V7 uses GPT-5.6 to transform unstructured company files into retrievable institutional memory for AI agents. The system does not summarize documents. It indexes them so agents can cite specific sources while completing multi-step tasks.
This matters because most enterprise AI deployments fail at retrieval. Agents hallucinate or lose context across long workflows. V7's architecture routes queries through a knowledge layer built from a company's existing files, grounding outputs in real organizational data with traceable links.
The full piece is worth reading for how V7 structures the ingestion pipeline and where GPT-5.6's capabilities specifically change what was previously impossible. The source-linking mechanic alone raises questions about auditability standards every AI deployment team should be asking right now.
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