why.
Our open-source suy-sideguy enforces runtime policy and produces forensic, offline-verifiable evidence of what the agent did.
Zenodo 19042469
For enterprise AI teams
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