Multi-source ingestion
Connectors for warehouses, message buses, object storage, document repositories, and the open web. Streaming and batch in one pipeline.
Muninn. The memory layer.
Muninn is the foundation everything at Raven stands on — a streaming, queryable picture of your environment built from every data source you care about. It normalizes structured records, parses unstructured text, indexes telemetry, and watches the open web. Every observation lands with provenance attached, so any answer downstream can be traced to source. Like the raven of memory in Norse myth, Muninn forgets nothing.
Capabilities
What Muninn does.
Vector + graph indexing
Hybrid retrieval that fuses semantic search with structured graph traversal. One query plane across both.
Provenance everywhere
Every record carries chain-of-custody. Trace any output back to the original source — automatically and without effort.
Anomaly detection
Continuous statistical and learned monitors flag the moments that matter, with thresholds you can tune live.
Time-aware schemas
First-class temporality. Replay any state of the world at any point in the past.
Open APIs
REST, gRPC, and SQL interfaces. Bring your own clients, plug into existing systems.
How teams use Muninn
From ingest to watch.
The day-to-day shape of Muninn in production. Your team rarely sees the seams.
- Step 01Ingest
Stream from every system you already run.
Muninn connects to your warehouses, message buses, document repositories, telemetry streams, and the open web. Streaming and batch share a single ingestion pipeline. Every record arrives normalized and stamped with its source.
- 120+ native connectors
- Streaming + batch unified
- Schema inference at ingest
- Step 02Index
Hybrid retrieval, one query plane.
Records are indexed across both vector and graph stores, with full-text and structured filters layered on top. Whether you ask in natural language or SQL, you query the same backing reality.
- Vector + graph + structured
- Time-aware indexes
- Cross-namespace search
- Step 03Watch
Continuous monitors flag what matters.
Statistical baselines, learned anomaly detectors, and rule-based triggers run continuously over the index. When something moves outside expected behavior, downstream systems know within seconds.
- Live anomaly thresholds
- Subscribe via webhook or stream
- Cross-source correlations
Built for
Where Muninn earns its keep.
01Finance
Real-time exposure
Continuous picture of risk across desks, books, counterparties, and venues — refreshed in seconds.
02Industrial
Supply-chain OSINT
Continuous monitoring of supplier signal across registries, news, and public filings.
03Energy
Asset health
Telemetry from rotating equipment, transformers, and pipelines unified with maintenance records.
04Cross-sector
Cross-system search
One query surface across SharePoint, Confluence, Drive, ticketing, code, and warehouse data.
Integrations · 120+
Muninn plugs into your stack.
Muninn ships with native integrations for the most common enterprise stacks, plus a typed HTTP surface for everything else.
Data warehouses
- Snowflake
- Databricks
- BigQuery
- Postgres
- Redshift
Cloud & infra
- AWS
- Azure
- GCP
- OVHcloud
- Scaleway
Messaging & ITSM
- Slack
- Microsoft Teams
- PagerDuty
- Opsgenie
- ServiceNow
Identity
- Okta
- Azure AD
- Google Workspace
- JumpCloud
- Auth0
Source systems
- SAP
- Oracle
- Salesforce
- Workday
- Custom HTTP
Document repos
- SharePoint
- Confluence
- Drive
- Notion
- S3
Frequently asked
Muninn, in plain English.
How is Muninn different from a data warehouse?
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A warehouse stores structured data and answers SQL. Muninn stores observations of any shape, indexes them across vector, graph, and structured stores, and continuously watches them. The output is a live operating picture, not a query result.
Can we point Muninn at our existing warehouse?
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Yes. Muninn ingests from Snowflake, Databricks, BigQuery, Postgres, and Redshift natively. Most customers run Muninn alongside an existing warehouse rather than replacing it.
How is provenance enforced?
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Records without a source identifier are rejected at the ingestion gateway. Every downstream read carries the chain back to the original observation, automatically.
How long are observations kept?
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Default retention is decade-scale. Tiered storage keeps hot data on fast indexes and cold data in archival object storage. Replay-as-of-time is supported across the full horizon.
Where is data stored?
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EU/EEA by default. Choose a specific region (Ireland, Frankfurt, Madrid, Stockholm) or run Muninn in your own EU cloud account or on-prem. Transatlantic transfer paths are off by default.
Pairs with
