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Cogni vs Argentic

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

Cogni compared with Argentic
Detail CogniArgentic logo Argentic
What it doesMemory that reasons An engine for long-running agents that rebuilds its prompt under a cap and runs on your budget
StageNot given MVP
FoundedNot given Not given
Based inUS Not given
Pricing modelFreemium Freemium
PricingFree plan at $0 USD; Pro plan at $5 USD per month. 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.
Key features
  • Entity-graph spreading activation for cross-vocabulary retrieval
  • Works with any LLM model
  • No LLM or GPU in retrieval path
  • Point-in-time and windowed recall
  • Timestamped memories
  • Fixed recall cost as memory grows
  • 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
What makes it different
  • Reaches answers across unrelated documents that share no keywords, where vector search scores zero
  • Deterministic retrieval with no model in the path, so results never vary between queries
  • Constant per-query cost regardless of memory size, even at 32,000 words
  • No infrastructure to run—no vector database, cluster, or GPU needed
  • Works with any model, so small local models gain the most from better retrieval
  • 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
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)4 no change since last checkNot checked yet no change since last check
Trust Flow (Majestic)20
Citation Flow (Majestic)219
Referring domains (Majestic)344

5 details filled in for both companies.

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