| What it does | An engine for long-running agents that rebuilds its prompt under a cap and runs on your budget
| Context infrastructure for AI agents
|
|---|
| Stage | MVP
| Startup
|
|---|
| Founded | Not given
| Not given
|
|---|
| Based in | Not given
| GB
|
|---|
| Pricing model | Freemium
| Freemium
|
|---|
| Pricing | Prototype: free during beta, then from December 16, 2026 it costs $1 per 1,000 agent calls after 1,000 monthly included calls. Production: $20 a month with 20,000 agent calls included, then $1 per 1,000 calls after that. Top-ups: $1 per 1,000 calls, from $10 to $500 at a time, never expiring.
| Not given
|
|---|
| Key features | - Prompt rebuilt from journal under token cap at each step to keep it bounded as history grows
- Spending limits checked before each model call at token prices you declare
- Resume after crash without repeating finished actions
- Tool calls returned as actions for your code to carry out
- Proof of what ran: check prompts, re-run engine, download hash-chained journal
- Integrations with Vercel AI SDK, OpenAI Agents SDK, LangGraph, Mastra, Pydantic AI
- MCP server for Claude Code, Claude Projects and Codex
- Works with any model via bring-your-own-key
- TypeScript and Python clients for HTTP API access
| - Memory system with self-managing advanced memory
- Isolated per-tenant instances with version rollback
- Portable context server with files, notes and links
- Sub-document multi-modal hybrid search
- Structured data extraction from PDFs, websites and images
- Autonomous agents for knowledge base automation
- 99.9% uptime SLA
- AES-256 encryption at rest and SSL in transit
- TypeScript SDK and REST API
- Model-agnostic and framework-agnostic
|
|---|
| What makes it different | - Bounded prompt under a fixed cap while history grows, so costs per call stop climbing on long sessions
- Every run recorded with cryptographic proof: rebuilable prompts, hash-chained journal, re-runnable engine
- Resumes from crash without repeating finished actions using stable idempotency keys
- Budget enforcement before each model call, not reactive overage billing
- No model key storage or logging; your provider bills you directly
| - Cut token spend by up to 81% through persistent agent memory instead of full context window stuffing
- State-of-the-art on two leading AI memory benchmarks
- Full-stack data layer eliminating need for multiple services
- Production-tested at scale powering Fabric platform
- Self-improving memory that tracks relationships and resolves contradictions
|
|---|
| Free plan | Not given
| Not given
|
|---|
| Open source | Not given
| Not given
|
|---|
| Platforms | Not given
| Not given
|
|---|
| Public API | Not given
| Not given
|
| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 29 ● no change since last check |
| Trust Flow (Majestic) | 0 | 11 |
| Citation Flow (Majestic) | 9 | 32 |
| Referring domains (Majestic) | 4 | 122 |