ContextVault vs Exabase: Which is Better in 2026?
A comprehensive comparison of ContextVault and Exabase covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose ContextVault if:
- →You want more affordable paid plans (from $9.99/mo)
- →You need a broader feature set (6 features vs 5)
- →You need one vault every ai client reads from and writes to or memories scoped per user, per agent and per tenant
Choose Exabase if:
- →You need self-managing agent memory system, benchmarked by the vendor as first on two ai-memory benchmarks or bases — isolated per-tenant instances with version rollback
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ContextVault vs Exabase: At a Glance
Pricing Comparison: ContextVault vs Exabase
Understanding the pricing differences between ContextVault and Exabase is crucial for making the right choice. Here's how their plans compare side by side.
ContextVault Pricing
Exabase Pricing
💡 Pricing takeaway: Both ContextVault and Exabase offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from ContextVault and Exabase stacks up.
What Makes Each Tool Unique
🔵 Unique to ContextVault
Features available in ContextVault but not in Exabase:
- ✓One vault every AI client reads from and writes to
- ✓Memories scoped per user, per agent and per tenant
- ✓Durable across sessions rather than living in chat history
- ✓MCP and REST API access
- ✓Shared memory collections across an organisation on Team
- ✓Reduces per-request context load rather than stuffing every prompt
🟣 Unique to Exabase
Features available in Exabase but not in ContextVault:
- ✓Self-managing agent memory system, benchmarked by the vendor as first on two AI-memory benchmarks
- ✓Bases — isolated per-tenant instances with version rollback
- ✓Sub-document multi-modal hybrid search rather than whole-document similarity
- ✓Structured extraction from PDFs, websites, images, audio and video
- ✓Published credit exchange rates per operation, so cost is modellable up front
Use Case Recommendations
Best for: ContextVault
ContextVault is a shared memory layer for teams using AI, built on the observation that individual AI memory does not compound across an organisation. Each person's assistant learns their working context and then that knowledge dies in their session history, so the next colleague asking the same question starts from zero and the team pays the onboarding cost repeatedly. ContextVault stores memories once in a single vault that every AI client reads from and writes to, scoped per user, per agent and per tenant, and durable across sessions — replacing the usual sprawl of scattered Markdown files and out-of-date local project folders. Beyond avoiding duplicated explanation, the pitch includes a concrete efficiency argument: pulling the right memory reduces the overall context load of each AI request rather than stuffing every prompt with the same boilerplate. Access is over MCP and a REST API, so it plugs into whichever clients a team already uses. Pricing is organised around seats, groups and memory count rather than tokens: a 7-day free trial gives 1 seat and 50 memories, Solo at $9.99/month gives 1 seat and 500 memories with full MCP and API access, and Team at $49.99/month covers 10 seats, 15 groups, 2,500 memories and 15,000 monthly queries with member management and shared collections. Enterprise removes the caps and adds data export and security-review support.
Ideal use cases:
- •Teams or individuals who need one vault every ai client reads from and writes to
- •Teams or individuals who need memories scoped per user, per agent and per tenant
- •Teams or individuals who need durable across sessions rather than living in chat history
- •Teams or individuals who need mcp and rest api access
- •Anyone focused on memory workflows
- •Anyone focused on mcp workflows
Best for: Exabase
Exabase is context infrastructure for teams building AI agents — the storage, retrieval and memory layer that otherwise gets rebuilt badly in every agent project. Six components make up the platform. Memory is a self-managing memory system the vendor states is first on both of the leading AI-memory benchmarks. Bases are isolated per-tenant instances with version rollback, which is the piece that matters if you are shipping an agent to customers and each tenant's knowledge must stay separated and restorable. Resources hold files, notes and links as a portable context server. Deep Search runs sub-document, multi-modal hybrid search rather than whole-document vector similarity. Extract pulls structured data out of PDFs, websites, images and other formats — the website-to-Markdown endpoint is exposed as a standalone tool. Workers are autonomous agents that enrich a knowledge base on their own schedule. Usage is credit-metered with the exchange rates published plainly: one credit buys roughly 18 PDF extractions, 18 website extractions, 30 audio extractions, 0.8 video extractions, 65 memories, or 10 memories with inference mode enabled, which makes cost modelling possible before you commit. The vendor reports over 100,000,000 pages processed and offers a zero-data-retention policy from the paid tier. Deployment is positioned as production-ready, private by design and security-first, and the vendor runs a demo booking route for teams evaluating whether the platform fits before committing to the credit model.
Ideal use cases:
- •Teams or individuals who need self-managing agent memory system, benchmarked by the vendor as first on two ai-memory benchmarks
- •Teams or individuals who need bases — isolated per-tenant instances with version rollback
- •Teams or individuals who need sub-document multi-modal hybrid search rather than whole-document similarity
- •Teams or individuals who need structured extraction from pdfs, websites, images, audio and video
- •Anyone focused on ai-agents workflows
- •Anyone focused on memory workflows
🤖 Other AI Agent Infrastructure Tools to Consider
ContextVault and Exabase aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is ContextVault better than Exabase?
It depends on your needs. ContextVault offers 6 key features including One vault every AI client reads from and writes to and Memories scoped per user, per agent and per tenant, while Exabase provides 5 features including Self-managing agent memory system, benchmarked by the vendor as first on two AI-memory benchmarks and Bases — isolated per-tenant instances with version rollback. ContextVault uses a freemium model with a free tier, while Exabase is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is ContextVault cheaper than Exabase?
ContextVault is cheaper, starting at $9.99/month compared to Exabase's $149/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use ContextVault and Exabase together?
Yes, many users combine ContextVault and Exabase in their workflow. ContextVault excels at one vault every ai client reads from and writes to, while Exabase shines with self-managing agent memory system, benchmarked by the vendor as first on two ai-memory benchmarks. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between ContextVault and Exabase?
While both are ai agent infrastructure tools, ContextVault emphasizes one vault every ai client reads from and writes to, whereas Exabase is known for self-managing agent memory system, benchmarked by the vendor as first on two ai-memory benchmarks. The best choice depends on your specific workflow and feature priorities.
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