Self-Correcting AI Agents
Production-grade AI reliability through automated self-evaluation
The biggest barrier to enterprise AI adoption is not capability — it is reliability. Single-pass LLM responses are inconsistent, hallucination-prone, and unacceptable in business-critical workflows. Organisations need AI that validates its own outputs before acting.
A two-agent feedback architecture: a worker agent executes complex tasks; an evaluator agent scores outputs against defined criteria and returns structured feedback. The system iterates until quality thresholds are met — fully automated, with complete LangSmith traceability for every decision cycle.
Business Impact
How It Works
Worker agent executes the business task and produces an initial response
Evaluator agent scores the response against defined quality criteria
System iterates automatically until quality threshold is met — then delivers
Deployment
Enterprise cloud, on-premise, or hybrid · Cloud-agnostic agentic architecture
Technology Stack
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