Run and fine-tune models. Deploy custom models. All with one line of code.
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
Paid
Open source
Pricing
Most models billed by time based on hardware used (CPU $0.000100/sec, T4 GPU $0.000225/sec, L40S GPU $0.000975/sec). Some models billed by input/output tokens or generated items. Private custom models billed for all uptime; fast-booting fine-tunes billed only for active processing.
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
Run thousands of community-contributed open-source models
Fine-tune models with custom data to create specialized versions
Deploy custom models using Cog, an open-source packaging tool
Automatic scaling based on demand
Pay only for compute time used
Image generation from text
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
One-line code interface for running models without ML expertise
Automatic infrastructure scaling without manual management
Open-source community with thousands of production-ready models
Fine-tuning capability to customize models for specific tasks
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
warm-rust