Secure conversational AI for federal knowledge missions.
Federal programs run on documents – policy manuals, regulations, contracts, technical libraries, SOPs, briefings, and years of institutional reports. The knowledge exists, but finding the right answer often depends on keyword searches, shared drive archaeology, or the one person who remembers where something is written.
Generic AI tools are not built for that reality. They cannot reliably see agency-specific content, may generate answers they cannot support, and can move sensitive information outside the agency’s environment.
Aletheia is built for the document-heavy work that drives federal missions: interpreting policy, applying regulations, reviewing contracts, searching technical libraries, answering program questions, and preserving institutional knowledge across changing teams.
The platform deploys inside a government-controlled AWS environment on Kubernetes, with encryption in transit and at rest, enterprise SSO (OAuth2/OIDC), mutual-TLS service mesh, structured audit logging, token-level AI usage logging for cost and oversight visibility, and per-tenant data isolation. Government customers retain full ownership of their data, and customer content is not used to train the underlying foundation models.
Aletheia was developed through CATHEXIS Labs and shaped by CATHEXIS’ direct experience supporting federal audit, oversight, and program missions – environments with large document sets, mixed file types, changing guidance, complex approval chains, and the need to show the source behind every answer.
The platform is operational today, running in production over CATHEXIS’ own federal-domain knowledge corpus of thousands of pages. Its multi-tenant architecture is designed to support new customer environments with separated data, configuration, branding, security boundaries, and document pipelines.
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