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Cognitive Infrastructure for AI

Your AI forgets everything. ACE fixes that.

Not another feature list. Here’s what actually changes when your AI has persistent, structured memory.

A Day Without ACE vs. A Day With It

Without ACE

9:00amStart a new Claude session. Spend 15 minutes explaining your project architecture. Again.

10:30amAI suggests MongoDB. You chose PostgreSQL three months ago for specific reasons. It doesn’t know.

1:00pmA teammate asks their AI about the auth flow. Gets a hallucinated answer because their AI has zero context about your codebase.

3:00pmYou hit a bug you’ve seen before. Your AI doesn’t remember the fix from last week. You debug from scratch.

5:00pmSwitch from Cursor to Claude Code. Start over.

With ACE

9:00amOpen Claude. It already knows your architecture, your conventions, and what you were working on yesterday.

10:30amAI recalls you chose PostgreSQL, traces the decision back to the performance benchmarks and the 3 alternatives you rejected.

1:00pmYour teammate’s AI pulls from the same shared knowledge. The auth flow answer is accurate because it’s reading your team’s actual decisions.

3:00pmAI recognises the error pattern, finds the linked issue from last week, and applies the same fix. Thirty seconds.

5:00pmSwitch tools. Memory follows. Nothing lost.

The Moments That Matter

ACE doesn’t just store data. It changes how your team works with AI.

It’s your first week on a new team.

Your AI already knows every architectural decision they’ve made, every bug pattern they’ve hit, and every coding convention they follow. You’re productive on day one because your AI has the institutional knowledge.

A junior developer is about to override a critical design decision.

The Observer catches it before the PR lands. "This contradicts Decision #47: we chose event-driven architecture over polling because of the latency requirements documented in Issue #112." The decision links to the rationale, the alternatives considered, and the performance benchmarks.

Six months into a project, someone asks "why did we choose Kafka?"

Your AI traces it: the original decision, the 3 alternatives considered, the benchmark results that informed it, the 2 issues it caused, and the patterns that emerged from working around those issues. Not a Confluence page — a living graph of connected knowledge.

You’re debugging at 2am and the error looks familiar.

ACE finds the linked issue from three weeks ago: same root cause, different symptom. The fix is already documented with the exact code change and the architectural decision that caused both bugs. Your AI applies it.

Your security auditor asks how AI tools access company data.

All memory lives on your PostgreSQL database. You show them the schema, the namespace isolation, the audit trail. They can query it directly. There’s nothing on a third-party server they need to worry about.

$207M+ in competitor funding

14 Capabilities. One Clear Winner.

Everyone else built a memory API. ACE3 built a cognitive OS.

CapabilityACE3Mem0ZepLettaCognee
Structured Memory (10 types)partial
Knowledge Graphpartial
Autonomous Agentspartial
AI Genome / Behavioural DNA
Passport Auth
Session Intelligence
73 MCP Tools
Self-Hostedpartialpartialpartialpartial
One-Time Pricing
94x

ACE3 Founder is up to 94x cheaper than competitors over 2 years — with 8 exclusive features nobody else offers at any price.

Data compiled March 2026. Pricing from publicly available sources.

What We Believe

AI memory shouldn’t be a feature. It should be infrastructure. Every AI tool you use today has its own memory silo. Claude doesn’t know what you told Cursor. ChatGPT doesn’t know what Claude learned. Your knowledge is fragmented across tools that don’t talk to each other.

Memory needs structure to be useful. A flat list of facts is not memory. Real knowledge has relationships — this decision caused that bug, which led to this pattern, which informed that architectural choice. ACE stores 10 structured entity types connected by a temporal knowledge graph, because that’s how knowledge actually works.

Your data belongs on your infrastructure. We don’t store your memories. ACE connects to your PostgreSQL database — Neon, AWS, Supabase, local, whatever you choose. Standard tables you can query, export, or migrate anytime. We built ACE so your AI gets smarter without you giving up control.

Memory should maintain itself. Nobody updates documentation. That’s why ACE has 10 autonomous agents that catch contradictions, flag stale knowledge, surface risks, and clean up noise. You don’t maintain ACE. ACE maintains your team’s collective AI knowledge.

Common Questions

Is this just another vector database?
No. Vector databases store embeddings. ACE stores structured knowledge — decisions with rationale, issues with root causes, architecture with trade-offs, patterns with examples. Your AI doesn’t just find similar text. It understands why your team made specific choices.
Why not just use CLAUDE.md or .cursorrules?
Those are static files you manually maintain. ACE is living infrastructure — your AI writes to it, reads from it, and agents continuously maintain it. When your team makes a decision, it’s captured automatically. When context becomes stale, agents flag it. You don’t maintain ACE. ACE maintains itself.
What if I switch AI tools next month?
That’s exactly the point. ACE is the layer underneath. Your memory persists regardless of which AI tool you’re using today. Switch from Claude to Cursor to ChatGPT — the knowledge graph, the decisions, the patterns all carry over. ACE is the constant.
We already have Confluence / Notion / docs.
Documentation is written for humans. ACE is written for AI. Your Confluence page about auth architecture is 2,000 words. The ACE decision record is structured data your AI can reason over in milliseconds — with links to the 4 issues it caused, the 2 patterns it established, and the 1 decision it superseded.

Ready for AI that actually remembers?

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