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Argentic vs Exabase

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Argentic compared with Exabase
DetailArgentic logo ArgenticExabase logo Exabase
What it doesAn engine for long-running agents that rebuilds its prompt under a cap and runs on your budget Context infrastructure for AI agents
StageMVP Startup
FoundedNot given Not given
Based inNot given GB
Pricing modelFreemium Freemium
PricingPrototype: 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 planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)Not checked yet no change since last check29 no change since last check
Trust Flow (Majestic)011
Citation Flow (Majestic)932
Referring domains (Majestic)4122

5 details filled in for both companies.

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