Turn data into shared, structured memory
Owletto gives all your agents the same durable graph: connectors, recall, and managed auth without leaking credentials to the runtime.
How it works
Turn scattered prompts, tools, and application data into a shared context layer your agents can use everywhere.
Model the world
Define the people, organizations, preferences, and follow-ups your agents should recognize across conversations and synced contact data.
Connect sources
Proxy MCP servers and ingest contact context from messaging apps, CRM syncs, email, and custom Connector SDK integrations through one runtime.
Relationship memory comes from the same channels support teams already work in every day.
| Type | Source | Added context |
|---|---|---|
| Inbox | Message threads | Capture promises, preference changes, and ownership notes directly from conversations. |
| CRM | Account sync | Pull company context, owners, and lifecycle state from the customer system of record. |
| Follow-up history | Attach promised summaries, deadlines, and replies to the right person record. | |
| Knowledge | Internal tools | Bring in structured account data or operational notes through MCP and custom integrations. |
Let users connect their data
Support OAuth for inbox and calendar context, API keys for internal tools, and imports for historical contacts without exposing credentials to agents.
Support teams can authorize inboxes, CRMs, and imports without handing secrets to the runtime.
| Access | System | How it works |
|---|---|---|
| OAuth | Inbox and calendar context | Connect communication tools so preferences and follow-ups stay in sync. |
| API key | Internal support systems | Store scoped credentials centrally for ticketing or account lookup tools. |
| Import | Historical contacts | Load CSV or manual records to seed memory before the next live conversation. |
| Isolation | Agent boundary | The support agent receives context, not the raw credentials behind it. |
Reuse context across agents
The same relationship memory powers support agents wherever teams work.
The same relationship memory powers support agents wherever teams work.
Keep it fresh
Watchers monitor new activity and update ownership, preferences, and follow-ups as the relationship changes.
A scheduled watcher keeps this memory current as new source changes arrive.
{ status, role_changed, new_preferences[], overdue_tasks[] }Latest blog posts
Filesystem vs Database for Agent Memory
Agents need a workspace to think in and a warehouse to remember in. The filesystem is for ephemeral work. The memory layer is for durable organizational knowledge.
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Beats other memory systems on public benchmarks
Apples-to-apples comparison on public memory datasets. Same answerer (glm-5.1) and same questions.
LongMemEval (oracle-50)
Single-session knowledge retention.
| System | Overall | Answer | Retrieval | Latency |
|---|---|---|---|---|
| Lobu | 87.1% | 78.0% | 100.0% | 237ms |
| Supermemory | 69.1% | 56.0% | 96.6% | 702ms |
| Mem0 | 65.7% | 54.0% | 85.3% | 753ms |
LoCoMo-50
Multi-session conversational memory.
| System | Overall | Answer | Retrieval | Latency |
|---|---|---|---|---|
| Lobu | 57.8% | 38.0% | 79.5% | 121ms |
| Mem0 | 41.5% | 28.0% | 66.9% | 606ms |
| Supermemory | 23.2% | 14.0% | 36.5% | 532ms |
Start building shared memory
Model the right entities, connect your sources, and keep long-term context available across every agent workflow.