What is Fusemomo?
FuseMomo is the behavioral Intelligence for action-taking AI agents. It gives your agents persistent behavioral intelligence for every entity they interact with using APIs.
Agents using Fusemomo:
- Know who an entity is, no matter which platform they appear in.
- Know what actions have worked or failed for that entity in the past.
- Know what to do next, guided by historical success data — before acting.
The Problem
AI agents are going to be biggest consumer of APIs. But, AI agents fail in production to deliver theur intended outcome not because they are unintelligent, but stateless and blind to outcomes.
1. Identity Fragmentation:
Without a unified identity layer, agents treat the same entity across systems as different records—duplicating effort and losing context.
2. Outcome Blindness:
No built-in mechanism tracks whether the intended outcome actually materialized. Actions are fire-and-forget. Intended outcome failures go unrecorded.
3. No Learning:
Every new agent session starts from zero. Decisions that failed repeatedly are made again identically. No cross-session pattern accumulation, no improvement over time.
The Solution: Three Layers
Fusemomo addresses all three problems with a unified three-layer architecture:
L1. Identity Resolution
Resolves any set of identifiers against a single canonical entity record. If the same underlying entity appears under different IDs across multiple APIs, Fusemomo merges them deterministically into one unified record with a consistent entity_id.
Works across any domain: users, customers, accounts, tickets, repositories, issues, assets — anything your agents operate on.
→ Learn more about Identity Resolution
L2. Behavioral Graph
Every action every agent takes on every entity — through every API — is recorded in an immutable, append-only log. Each entry captures:
- Which agent acted
- Which external API was used
- What type of action was performed
- What the outcome was (
success,failed,pending,ignored,unknown)
This log accumulates behavioral patterns over time that cannot be replicated by starting from scratch.
→ Learn more about the Behavioral Graph
L3. Behavioral Intelligence
Before your agent decides what to do, it can ask Fusemomo for a recommendation. Based on historical outcome data for that specific entity and intent, Fusemomo returns the action type with the highest observed success rate, a confidence score, and the full ranked opportunity set.
Recommendations get better as more data accumulates. The feedback loop is explicit: agents report back whether they followed the recommendation and what happened.
→ Learn more about Behavioral Intelligence
Integration Methods
Fusemomo is designed for flexibility:
| Method | Best For |
|---|---|
| MCP Server | Claude Desktop, Cursor, and any MCP-capable agent |
| REST API | Any agent framework, backend service, or custom integration |
What Fusemomo Is Not
Fusemomo does not track:
- Conversation history or LLM context
- LLM prompt/response traces
- Marketing event streams
Fusemomo tracks what happens when agents call third-party APIs, and helps them learn what actions produce successful outcomes for specific entities.