Hybrid search, graph indexing, and vector-symbolic memory for AI agents
Stage
Not given
Startup
Founded
Not given
2026
Based in
US
US
Pricing model
Not given
Open source
Pricing
Not given
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
Governance: checks proposed AI actions against defined rules before execution
Recorded decision records that can be reviewed, replayed and verified later
Evaluation: compares AI agent performance using representative test cases and expected outcomes
Optimization: recommends model and cache candidates based on usage, prices and evaluation evidence
Regress detection identifies changed action paths and quality regressions
On-premises and private cloud deployment
Integration with existing AI tools via connectors and wrappers
No model training on customer data; separate data boundaries from external AI providers
Cost comparison and optimization across model and cache configurations
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
Independent accountability: checks run inside your systems, not asking another AI to audit AI
Your people keep authority: Forge produces decision evidence, your business enforces results
Recorded decision evidence that auditors and regulators can examine
Designed for consequential work in regulated industries like financial services
Not another dashboard: integrates into your workflow without replacing your AI tools
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
Forge Orbital
warm-rust