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DTSTAMP:20260722T235849Z
DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16736\nProfessional serv
 ices firms run on institutional knowledge — who knows what, who's
  done what, and where the best thinking already lives. But that knowledge i
 s typically scattered across resumes, project records, proposals, and the m
 emories of long-tenured colleagues. This session presents a real-world case
  study from Health Management Associates (HMA), a national healthcare consu
 lting firm, on the design, development, and deployment of Colleague Central
  — an AI-powered enterprise knowledge graph that connects people, ski
 lls, project histories, proposals, deliverables, and subject-matter experti
 se into a single searchable platform powered by large language models.&nbsp
 ;\n\nWe'll walk through the full journey: from identifying the business
  need, to architecture decisions, to data ingestion strategy, to driving ad
 option across a distributed consulting workforce — and share practica
 l lessons on governing AI-generated outputs in a regulated healthcare envir
 onment. 
DTSTART:20261118T113000
SUMMARY:From People Search to Enterprise Brain: Building an AI-Powered Know
 ledge Graph
DTEND:20261118T121459
LOCATION: See Description
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