Memory Store

Competitive Intelligence & Product Roadmap

Shared memory layer for a team’s AI agents.

Company Overview

Memory Store is an AI memory layer that records team context and recalls it inside agents via MCP. It serves AI-heavy founders, engineers, product teams, sales teams, and operators rather than named public customers.

Latest Intel

Zeitgeist tracks private signals to determine where the company is heading strategically.

New Intel: Memory Store is pushing one MCP-accessible memory layer across Claude, ChatGPT, Cursor, meetings, and Slack. That makes native assistant memory and workplace search the real competitive line.

What They're Building

The company's public product roadmap & what they're committed to building.

Claude & ChatGPT MCP Setup

Memory Store publishes setup paths for using one shared memory inside Claude and ChatGPT through MCP.

Cursor and Raycast Guides

The product is being pushed into daily developer and operator workflows rather than kept as a standalone notes app.

Fathom Meeting Sync

Meeting summaries and action items can feed the same memory layer used by coding and chat agents.

Gmail and Slack Sync

Pricing lists Gmail and Slack sync as coming soon, pointing toward automatic workplace ingestion.

Reflect

Reflect is listed as coming soon for multi-agent deep research over a team’s stored memories.

Founder and Key Execs

Ishita Jindal

Co-Founder (built Julep AI, worked as a data scientist at IBM, and had product roles at Lenskart and Jar)

Diwank Singh Tomer

Co-Founder (2013 Thiel Fellow, founder of Julep AI, former Head of Engineering at Jar, and former CEO of Whitehead AI)

Founder Force Multiplier

The founders bring prior agent infrastructure experience from Julep AI and hands-on consumer and engineering scale experience from Jar, Lenskart, IBM, and Whitehead AI. That mix fits a product that needs both technical memory architecture and fast adoption by AI-heavy teams.

Funding History

2026 | YC Spring 2026 company
2026 | Public pricing shows Pro at $20 per month and Teams starting at $100 per month
2026 | No disclosed priced round, lead investor, valuation, or named angels found

Competitors

LangMem:

LangMem is a developer framework for agent memory, while Memory Store sells a shared team memory layer across end-user AI tools.

OpenMemory:

OpenMemory points toward local private memory, while Memory Store focuses on team context and MCP-connected workplace tools.

ChatGPT Memory:

ChatGPT Memory is native to one assistant, while Memory Store is built to carry context across ChatGPT, Claude, Cursor, and other MCP clients.

Claude:

Claude can hold context inside its own product, while Memory Store positions itself as shared memory that Claude and other agents can query.

Cursor:

Cursor owns the coding-agent surface, while Memory Store aims to provide project and decision history that follows users beyond the IDE.

Memory Store

's Moat:

Workflow switching costs are the likely moat path: once team decisions, meetings, and code context sit in one MCP-accessible store, replacement requires moving the history and habits.

How They're Leveraging AI

Structured Team Memory Retrieval

Memory Store turns meetings, chats, notes, decisions, and agent sessions into shared context that AI tools can recall across Claude, ChatGPT, Cursor, Slack, and other MCP clients. The product is aimed at teams that need agents to remember project, customer, and decision history without repeated copy-paste.

Meeting And Agent Session Summarization

Memory Store converts meeting summaries, action items, Claude sessions, Slack chats, and coding-agent activity into durable memories that can be searched later by other tools. This turns transient work into reusable team context.

Multi-Agent Research Over Stored Memories

Memory Store lists Reflect as a coming product for multi-agent deep research over stored memories. The likely use case is a research workflow where agents query a team’s private context, synthesize prior decisions, and return grounded briefs.

AI Use Overview:

Memory Store uses embeddings, summaries, entity extraction, and retrieval explanations at ingest and recall time, making the memory layer more structured than raw prompt stuffing.

Agent Infrastructure

Tasklet

Runs cloud AI agents for recurring knowledge-work workflows.

Firebase-grade infra founders are attacking workflow automation as LLMs start to operate software, with early ARR and USV as both customer and investor.

Decagon

AI agents that autonomously handle enterprise customer support across chat, email, voice, and SMS.

Agentic AI for customer support is one of the few GenAI categories with clean ROI math, and Decagon has locked in the blue-chip logo sweep that compounds into category default status.

Manus

Autonomous AI agent platform that executes multi-step business workflows end-to-end

A model-agnostic orchestration layer with real browser and shell execution captured viral enterprise demand faster than any US agent startup, a thesis validated by Meta's $2B acquisition.

Bubble Lab

Gives ops teams an AI super-employee in Slack that automates cross-platform workflows.

Zapier and Make require users to think in workflows. Bubble Lab's Pearl lives in Slack and runs multi-step operations (Jira, Stripe, Notion) from plain English, which means ops teams adopt it without learning a new tool.

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