Knowledge infrastructure that gathers your company's knowledge into one durable memory, gives every AI tool the same truth, and knows when each thing was true.
Three Assistants, Three Different Answers. The Problem Is Memory, Not the Model.
Companies moving to AI tend to stall in the same place: each tool knows half the story, one forgets yesterday's decision, another quotes a price cancelled two months ago. We separate knowledge from the tools and move it into one enterprise memory. Every agent reads from the same source, and a new AI tool inherits the company's entire knowledge on its first day.
We build memory with time in it. A new decision does not delete the old one, it supersedes it — even "what did we know in March?" has an answer. Retrieval scores meaning, importance and recency together; precise questions go to structured queries, vague ones to semantic search. Embeddings are generated on your own infrastructure, and retention periods follow data-protection rules.
What We Build
- Bi-temporal enterprise memory: version chain, supersede, never delete
- Hybrid retrieval: structured query + vector search + recency and importance scoring
- Source classification: public, internal and confidential knowledge managed apart
- One memory served to every agent over MCP; Linear, Drive and CRM connectors
- Local embeddings and retention periods aligned with data-protection law
Where It Fits
Proposal and contract drafting, on-brand content production, team and project status reports, product catalogue search, internal knowledge bases and customer support knowledge.
In Our Own Projects
APEX: Unitic's own collective AI brain — our conversation, coding and content agents run on the same memory. Hardiye: product search over a 150-item catalogue that routes precise requests to a structured query in milliseconds and vague ones to semantic search.