Litica
One memory. One truth. Every agent.Shared memory, governed. For agents that can't disagree.
Governed shared memory for multi-agent workflows. Conflict resolution, full provenance, audit-complete logs.
The Problem
Your agents don't share memory.
They share confusion.
When Agent A and Agent B operate in the same workflow, they each carry their own isolated context. Agent A researches. Agent B drafts. Neither knows what the other knows. When they contradict each other, no one knows which one is right. Or why.
Every memory layer on the market was built for a single agent remembering a single user. That architecture breaks the moment your pipeline has more than one agent in it.
The Solution
One substrate. Every agent. Full governance.
Shared Namespace Memory
Agents read and write to a governed shared memory namespace. What Agent A learns, Agent B can retrieve. Full provenance shows exactly where that knowledge came from, when, and with what confidence.
Conflict Resolution
When two agents assert contradictory facts about the same entity, Litica resolves the conflict using competitive consolidation: salience scoring, recency, and source confidence. No more silent contradictions corrupting downstream decisions.
Audit-Complete Logs
Every memory read, write, and promotion is logged with agent ID, timestamp, and provenance chain. Audit-complete logs are not a feature you add later. They are the architecture.
How It Works
Memory that propagates the way understanding does.
Litica uses spreading activation, a cognitive architecture borrowed from how the brain links related concepts, to surface relevant memories across the shared namespace. When Agent B queries for context, activation spreads through the memory graph, amplified by salience scores and shaped by reference frame decomposition. The result is not keyword retrieval. It is structured recall with provenance.
Benchmark
In head-to-head testing against flat retrieval on evaluative multi-agent queries, Litica achieved a mean P@3 of 0.67 versus 0.29. On evaluative queries specifically (“what made this customer hesitate?”, “what did we decide last sprint?”), flat retrieval scored 0.00 on 5 of 5. Litica resolved all 5.
Read the full benchmark →Architecture
Built on a theory of memory, not a theory of retrieval.
Mem0 and Zep extract facts and store embeddings. Litica implements spreading activation over a structured associative graph, where each retrieval dimension is an independent reference frame with its own decay curve and salience weight. Memories compete for consolidation. Conflicts resolve with evidence. Facts carry provenance from the agent that wrote them to every agent that reads them. Your existing PostgreSQL database is your memory infrastructure. No proprietary graph database required.
| Capability | Litica | Mem0 | Zep | AgentCore |
|---|---|---|---|---|
| Shared cross-agent memory | Yes | No | No | No (per-agent scoped) |
| Conflict resolution | Competitive consolidation | Self-editing | None | None |
| Spreading activation | Yes | No | No | No |
| Provenance per memory | Full | Partial | Partial | Partial |
| On-prem / multi-cloud | Yes | Enterprise only | Enterprise only | AWS only |
| EU AI Act audit logs | Native | Overlay | Overlay | No |
Use Cases
Where shared memory changes the outcome.
Research + Draft Pipelines
Agent A researches. Agent B drafts. The draft is grounded in everything the researcher found. Not a context dump in the prompt. Structured memory with salience scoring and decay. When the research changes, the memory updates. The draft reflects it.
Multi-Step Underwriting and Intake
A planner agent, a retrieval agent, and a compliance agent all operate on the same customer record. Litica ensures they share a coherent world model. Contradictions surface before they become decisions. The audit log proves it.
Agentic Developer Tooling
Claude Code, Cursor, and OpenCode can share context across sessions and across agents. A coding agent that knows what the debugging agent already tried is not a future feature. It is a namespace configuration.
Design Partners
Built for the teams hitting the wall.
If your multi-agent pipeline is producing contradictions your compliance team can't explain, you are the team Litica was built for. We are working with early design partners in financial services, legal AI, and healthcare AI. Pilots run 90 days. ACV starts at $50K.