Production-ready context infrastructure for AI agents. Auto-sync from your codebase, docs, and data sources. Memory, retrieval, and knowledge assembled in one layer. Built for scale.
$20/month | 7-day trial (card required) | 5 minute setup
import { RetainDB } from '@retaindb/sdk';
const context = await whisper.query({
query: "How do we handle authentication?",
includeMemories: true, // User preferences
includeGraph: true, // Code relationships
});
// Context stays fresh automatically
console.log(context.answer);Not just retrieval. A complete state system designed for production AI applications.
Connect 15+ data sources. GitHub, Notion, Slack, Discord, and more. Your context updates automatically when your data changes.
Remember user preferences, facts, and context across sessions. Scoped per-user, per-session, or per-agent.
Understand code relationships. Which functions call what? What depends on this API? Graph traversal gives deeper context than vector search alone.
Vector similarity + BM25 ranking + optional reranking. Get the most relevant results every time.
Reduce token usage with smart compression. Save costs without losing context quality.
Built for SaaS. Isolate data per organization. Rate limiting, usage tracking, and webhooks included.
Pick the method that fits your stack
Use from any language. Full OpenAPI spec available.
Type-safe clients for JavaScript/TypeScript. Python & Go coming soon.
Model Context Protocol for Claude Desktop. Zero configuration needed.
Build AI coding assistants that understand your entire codebase. Index repos, traverse dependencies, answer questions about your architecture.
Give your chatbot access to help docs, FAQs, and conversation history. Remember user preferences across sessions.
Index research papers, build knowledge graphs of concepts, and keep everything up-to-date as new papers are published.
Connect Notion, Confluence, Slack, and Google Docs. Make company knowledge searchable across all platforms.
Four layers that work together to give your AI the perfect context
Point to your GitHub repos, Notion pages, Slack channels, or any of 15+ data sources
We chunk, embed, and build knowledge graphs automatically. Code relationships, entity extraction, all done.
Hybrid search (vector + keyword) + knowledge graph traversal + conversation memory = best results
Auto-sync on git push, doc updates, or schedule. Your context is always current.
┌─────────────┐ ┌──────────────┐ ┌────────────┐ ┌──────────┐ │ Data Sources│─────▶│ Knowledge │─────▶│ Hybrid │─────▶│ Your │ │ 15+ types │ │ Graph │ │ Search │ │ Agent │ │ │ │ + Embeddings │ │+ Memories │ │ │ └─────────────┘ └──────────────┘ └────────────┘ └──────────┘ GitHub, Notion Auto-indexed Sub-50ms p95 Perfect Slack, Confluence Real-time sync context answers
Real benchmarks from production workloads
Your data stays yours. Always encrypted, isolated, and compliant.
All data encrypted with AES-256. Keys managed via AWS KMS.
In progress. GDPR and CCPA compliant today.
Multi-tenant architecture with complete org-level data isolation.
Choose US, EU, or Asia regions for data residency requirements.
Enterprise SSO with Okta, Azure AD. Role-based access control.
Complete audit trail of all API calls and data access.
Pinecone and Weaviate are vector databases. RetainDB is a complete memory and context layer that includes retrieval, memory management, connectors, and context assembly. Think of it as the full stack instead of only the database.
Yes! We support OpenAI, Cohere, and custom embedding endpoints. You can even bring your own vector database if you have a custom setup.
RetainDB is $20/month. Your 7-day trial starts after you add a card, and you are charged automatically when the trial ends unless you cancel.
Rate limits are per API key. Pro includes 100K queries/month. Enterprise limits are custom.
Not at this time. If you have strict requirements, reach out and we can discuss options.
You get 30 days to export your data via API. After that, all data is permanently deleted. We can provide longer retention for Enterprise customers.
RetainDB versus leading memory and context systems
| Feature | RetainDB | Mem0 | Nia |
|---|---|---|---|
| Hallucination Rate | 12.5% | ~35% | 52.1% |
| Context Relevance | 92.5% | ~80% | 85.0% |
| Memory Consistency | 98.2% | ~85% | 90.0% |
| Knowledge Graphs | Limited | ❌ | |
| Temporal Reasoning | Basic | ❌ | |
| 15+ Data Connectors | ❌ | Limited | |
| Auto-Sync | Manual | Manual | |
| Hybrid Search (Vector + BM25) | Vector only | Vector only | |
| Oracle Research Mode | ❌ | ❌ | |
| Multi-Tenant Ready | Build yourself | Build yourself | |
| Setup Time | 5 minutes | 1-2 days | 1-2 days |
Benchmarks run on production workloads. See full benchmark results →
Included in every RetainDB plan. No extra cost.
$20/month | Memory and context | Cancel anytime
These pages connect the broad context story to the pages buyers and developers use to validate the implementation.
Context answers are stronger when the agent also remembers users and prior decisions.
A guide to working context, retrieval, and persistent memory.
A practical view of assembling the right state before the model call.
Useful when the team is debating retrieval versus continuity.
Benchmark proof for the memory layer that complements context assembly.
A commercial comparison page for buyers evaluating adjacent memory stacks.
Useful when the team is deciding between context infrastructure and memory layers.
A direct comparison against another memory-and-context orchestration product.