How do I keep my AI up to date on company changes?
Let writes flow in, not pulls flow out. Every commit, email, and decision is ingested via MCP connectors and merged by the Consolidator. The graph is always current because it's updated continuously, not batched nightly.
Why nightly batch updates fail for AI memory
The old pattern for keeping an AI "up to date" was nightly ETL — pull the week's docs, re-index, ship to the vector store. That pattern is obsolete for two reasons. First, the graph is stale by morning because today's commits, emails, and decisions aren't in it yet. Second, batch ingestion duplicates content, misses updates, and costs token budget to re-embed. Modern AI memory has to be a push system, not a pull system: every new write flows in as it happens. Freshness becomes a property of the pipeline, not a nightly promise that sometimes slips.
The push model powered by the Consolidator
bRRAIn's Consolidator is an event-driven merge layer that listens for every write across your Workspaces and the MCP-connected systems. When someone commits code, sends an email, or logs a decision, the event lands in the Consolidator, which folds the change into the POPE graph. There is no nightly job; the graph is updated continuously. A question asked at 3:47pm sees decisions that were made at 3:45pm. The freshness gap collapses from a day to a minute, without the team doing anything different.
Where MCP connectors fit in the ingestion chain
Push ingestion needs the right taps. The MCP Gateway hosts connectors that speak the Model Context Protocol for each source system — Gmail, Google Calendar, GitHub, Jira, your CRM, and your decisions log via the Document Portal. Each connector emits events when the source changes, routed into the Consolidator. The Security Policy Engine enforces which events are accepted and who can see the downstream graph nodes. Ingestion becomes configurable at connector level: you decide which sources feed the graph and which stay out, without touching application code.
Handling contradictions and supersession cleanly
When company reality changes, new facts often contradict old ones. A decision from last quarter gets reversed; a product name changes; an owner rotates. Naive ingestion either overwrites silently (losing history) or piles facts on top of each other (confusing the model). The Consolidator resolves this with explicit supersession: old nodes stay in the graph with a superseded-by link, so the current answer is based on the latest truth while history remains auditable. The Ontology Viewer lets a reviewer see the chain — who changed what, when, and why. Updates become a feature, not a risk.
Verifying freshness with a three-second check
You can prove freshness in three seconds. Make a change in a source system — send yourself an email, push a commit, add a row to your decisions log. Ask the AI about it thirty seconds later. If the answer cites the change, the pipeline is live. If it does not, an MCP connector is offline or a policy is blocking ingestion. That test is the simplest ongoing health check for AI freshness. If you want to see it live on your own systems, book a demo, or start with the SDK quickstart to wire your first continuous connector. Fresh AI is a plumbing choice.
Relevant bRRAIn products and services
- Consolidator / Integration Layer — event-driven merge engine that keeps the graph current by the minute.
- MCP Gateway — hosts the connectors that emit source-system events into ingestion.
- Document Portal — the decisions-log home that feeds the graph continuously.
- POPE Graph RAG — the graph that absorbs pushed updates with supersession intact.
- Ontology Viewer — shows supersession chains so history and current truth stay auditable.
- SDK quickstart — wire your first continuous connector and test the three-second freshness check.