Agent layer for SaaS with grounded answers, sandboxed tools, and per-customer isolation
Hybrid search, graph indexing, and vector-symbolic memory for AI agents
Stage
Not given
Startup
Founded
Not given
2026
Based in
Not given
US
Pricing model
Free
Open source
Pricing
Free during launch period. Customers pay their LLM provider directly for model usage at provider rates; Oberik does not markup or resell tokens. No credit card required, no usage meters tracked by Oberik itself.
Open source under Apache-2.0 license. WARM Cloud is in development with usage-based pricing for sync, backup and verification; details to be published at launch.
Key features
Document-grounded answers with page and quote citations
Linux sandbox environment for agent execution
Per-customer cost tracking and billing
Memory and wiki persistence across sessions
Scheduled and recurring work with durability
Capability-scoped JWT tokens enforced per-request
Support for custom tools and MCP servers
Multi-model support with bring-your-own-keys
Server-side prompt injection and PII screening
SSH dashboard interface for programmatic configuration
Hybrid search combining BM25 lexical and vector scoring
Vertex graph vector index with 2.29-2.75x throughput vs hnswlib
Vector-symbolic fact memory with holographic reduced representations
AES-256-GCM encryption at rest with Argon2id key derivation
Signed audit log with Ed25519 and W3C DID identity
Secure purge that overwrites deleted data with zeros
Crash-safe append-only log with checksumming
Native Rust API with Python HTTP client and Node.js bindings
MCP server integration for editors and AI agents
WARM Cloud sync, backup and verification without server access to keys or documents
What makes it different
Hard isolation between customers with no shared state or tenant leakage
Citations with document, page and quote provided automatically with every answer
Only two API calls needed to integrate grounded AI into any SaaS product
Customers never charged by Oberik; direct billing from their own LLM provider keys
Runs entirely locally in your process with no network calls or telemetry
Encryption at rest built into the open-source engine itself, not an enterprise add-on
Significantly faster vector search than hnswlib with graph-indexed vertex retrieval
Signed provenance and verified audit trail using C2PA, COSE and SCITT standards
Embedded library model eliminates dependency on external services or vendor lock-in
Oberik
warm-rust