An active map for your business operations. Transforming scattered institutional knowledge into executable skills for AI agents. Train, govern, and continuously improve your agents as they learn how your company operates.
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Every department gets its own complete brain — sources, graph, skills, agents, gap analysis, and learning evaluations.
Processes, concepts, people, and data — mapped with dependencies so AI understands how your business actually works.
AI-executable procedure documents compiled from your knowledge. Agents follow them step-by-step — no hallucination, no guesswork.
Weekly compilation of new knowledge, changes, and insights — automatically fed back into your agents so they stay current.
Automatically identifies what’s missing from your knowledge base — undocumented processes, outdated info, coverage blind spots.
Judge and rubric system that evaluates agent output quality against your standards. Continuous improvement, measured.
Every knowledge change tracked with who, when, and why. Critical for regulated industries and for debugging when an agent starts behaving differently.
Sales depends on Product for feature specs, Support depends on Engineering for incident docs. Map these relationships so gap analysis flags stale upstream knowledge.
Test a skills file against sample inputs before deploying to production agents. See what the agent would do step-by-step without it actually doing it.
Proactive notifications when knowledge goes stale. Know when an onboarding doc hasn’t been updated in 90 days and 3 agents still reference it.
Bulk import from Notion, Confluence, and Google Docs. Export the full knowledge graph as JSON or Markdown for backup or migration.
Admin-controlled permissions matrix. Sales team edits Sales knowledge but only reads Engineering. Granular control over who sees and changes what.
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A structured knowledge OS organizes your company’s scattered documents, processes, and expertise into a machine-readable format that AI agents can actually use — not just search, but reason over.
Wikis store text. Certexa structures knowledge into graphs, compiles it into executable skills files, identifies gaps, and feeds everything back into your AI agents through a continuous digest cycle.
Branches are top-level organizational units — Sales, Engineering, Support, HR, etc. Each branch gets its own complete knowledge stack: sources, graph, skills, agents, gap analysis, and learning evaluations.
Yes. Certexa is agent-agnostic. It structures your knowledge so any AI agent — whether custom-built or off-the-shelf — can query, reason over, and act on your company’s intelligence.
Certexa runs as a desktop application. Your knowledge stays on your infrastructure. Nothing leaves your environment unless you explicitly configure it to.