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Aptive has received a three-year, $9.4 million contract to modernize the Veterans Health Administration's Veteran and Family Member Programs, bringing automation, data migration and data exchange support to a program serving more than 7 million Veterans and family members.
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Multi-model and multi-agent AI architectures are now the default way serious enterprise and federal AI work gets built. That power comes with real tradeoffs: expanded attack surface, harder audit trails and governance gaps most teams underestimate. Article 6 of Aptive’s Agentic AI Governance Series lays out the risk taxonomy, a control baseline mapped to NIST 800-53 and the architecture patterns that hold up in regulated environments.
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Aptive has won a two-year, $2.3 million VA task order to support the Office of Suicide Prevention's Strategic Sprints.
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Aptive is a Veteran-owned healthcare company, so when this year's Fitness Frenzy challenge wrapped up Aug. 31, the mileage was only part of the story. Employees logged 4,089 miles over six weeks, and Aptive Cares made a donation to the National Disabled Veterans Winter Sports Clinic in their honor.
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Multi-agent AI systems create an authorization problem most security frameworks were never built to address. Article 5 in Aptive's Agentic AI Governance Series introduces the Orchestrator Capability Manifest, a runtime-enforced policy document that governs which tools each AI agent can use, which prompt version it runs, which model it's pinned to and when a human has to review its output before it moves downstream.
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The first three articles in Aptive's agentic AI governance series defined the architecture. Article four defines the infrastructure that enforces it: container isolation, sandboxed code execution, zero trust network zones, CI/CD security gates and an AI incident response plan built around CISA's 72-hour reporting window.
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Aptive congratulates Tammy Czarnecki, executive vice president for health services, on being named a winner of FORUM's Leading for IMPACT, Women in Leadership award.
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Most AI governance failures aren't technical. They're organizational. In Article 3 of Aptive's Agentic AI Governance series, Ian Meinert breaks down the nine artifacts that turn NIST AI RMF requirements into working governance: risk tolerance statements, accountability matrices, impact assessments, bias evaluation frameworks and more. If leadership hasn't defined what risk the organization accepts, who owns what and what happens when something goes wrong, the technical controls aren't enough.
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