Cynapa runs alongside the AI tools, devices, and systems your team already uses. It doesn't replace any of them. It connects them at the layer underneath — the layer where memory lives.
Cynapa observes work as it happens. AI conversations across every vendor your team uses — Claude, ChatGPT, Gemini, Copilot, and others. Agent runs and tool calls. Document edits, code commits, communications, calendar entries, browser sessions. These become a stream of events in your tenant — append-only, timestamped, attributed to the person and the tool that produced them.
The ingest path doesn't require behavior change from your team. They keep using the tools they use. Cynapa connects to those tools through standard APIs and observes the work that flows through them.
Across every substrate, the same person, the same project, the same artifact, the same decision shows up under different identifiers. Cynapa resolves them. Your engineer is the same engineer in chat, in email, in the code repository, in the meeting transcript, on every AI tool. The repository they're working on is the same repository whether referenced by URL, by name, or by hash. The bug they're investigating is the same bug whether described in a chat message, a ticket, or a code comment.
This resolution is what makes cross-tool memory possible. Without it, you have a stream of events that don't connect. With it, you have a graph.
Inside the stream, work happens in topics and workstreams. A person investigates a bug, gets distracted by a different bug, returns to the original. Two engineers investigate related problems in parallel. A topic spans hours, days, weeks. Cynapa segments the stream into topics and workstreams that survive the surface that originated them.
The segmentation is what makes memory queryable. "Show me everything about the auth bug" returns the workstream, not the session it happened in.
The graph is the memory. Events, entities, topics, workstreams, decisions, artifacts — all connected by typed edges. Every authorized person and every authorized agent in your organization queries the same graph. The graph compounds with every interaction.
The graph is yours. It lives in your tenant, under your administrative control, with your data sovereignty. Cynapa is the infrastructure that builds and serves the graph. The graph itself is your asset.
When a person asks a question or an agent needs context, retrieval pulls a relevant slice of the graph — a memory neighborhood — and assembles it into a context packet. The packet is the answer to "what does this person, this agent, or this workflow need to remember to do this work?"
Retrieval is permission-aware. Permissions are enforced structurally at the graph level. What you can see is a coherent slice of the graph, not a redacted projection.
When the same question has already been answered for someone else in your organization with the same authorization scope, Cynapa serves the existing answer instead of re-issuing the inference. The answer carries provenance: who asked, when, in what context, with what supporting graph state.
The deduplication is what makes the AI bill stop compounding as your team grows.
Cynapa supports private-tenant and dedicated deployment models. Your data sovereignty is a deployment-time choice. Cross-tenant federation is supported when both tenants explicitly opt in — for partners, vendors, customers, supply chains — and is governed by federation policies you control.
Cynapa supports common AI vendors and common enterprise systems out of the box. The integration layer is uniform: connectors implement a standard contract, declare their capabilities, version their protocols, and surface typed errors. Adding a new tool is connector work, not platform work.
Where standards exist for the substrates we connect to, we use them. We are not interested in being the data-format gatekeeper. The work the substrate does is more valuable than the lock-in any one format would create.
We don't replace your AI tools. We work above them.
We don't replace your enterprise systems. We connect to them.
We don't hold your data. Your data lives in your tenant. Cynapa holds the substrate that makes the data work as one mind.
Memory that follows the person, not the tool.
Continuity across devices and sessions.
Context that survives every restart, every new tab, every "let me try another way."
Visibility into agent behavior at the level where it matters.
An AI bill that stops compounding as your team grows.
A graph that compounds in value the longer it runs.
— Cynapa, Patents pending