Governed Agentic RAG that tunes retrieval, routing, prompts, and validation loops.
73%
SCORE GAIN
17
EXPERIMENTS
$15
TOTAL COST
INDUSTRIES
Life sciences · Research · Quality · Engineering · Finance
§ ARCHITECTURE
How it fits together.
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SYSTEM OVERVIEW
Optimizes retrieval pipelines across chunking, embeddings, hybrid retrieval, routing, prompts, and hallucination controls, with benchmark-driven evaluation and reviewer-loop compatibility.
FOR YOU
You need source-backed answers across regulated or mission-critical knowledge bases, with evaluation-driven tuning before production rollout.
§ CAPABILITIES
Governed Agentic RAG01
Hybrid retrieval02
Hallucination controls03
Evaluation-driven tuning04
Source-backed answers05
Multi-model routing06
§ IN DETAIL
a.
7 optimizable dimensions including chunking, retrieval, routing, prompts
b.
Baseline 0.208 → 0.360 composite score
c.
Hallucination controls proved more impactful than model upgrades
d.
Evaluation-driven tuning for source-backed answer workflows
e.
Reviewer-loop compatibility for regulated and mission-critical knowledge workflows