PersistentmemoryforAIagents.
Contexta is the memory layer that gives AI agents continuity across conversations, models, and deployments.
It turns every interaction into structured, persistent knowledge: automatically redacting secrets, resolving contradictory statements when users change their mind, and delivering sub-50ms hybrid recall.
Built for autonomous agents that can't afford amnesia.
Context windows were never engineered to act as durable memory stores. Damping raw conversation history into prompts triggers attention degradation, explodes API costs, and fails on evolving facts. Contexta extracts discrete truths and maintains them over time.
Hybrid Multi-Layer Recall
Vector search captures intent, keyword search finds exact codes and ports, and graph hops connect ideas across past sessions in under 50ms.
Self-Healing Memory
When a user updates a preference, older facts are automatically archived and linked to the new truth. Your agent never contradicts itself.
Zero-Trust Credential Redaction
API keys, bearer tokens, passwords, and sensitive card numbers are scrubbed at the gate before indexing. Secrets never enter durable memory.
82.2% Token Reduction
Stops flooding LLMs with 25k raw transcript tokens. Contexta packs only the top 3–5 high-priority facts into your prompt, slashing API bills.
100% Local & Offline
Runs sovereignly on your hardware using embedded Qwen3 embeddings and rerankers. Zero cloud dependencies, zero subscription markups, 100% private.
Zero-Leak Multi-Tenancy
Strict tenant boundaries and isolated namespaces prevent data crossover between users, projects, and parallel agent threads. Safe for enterprise swarms.
The open source AI memory engine.
Engineered for high-accuracy agent reasoning. Benchmarked across multi-turn dialogue, temporal truth revision, and multi-hop graph expansion.
Multi-hop associative entity graph traversal
Reciprocal Rank Fusion across 3 layers
Continuous state supersession without deletion
Built for privacy first.
Contexta does not store or train on your private code, conversation contexts, or sensitive credentials. All secrets and PII are redacted at the boundary, ensuring air-gapped readiness and enterprise compliance.
How Contexta works.
Raw context windows were never designed to hold durable state. Shoveling unbounded chat history into LLM prompts leads to hallucination, context drift, and fourfold API costs. Contexta provides a dedicated external memory plane.
Sanitize & Distill
Continuous observation at the agent loop with automated secret masking and discrete fact distillation.
- Credential Masking: Automatically detects and redacts API tokens, bearer keys, passwords, and card numbers before persistence.
- Atomic Fact Extraction: Distills conversational turns into canonical statements of fact with confidence and importance scoring.
- Zero Context Bloat: Eliminates conversational filler, keeping memory stores concise, clean, and signal-rich.
Self-Healing Dream Cycles
Background reflection workers that resolve contradictions and version evolving knowledge when users change their minds.
- Bi-Temporal Lineage: Automatically marks outdated facts as superseded (valid_to = now()) when new instructions arrive.
- Deduplication & Clustering: Merges overlapping facts and binds entities into an interconnected knowledge graph.
- Read-Age Decay: Continuously re-weights memory salience based on access frequency and recency so stale data fades naturally.
Sub-50ms Tri-Modal Recall
Unified Reciprocal Rank Fusion delivering high-precision recall in sub-50ms without slow cloud roundtrips.
- Multi-Layer Synthesis: Fuses lexical precision for exact identifiers, semantic vectors for intent, and graph hops for multi-session relations.
- Local Neural Reranking: Cross-scores candidates with a local neural reranker (Qwen3-Reranker-0.6B) to filter out noise.
- Injected Salience: Returns only the top 3–5 high-precision facts, reducing context token overhead by over 80%.
Right now, the sovereign Open Source edition is live. All core memory algorithms, retrieval optimizations, and operator console dashboard features are actively developed, maintained, and published with regular releases under the Apache 2.0 license.
For developers and teams who prefer zero DevOps overhead and don't want the hassle of self-hosting, managed Edge Functions will be launching soon. This will deliver 1-click plug-and-play integration with the Model Context Protocol (MCP) and agent frameworks.
Memory that stays true, private, and explainable.
Context windows were never designed to hold durable state. Contexta separates raw conversational exhaust from verified truth, maintaining an external memory plane across months of interaction.
Self-Healing Bi-Temporal Memory
When user preferences evolve, older facts are retired, not duplicated.
Naive vector databases append new vectors indefinitely. When a user switches from 'PostgreSQL' to 'Cloudflare D1', both facts are retrieved, triggering model hallucinations.
Contexta detects fact collisions, marks valid_to = now() on obsolete records, and links lineage. Active agent queries filter WHERE valid_to IS NULL.
// Ingestion detects fact collision & applies bi-temporal supersession:
UPDATE memory_record
SET valid_to = NOW(), superseded_by_id = 'mem_new_88f'
WHERE user_id = 'usr_42' AND valid_to IS NULL;
// Active agent queries always retrieve pure current truth:
SELECT * FROM memory_record
WHERE user_id = 'usr_42' AND valid_to IS NULL;Engineered for enterprise sovereignty and scale.
100% Offline Local Architecture
Runs sovereignly on your hardware using embedded Qwen3 models (Qwen3-Embedding-0.6B and Qwen3-Reranker-0.6B on port 8001). Zero cloud API key requirements.
Zero-Trust Multi-Tenancy
Zero missing WHERE clauses. Queries are cryptographically scoped by organization and user tenancy at the TenantScopedRepository base kernel.
Universal Model Context Protocol
Plug-and-play memory for Claude Desktop, Cursor, and Antigravity IDE over standard Stdio and SSE transport with one line of JSON config.
100% Explainable Provenance
Every retrieved memory hit links back to origin session ID, turn timestamp, confidence score, utility rating, and supersession history for enterprise compliance.
Context windows were never engineered to be memory.
Shoveling raw conversation history into every prompt is slow, expensive, and error-prone. Contexta separates raw conversational exhaust from durable, verified knowledge.
Exploding Token Costs & Slow Responses
Dumping 30 pages of raw chat history into every prompt drains your API budget and makes the LLM sluggish. As chats grow, earlier context gets lost or diluted.
Memory Amnesia & Contradictory Answers
When users change their mind (like switching frameworks, locations, or database ports), basic vector databases remember both versions. The agent gets confused and hallucinates.
Accidental Secret Leaks (PII & API Keys)
Developers and agents often paste code snippets containing passwords, API tokens, and credentials. Sending raw history to cloud memory stores risks exposing private data.
82.2% Token Reduction & Lightning Speed
Contexta extracts discrete facts and injects only the 3 to 5 precise nuggets needed for the current conversation turn. Prompts stay tiny, fast, and cost-efficient.
Bi-Temporal Truth & Self-Healing Memory
When a new fact updates an old one, Contexta automatically archives the obsolete record and links the new truth. Your agent stays consistent across months of dialogue.
Zero-Trust Ingestion Redaction
API keys, JWTs, passwords, and credit card numbers are detected and masked at the door before indexing. Sensitive credentials never touch durable memory.
Works with the stack you already use.
Private by default, proven in depth.
Engineered for enterprise security and air-gapped compliance. Your private code, conversation contexts, and credentials never leave your cryptographic perimeter.
Three-Layer Tenant Isolation
Repository scope, Postgres row-level security, and CI cross-tenant tests. One customer or agent swarm can never read another tenant's memory graph.
Deterministic Ingestion Redaction
Passwords, API keys, JWTs, OTPs, and Luhn-validated credit cards are stripped synchronously at the front door before anything touches the memory store.
100% Offline Sovereignty
Runs completely on your local machine using embedded Qwen3 models. Zero external API calls, zero telemetry leakage, 100% air-gapped readiness.
BYOK Privacy (Optional Online)
If you opt into online mode, your own OpenAI, Anthropic, or DeepSeek API key drives extraction. Your memory tokens never pass through third-party reselling pipelines.
Full Audit Logs & Provenance
Every observation, redaction event, and retrieval touch includes cryptographic tenant metadata and timestamped execution records for SOC 2 audits.
VPC Peering & Self-Hosting
Deploy sovereignly via Docker Compose on your own private VPC, Kubernetes cluster, or bare-metal server with zero external cloud lock-in.
Frequently asked questions.
Everything you need to know about Contexta's open source architecture, offline defaults, truth maintenance, and roadmap.
Give your agents a memory they can trust.
Sub-50ms hybrid retrieval. Real-time credential redaction. Self-healing truth maintenance. Free and open source under Apache 2.0.