Exabase
Exabase is an infrastructure layer for AI agents that provides self-improving memory, versioned cloud filesystems, multi-modal hybrid search, structured data extraction, and autonomous knowledge workers. It offers a managed data layer with APIs and SDKs, benchmarked as #1 on the leading AI memory benchmark.
Key facts
What is Exabase?
Give your AI agents persistent memory, context, and a cloud filesystem through a single API, so you ship faster without building and maintaining data plumbing.
Who is Exabase best for?
Teams shipping AI agents to production, startups building copilots, SaaS companies adding AI features, and enterprise teams replacing brittle RAG pipelines.
What are its main limitations?
- The product description does not specify any downsides, but potential limitations may include reliance on Exabase's platform for data portability and possible costs at scale beyond the free tier
Limitations are based on product materials or editorial synthesis; confirm on the official site.
Key features
- ✓Memory: Self-managing, self-improving memory system that stores facts, preferences, events, and handles contradictions with semantic retrieval
- ✓Bases: Isolated per-tenant cloud filesystem instances created via API with version rollback (Filesystem Snapshotting)
- ✓Resources: Portable context server for files, notes, and links with full CRUD, folders, tags, and semantic search
- ✓Deep Search: Multi-modal hybrid search at sub-document level across PDFs, audio, video, and images
- ✓Extract: Structured JSON extraction from PDFs, images, audio, video, and web pages via one endpoint
- ✓Workers: Autonomous AI agents that schedule and run tasks (search, organize, tag, create notes) without cron jobs or servers
- ✓Model-agnostic and framework-agnostic: works with any LLM and any stack
- ✓Production-ready: encrypted (SSL/AES-256), CASA certified, 99.9% uptime SLA
Use cases
- →Customer support bots with long-term memory that remember user history and preferences
- →Research agents that build and maintain their own knowledge bases automatically
- →Coding assistants that remember codebase context across sessions
- →Sales copilots that track deal context across multiple conversations
- →Learning platforms and healthcare agents that need persistent user data
- →Any agent, copilot, or assistant that interacts with the same user more than once
Pricing
Free
$0/mo
- · $30 free credit
- · 1k requests per hour
- · 1GB included storage ($0.06/mo per additional GB)
- · 200/mo included credits ($0.02 per additional credit)
- · Up to 100 Bases
Scale
$149/mo (billed yearly at $1490/year)
- · 5k requests per hour
- · 2TB included storage ($0.05/mo per additional GB)
- · 5k/mo included credits ($0.01 per additional credit)
- · Up to 10k Bases
- · Zero data retention policy
- · Basic Support
Enterprise
Custom
- · Unlimited requests
- · Negotiable included storage
- · Unlimited Bases
- · Priority Support
Free plan available with $30 credit and limited usage; paid plans start at $149/mo (billed yearly at $1490/year) with higher limits; Enterprise pricing custom.
Pros
- +Provides a complete managed data layer (memory, storage, search, extraction) instead of stitching together separate services
- +Self-improving memory with relationship tracking and contradiction resolution – more than simple retrieval
- +Per-tenant isolation (Bases) with version rollback, useful for SaaS multi-tenant scenarios
- +Model-agnostic and framework-agnostic, integrates with any stack via REST API or TypeScript SDK
- +Benchmarked #1 on leading AI memory benchmark (Exabase M-1)
Cons
- −The product description does not specify any downsides, but potential limitations may include reliance on Exabase's platform for data portability and possible costs at scale beyond the free tier
Positioning
- Core value: Give your AI agents persistent memory, context, and a cloud filesystem through a single API, so you ship faster without building and maintaining data plumbing.
- Ideal for: Teams shipping AI agents to production, startups building copilots, SaaS companies adding AI features, and enterprise teams replacing brittle RAG pipelines.
- Product type: API (REST) and TypeScript SDK
Frequently asked questions
What is Exabase?
Exabase is infrastructure for AI agents. It gives your agents memory, versioned file storage, AI deep search, and context automation through a set of APIs. Store what your agent learns, search inside any content type, and keep knowledge bases current automatically. Built for production use.
Who uses Exabase?
Teams shipping AI agents to production. Startups building copilots that need persistent memory. SaaS companies adding AI features with per-user data isolation. Enterprise teams replacing brittle RAG pipelines with a managed data layer.
What's the difference between Exabase and a vector database?
A vector database gives you semantic search over embeddings you create. You still build the ingestion pipeline, handle chunking, manage file parsing, and figure out citations yourself. Exabase handles the full stack from raw file to searchable, locatable result. It also does structured extraction, memory that tracks relationships and resolves contradictions, deep AI search inside files, versioned file storage with folders and tags, and scheduled agents that maintain your knowledge base.
What are Exabase Workers?
Autonomous agents that run inside your Bases on a schedule. Define a task in natural language, set a frequency (daily, weekly, monthly), and Workers handle it. They can search the web, organize files, tag content, create notes, and manage tasks. No cron jobs, no servers.
What does it cost?
Sign up and start building for free. See the pricing page for plan details and limits. Free tier includes $30 credit; Scale plan is $149/mo (billed yearly at $1490/year); Enterprise is custom.
What is a Base?
A Base is an isolated cloud filesystem instance. It's where you can store memories, files and more. Use it as a knowledge-base for your agent, or a secure data storage isolate for a tenant of your app.
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