Hybrid search, graph indexing, and vector-symbolic memory for AI agents
Interactive worlds for people and AI to build, learn and solve problems together
Stage
Startup
Not given
Founded
2026
Not given
Based in
US
Not given
Pricing model
Open source
Free
Pricing
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.
Not given
Key features
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
Photo to brick set conversion with 3D preview and parts list
Workbench for collaborative brick-by-brick editing
MCP server integration with Claude Code, Codex, Cursor and more
Build structure checking and validation
OAuth sign-in with no token storage
Offline build access with local browser storage
Export digital manuals and wanted parts lists
Interactive environments for AI training
Consent-based human demonstration recording
What makes it different
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
Checked outcomes - part connections and build validity are verified by software before delivery
Real objects from photos - converts pictures into buildable brick sets with actual parts that exist
People and AI work on the same design simultaneously within the workbench
Measurable AI learning with transfer testing across different worlds