Compiled context for teams that depend on accurate answers
Compile documentation into cited, permission-aware context packets for internal assistants, support workflows, sales enablement, website chatbots, APIs, and MCP tools.
Docs uploaded or crawled
FilesThe system supports SSO with SAML 2.0 and OIDC [1]. Audit logs are retained for 365 days [2].
{
"context": {...},
"citations": [1, 2]
}Runtime RAG searches chunks
- Finds fragments and misses relationships
- Hard to cite and verify
- Inconsistent answers across sessions
- Expensive as context grows
Octoplexity compiles knowledge first
- Understands structure and relationships
- Grounded, cited, and auditable
- Consistent, accurate, and explainable
- Efficient packets for every use
One context backend for internal teams and customer-facing chat.
Documentation powers more than one interface. Octoplexity keeps the source layer consistent across them.
Internal Knowledge
Give employees answers from current internal documentation while preserving source boundaries and citations.
Learn more ->Support Teams
Help support teams draft source-backed responses from product docs, known issues, runbooks, and release notes.
Learn more ->Sales Enablement
Turn product detail, implementation guidance, and current positioning into reliable context for revenue teams.
Learn more ->Website Chatbots
Power hosted or custom site chat with compiled documentation context, citations, and permission-aware source access.
Learn more ->Designed as infrastructure, not a demo chatbot.
Hosted chat matters, but the durable primitive is the compiled context packet.
Source intake
Upload documents or crawl web documentation, then normalize each source into documents, versions, and source spans.
Document compiler
Compile claims, entities, summaries, relationships, and provenance before the user asks a question.
Context packets
Return compact, cited, model-ready payloads instead of loosely ranked chunks stuffed into prompts.
Permission filtering
Apply tenant, project, source, role, API key, and MCP client boundaries before context reaches a model.
Give your AI systems a better context layer.
Bring documentation, support knowledge, sales context, and website answers into one compiled source of truth.