Today we're launching TekMemo — a memory layer designed specifically for AI agents that need durable, queryable context across sessions.

The Problem

AI agents today suffer from amnesia. Every conversation starts from zero. Context windows help, but they're:

• Expensive — paying for tokens you've already processed
• Limited — hard caps on how much fits
• Fragile — one context overflow loses everything
• Opaque — no way to inspect, search, or curate what the agent "knows"

The Solution

TekMemo gives agents a persistent memory layer with:

Capability	What It Means
Core Memory	Stable project briefing — facts the agent must know every time
Notes Memory	Durable records — decisions, constraints, preferences, summaries
Recall	Semantic retrieval over indexed memory fragments
Graph Memory	Entities, relationships, and semantic connections
Cloud Sync	Multi-device, multi-agent shared memory with conflict resolution
Vector Search	Semantic recall across all memory types
Reranking	Precision filtering with deterministic fallback

Quick Start

Install TekMemo:

npm install @tekbreed/tekmemo

import { Tekmemo } from "@tekbreed/tekmemo";

const memo = new Tekmemo({
  rootDir: "./.tekmemo",
  projectId: "my-app",
});

// Read durable, project-wide facts (lives in memory/core.md)
await memo.core.read();

// Record a durable note (appended to memory/notes.md)
await memo.notes.record({
  content: "User prefers dark mode with high contrast.",
  kind: "preference",
  tags: ["ui", "theme"],
});

// Recall relevant context for an agent — works offline, no API keys
const hits = await memo.recall("What does the user prefer for UI?");

What's Next

• Visual memory inspector — Browse and edit memory in the browser
• Team workspaces — Shared memory with access controls
• Memory analytics — Understand what your agents actually remember
• More vector adapters — Pinecone, Weaviate, Qdrant support

Get Started

• Installation Guide
• Architecture Overview
• API Reference

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Have questions? Open a discussion or file an issue.