MemexAI
memexai.spaceInspectable memory infrastructure for multi-tenant AI agents, preventing 'forgetfulness' and enabling debugging.
Inspectable memory infrastructure for multi-tenant AI agents, preventing 'forgetfulness' and enabling debugging.
memexai.space1 discovery signals in the last 7 days.
MemexAI provides a drop-in memory infrastructure designed for AI agent products, addressing the common problem of AI agents 'forgetting' past interactions. It stores agent memories as scoped, Markdown-like files in Postgres, complete with revisions, access logs, and administrative operations. This allows developers to inspect every read, write, and consolidation, correct wrong facts directly in memory, and understand why an AI agent responded in a particular way.
Teams building AI products and multi-tenant AI agents, especially those struggling with agent memory, consistency, and debugging user interactions across sessions.
MemexAI tackles a fundamental challenge in AI agent development: reliable, consistent, and explainable memory. By offering inspectable and editable memory, it provides a powerful tool for debugging, improving agent accuracy, and ultimately reducing user churn for AI products. Its 'drop-in' nature and clear technical approach make it an attractive solution for developers.
AI-assisted scores estimated from public website information only.
This FounderDeck signal estimate of $750,000 reflects MemexAI's clear value proposition in solving a critical, recurring pain point for AI product developers: agent memory and explainability. The product appears well-defined with a clear technical architecture and a '90-second proof,' indicating a strong prototype or early product in a rapidly growing market. The estimate is not higher due to the absence of explicit public information regarding customer adoption, pricing models, or verified traction.
Valuation date: 2026-06-05. Estimate generated from public signals.
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