Your AI agents forget everything. Supabrain remembers.
Persistent, local-first memory for AI work. Your coding agents keep every decision, fix, and dead end, and so does every other agent you run, across sessions, tools, models, and machines.
From Supabrain's audited value model, assuming a US-based developer at about 64 USD/hour (roughly 130,000 USD all-in). Time figures modeled; team figures projected.
Every session starts from zero.
AI agents are brilliant inside a session and amnesiac across them. The model's own memory expires in about five minutes, so nothing survives a lunch break, let alone a project or a teammate.
Re-orienting an agent burns 30,000 to 150,000 tokens before it does anything useful. Your team re-solves the same bugs. A fix you shipped last month gets quietly undone because nobody remembered why the code looked that way.
The fix is not a bigger context window. It is memory that survives every boundary.
Capture. Recall. Compound.
Your agent connects once over the Model Context Protocol. From then on it remembers.
Saved as it works
Your agent saves the decisions, fixes, and dead ends as it works. A validator checks every entry on the way in, so the store stays signal, not a junk drawer.
One short query
Next session, on any machine, in any MCP client, it retrieves the right memory in one short query. No cold start, no re-explaining.
Everyone inherits it
Across your tools and your team, one person's solved problem becomes everyone's. The store gets more valuable every day it runs.
Memory that pays for itself in hours.
The token saving is trivial. The reclaimed time, the team-wide knowledge, and the capacity it unlocks are not.
About 155 hours a year you stop spending on cold starts, re-solved bugs, and re-explaining context.
From 31,000 USD at five people. Shared memory adds 0.9 to 2.5 people of capacity on top of each person's gain.
Re-entering any project costs a single query, not an afternoon. The work that simply would not happen otherwise.
Based on a US-based developer at about 64 USD/hour (roughly 130,000 USD all-in, at or below the US average). Modeled; team figures are projections.
One argument, six sides.
An asset, not a tool
The only line item in your AI stack that builds equity instead of depreciating. It even shows up in due diligence.
Yours across any model
Swap models freely. Your knowledge lives outside the model, portable and yours. Native memory is theirs; this travels with you.
Right, not just fast
Stops your agent being wrong the same way twice. Memory is the scar tissue agents lack, so a fixed bug stays fixed.
Built for agent fleets
The shared state layer as work goes multi-agent. Memory is to a fleet what a database is to an app.
Local-first
Your data and embeddings stay on your machine. No meter, no usage anxiety, no vendor lock-in.
Not just code
The same memory captures your finance, research, and marketing work. Wherever there is an MCP, Supabrain remembers.
We build Supabrain on Supabrain.
The founding team runs its entire operation through the product: 2,000+ memories across 46 projects and two machines in six months. The value numbers on this page come from an internally audited model built to survive CFO-level scrutiny, not from marketing.
Supabrain is in early access. No invented logos, no borrowed testimonials.
"A complete game changer. I would not do without it. Wherever there is an MCP, Supabrain saves the work that was done."
— Supabrain founding team
Not another memory tool.
Supabrain is the only persistent cache that survives across sessions, machines, and people, and it remembers your reasoning, not just your code. The hypotheses you ruled out are the most expensive thing to rediscover, and the first thing an agent forgets.
Unlimited memory. Flat price.
No meter, ever. Your knowledge grows; your bill does not.
- Full local memory
- Semantic and keyword search
- MCP access
- Single machine
- Everything in Solo
- Shared knowledge store
- Cross-machine sync
- Unlimited memories and queries
- SSO and SAML
- Agent ledger for governance
- Self-host or BYOC
- SLA
Pricing locks in for early-access teams. For comparison: Copilot Business 19 USD, Cursor Teams 40 USD per seat.
Questions, answered.
Which tools does it work with?+
Any MCP client, including Claude Code and Cursor, on any machine.
Is my data private?+
Local-first. Embeddings and search run on your machine. Nothing leaves unless you turn on sync.
Does it lock me into a model or vendor?+
No. Your memory is portable across any model, so a model switch costs you nothing.
How is it different from my AI's built-in memory?+
Built-in memory is per-vendor and disappears when you switch tools. Supabrain is yours, portable, and shared across your team.
Where do the time and dollar figures come from?+
An internally audited value model grounded in a live 2,000+ memory store. They assume a US-based developer at about 64 USD/hour (roughly 130,000 USD all-in, at or below the 2026 US average). Time figures are modeled; team figures are projections.
What does it cost?+
Solo is free. Teams pay a flat per-person price with unlimited memories and queries. There is no usage meter.
Is it available now?+
Supabrain is in early access. Join the waitlist for an invite.
New to agent memory? Read How to give Claude Code persistent memory →
Own your AI's memory.
Join early access. Bring it to any model, any tool, any machine.