Post-train specialized models for your task, creating an AI edge your competitors can't buy
Hybrid search, graph indexing, and vector-symbolic memory for AI agents
Stage
Established
Startup
Founded
Not given
2026
Based in
IL
US
Pricing model
Contact for pricing
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
Forward-Deployed Researchers provide end-to-end model training and optimization
Custom evaluation suite development from real tasks
Production-ready deployment with cost-quality trade-offs
Deployment flexibility including on-premises and VPC options
Data security with no retention and full traceability
Continuous model improvement from production traffic
Customer ownership of model weights and training recipes
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
Customers own specialized models trained on proprietary data, not rented general-purpose models
Achieve frontier-level quality at lower costs through specialized training
Five years of experience with diverse post-training and optimization methods
Models ship production-ready in weeks with ongoing improvement capability
Secure deployment with no data retention and auditable access controls
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
AI21
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