What they do
One shared memory built from meetings, Claude sessions and Slack
How close to us
3, close
Shared team memory is the core product; agents read it, but it is not for consultancies specifically.
Wedges
- W9 Ask my agent before you book my time direct
- W1 Trusted 24/7 coding for small startup teams adjacent
- W3 Company memory from every call, for consultancies adjacent
L1 Company brain (knows the organisation) 3, strong
L2 Agent team (runs agents, tools, approvals) 1, light
L3 Does and learns (finishes, checks, measures, updates the brain) 0, none
Who buys
- Firm size
- sme
- Buyer type
- developer
- Role
- team leads and founders of small teams that use AI agents every day
- UK
- not known
Their own description (from YC)
One memory for your team's agents.
Turn every meeting, Claude session, and Slack chat into context your team and agents share.
Full teardown
Memory Store (YC Spring 2026): teardown vs XMarts
In one line: Memory Store sells a shared memory that the AI agents of a small team write to and read from, over MCP, at a price per person [site] [yc]. Threat: 2, because it is the same "company brain" idea for the same kind of small team and it is YC funded, but it is early, has no named customer and stops at one layer [site] [press].
1. Fact file
| Item | Finding | Source |
|---|---|---|
| What they say | YC line: "One memory for your team's agents." Live site: "Give your AI your team's context." | [yc] [site] |
| Founded, team, funding | Founded 2025, YC Spring 2026, 4 people, San Francisco. Funding amount not public. One directory lists YC and Rebel Fund as investors in a pre-seed round dated June 2026, amount undisclosed. Another aggregator lists $500K, which I could not confirm. | [yc] [press] |
| Founders | Diwank Tomer (CEO, Thiel Fellow, builds AI products since about 2012, earlier company powers phone ordering for Domino's and Wingstop). Ishita Jindal (CPO, built the open source agent orchestrator Julep AI, 7K+ GitHub stars, earlier product roles at Jar and Lenskart). What YC likely saw: two founders who already built agent infrastructure and hit memory as the recurring problem (inference). | [yc] [blog] |
| Customers | None named. The site shows no logos. The sample email uses anonymised names. | [site] |
| Price | $150 per team member per month after a 7-day trial for "qualifying teams". Every member who signs in is billed, including read-only members. | [site] |
| Path | Site moved from memory.store to mem.store, and the product is now called MemStore on the live page (rename date not found, inference that it is recent). The YC page promises auto-capture from Slack, Gmail and Granola. The live page lists GitHub, Fathom and a Claude chat importer, and says Slack decisions are not captured automatically. | [site] [yc] |
2. Their proposition, reverse engineered
| Part | What they do |
|---|---|
| Who buys | Teams "that use agents daily" and accept that teammates' agents can search each other's stores [site]. In practice a founder or team lead on a small team (inference from the 3-person price example) [site]. |
| The pain | AI makes teams faster but multiplies what they must track. Decisions get lost in Slack, insights sit in transcripts, knowledge lives in chat sessions and heads [yc]. |
| The promise | Your agent starts a session knowing where work stands and what teammates are doing [site]. |
| How it works | An MCP server with three tools: checkin (where work stands), record (save decisions and progress), recall (answer from your store or teammates' stores, with sources) [site]. Connects GitHub and Fathom, imports past Claude chats [site]. The YC post also names Slack, Gmail and Granola, and "Briefs", docs that update themselves when new memories arrive [yc]. |
| The output | A morning email per person: what changed, what is blocked, who is waiting on you [site]. Answers with sources when an agent asks. |
| Proof style | None yet. No customer number, no usage number. The only counts are the founders' past work (Julep stars) [yc]. |
| Who sells it | Self-serve trial plus a booked call [site]. No sales jobs open [yc]. |
| Price model | Per seat, $150 a month, all signed-in members billed [site]. |
| The story | Memory is the bottleneck for people and agents. The founders built Julep because memory was the repeated blocker (they say) [yc]. |
3. Positioning
- Category they claim: "Company Brain" on the YC page [yc]. On the live page the claim is smaller: team memory for agents, with a "company brain" listed as the thing they are building toward [site].
- Category a YC partner would put them in: shared agent memory for small AI-native teams (inference).
- What they want to be known for: the memory layer every team's agents read from and write to.
- Where they sit on the map: L1/L2/L3 = 3/1/0. Buyer: sme, developer-led (inference).
4. Three layers vs ours
| Layer | Them (score + evidence) | Us (Marton's logs show) |
|---|---|---|
| L1 Company brain | 3. Memory is the whole product. Agents record and recall across a team, with sources [site]. Memory is written by agents and people, and Slack is not auto-captured [site]. | A vault of about 1,400 pages, 112 call transcripts and about 8,700 customer quotes, searchable by meaning. Learns from calls and checked work. |
| L2 Agent orchestration | 1. They do not run agents. Agents connect to the store and share state (checkin and recall); no approvals or handovers are described [site]. | About 5,600 jobs run by agents from three makers, each checked by a different AI, then automatic tests. |
| L3 Execution and learning | 0. No work is done and no result is checked. Rollups and Briefs summarise [site] [yc]. | Every failure gets a record and an automatic check (about 160). Offer feedback lines fell from 44 to 18 as rules were added. Only about 15% of jobs reached the main code, and merges were unreliable in October. |
5. Same and different
| Topic | Same or different | Them | Us |
|---|---|---|---|
| Core belief | Same | Agents and people both need shared context [yc]. | Same (brief). |
| Buyer | Similar | Small teams using agents daily [site]. | SMEs and scale-ups (brief). |
| How memory fills | Different | Agents and people record; connectors for GitHub and Fathom [site]. | Calls filed automatically into one knowledge base. Marton's logs show 112 transcripts. |
| What happens next | Different | Memory is read back as answers and emails [site]. | Marton's logs show agents do and check work from the memory. |
| Learning | Different | Memory grows; no check that a memory was right or useful (inference, not stated on the site) [site]. | Marton's logs show rules added from failures and feedback. |
| Owner of the result | Different | The customer's own agents do the work [site]. | The system does the work and measures it (one business so far). |
| Delivery | Different | Self-serve MCP plus calls [site]. | System plus the two founders. |
| Proof | Different | None public [site]. | Our own business only; no customer number yet. |
| Price | Different | $150 per seat, per month [site]. | Not set yet. |
| Privacy stance | Open on both | The site leaves retention, deletion and training questions open [site]. | Client data safety is an open question in our own brief. |
6. Wedge overlap
| Wedge | Fit | Why |
|---|---|---|
| W9 Ask my agent before you book my time | direct (inference) | Recall from teammates' stores, "what teammates are working on", and a "who is waiting on you" email do the same job: fewer status meetings, same small-team buyer [site]. They do it without a per-leader agent kept current by checked work. |
| W1 Trusted 24/7 coding for small startup teams | adjacent | Memory for Claude Code and Codex sessions plus a GitHub link; they feed coding agents context but do not run or check them [site]. |
| W3 Company memory from every call | adjacent | Fathom and Granola meetings flow into memory [yc] [site], but the buyer is an agent-using team, not a services firm. |
7. Whitespace (where they stop)
- Layer gap: memory only. They do not run, check or measure work [site]. To own it we need one workflow where memory feeds agents that finish work and a checked number moves.
- Buyer gap: the site names no sector and no country, and shows no customers [site]. UK consultancies and agencies are not addressed. To own it we need calls with named people at those firms who say they have the pain.
- Number gap: no result, no usage figure [site] [yc]. To own it we need one before/after number from a live customer workflow.
- Price gap: $150 per person per month, and read-only users are billed [site]. A 30-person firm would pay about $4,500 a month (arithmetic on their price). To own it we need a price tied to the result, not to seats.
- Speed gap: not a gap. They offer a 7-day trial and a three-step setup [site]. We would need first value in days to match them.
8. For the YC application
- Proven today: Marton's logs show his system keeps a company memory (about 1,400 pages, 112 call transcripts, about 8,700 quotes) and that the same system runs about 5,600 agent jobs, each checked by a different AI, with about 160 failure records that each added a check. Memory Store's public product stops at memory [site].
- Draft answer to "how are you different from Memory Store?": DRAFT. "Memory Store stores what a team's agents remember. Our system already uses its memory to run agents that do the work and check it, every day, on our own business." Founders say it their own way.
- Future claim (needs proof): "Our memory improves because every result is checked, and one workflow for a UK firm gets measurably better." Needs one customer workflow run for 4+ weeks with a before/after number and a rule-change log tied to checked runs.
- What we understand that they don't: a memory is only as good as the checks on what goes into it, and you need the work loop to get those checks.
needs proofwith a customer; Marton's logs show it on his own work only. - Copyability (M3): medium. Evidence: their roadmap says they will add tools and flag overdue commitments and decisions that affect people [site], which is a step toward acting, so the idea is in reach. But running and checking agents is a different product, and they only have 4 people and sell per seat to agent users (inference). Not
hard, so M3 can not score above 3 against Memory Store alone. - Why now (M4): None found in this teardown. MCP adoption is general AI progress, not a dated change tied to our edge.
- Do not claim: "company brain" as our headline (their YC line uses it and a YC partner already funded them). Anything about their product being weak on capture quality (not tested). "No one does the checked loop" (UNVERIFIED across the field; only this company was checked). A buyer count or customer for our system (none yet).
9. Ideas worth taking
- Three-verb agent contract: checkin, record, recall. Small and easy to explain in one breath [site].
- A personal morning email that says what changed, what is blocked and who waits on you. A buyer can feel this on day one [site].
- Open the product to a stranger in a 7-day trial with a three-step setup. Fast first value, no sales call needed [site].
10. Unknowns
- Real customers, usage and revenue. The homepage and YC page show none. Look for a Launch YC comment thread or founder posts on X.
- When the rename to MemStore happened and why the live page is narrower than the YC pitch. The Wayback Machine could not be fetched here; check it by hand.
- Funding amount. Directory figures conflict ($500K versus undisclosed).
- Whether they have a security page, retention policy or SOC 2. The site names none, and its own sample email lists the questions as open.
- Whether Briefs and Slack auto-capture ship today or are roadmap. The YC page says yes; the live page says Slack decisions must be recorded by you or your agent.
Sources
- mem.store (memory.store redirects here) [site], checked 2026-10-19
- YC company page [yc]
- YC Launch post: Memory Store, your company's brain [yc], undated ("5 months ago" on the page)
- VCBacked profile [press], June 2026 data
- YC Tier List review [press]
- Julep docs [docs], founders' earlier product
- Composio post by Diwank Tomer, Julep AI [blog]
Technical detail
- Slug
- memory-store
- Lens hash
- 179096c479
- Pass
- deep
- Stale
- no