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TLDRocket
16 October 2026
The biggest thread today is that “agentic AI” is getting practical through layers that control what models know, how they reason, and what they’re allowed to do with that knowledge. Raymond James Financial is using knowledge graphs as a reasoning layer for agentic systems built over trusted financial data, with evaluations against “golden sources” and a claim of 100% accuracy before launch—an explicit bid to move advisors from manual screen-hunting to supervising AI agents. Uvi’s pitch is similar in spirit but aimed at cost: it says semantic, permissioned company knowledge graphs can cut per-answer tool/context costs from roughly $0.75–$1.41 (sometimes over $2.00) down to $0.10–$0.16 by avoiding repeated “amnesia”-style re-collection from Slack, Jira, and GitHub.
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