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warm-rust vs CogniCore

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

warm-rust compared with CogniCore
Detailwarm-rust logo warm-rustCogniCore logo CogniCore
What it doesHybrid search, graph indexing, and vector-symbolic memory for AI agents Memory that follows you between AI apps
StageStartup Not given
Founded2026 Not given
Based inUS Not given
Pricing modelOpen source Open source
PricingOpen 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. Not given
Key features
  • 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
  • Connect to Claude via custom connector in Settings
  • Add to ChatGPT with developer mode
  • Automatic session save for Claude Code and Codex
  • Save and resume sessions with brief summaries
  • GitHub sign-in for private separate memory
  • Delete individual memories or all data by email
  • Zero model calls to save a session
  • Session brief generated in ~450 tokens
What makes it different
  • 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
  • Shared memory across multiple AI apps and agents, not confined to one app
  • Setup in about one minute with no credit card or waitlist
  • Open source code so users can verify data handling
  • No data selling, ads or use for AI model training
  • Private per-account database with no cross-account access
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)26 no change since last checkNot checked yet no change since last check
Trust Flow (Majestic)121
Citation Flow (Majestic)2410
Referring domains (Majestic)5612

4 details filled in for both companies.

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