Hybrid search, graph indexing, and vector-symbolic memory for AI agents
Stage
Growing
Startup
Founded
2022
2026
Based in
US
US
Pricing model
Paid
Open source
Pricing
Pay-per-token for language models, per-minute for audio, per-image for image generation, and per-hour for GPU rental. No long-term contracts or upfront costs.
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
100+ machine learning models
Developer-friendly APIs
Text generation models
Image generation with Flux
Automatic scaling
Custom model deployment
Zero data retention policy
SOC 2 and ISO 27001 certified
Dedicated GPU clusters
Multi-GPU setups with SXM connections
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
Own cutting-edge inference-optimized infrastructure with secure US-based data centers
Zero retention policy with SOC 2 and ISO 27001 certification for data privacy
No long-term contracts or hidden fees with simple pay-as-you-go pricing
100+ production-ready models covering all major AI use cases
Customizable inference solutions tailored to cost, latency, throughput or scale priorities
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