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
Freemium
Open source
Pricing
Free plan with 10,000 monthly credits; Starter at $50/month with 40,000 credits; Pro at $500/month with 400,000 credits; Enterprise with custom pricing. Additional pay-as-you-go credits available. Pricing based on a credit system where 1,000 credits equals $1.25.
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
Agentic OCR parsing with semantic understanding for complex document layouts
Support for 130+ file formats including PDFs, Office docs, images, and spreadsheets
Structured data extraction with schema-based, LLM-powered agents
Document classification and splitting based on natural language rules
Enterprise-grade RAG indexing and retrieval pipeline
Handwritten text parsing and structured extraction
Table and chart extraction with structured row and column relationships
Cloud SaaS or VPC deployment with flexible data residency options
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
4x cheaper than frontier labs, 5x more accurate than other APIs
Auto-correction loops with recursive checks that detect and fix errors automatically
Task-specific specialist agents that route content to the right expert
HIPAA, GDPR, and SOC2 compliant with enterprise-grade security
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