Company second brain

Your company knows a lot. It just can't remember any of it.

We help SMBs and smaller enterprises plan, prototype and build a company second brain: one governed memory of how the business works, that your people can ask and your AI agents can trust.

Most of what a company knows lives in heads, inboxes and chat threads. When someone leaves, it leaves with them. When someone new arrives, they spend months finding out what everyone else already knows. And when you switch on Copilot, Gemini or ChatGPT, it guesses, because the context it needs was never written down anywhere it could reach.

A company second brain fixes that. It is a shared, governed memory: decisions and why they were taken, how things are done, who owns what, what customers have told you, what has been tried and failed. Connected to the systems you already run, kept current by a few simple rituals, and readable by both people and AI agents, each seeing only what they are allowed to see.

Supercase helps you get there in steps you can stop after. We start with a short discovery that tells you what you have, what you are missing and what to build first. Then, if it makes sense, we prototype it with you in weeks.

What a company second brain is

Not a new wiki, and not another chatbot. A second brain is the layer that sits between your systems and the people and agents who need to know things.

For people

Ask in plain language and get an answer with a source. Where is the latest pricing, why did we drop that supplier, how do we onboard a customer in Finland. Less asking around, less redoing work someone already did.

For AI agents

Assistants and agents only work as well as the context they are given. The second brain is that context: current, structured and permission-aware, so the AI you have already licensed finally does something useful.

Governed

Every source has an owner. Every answer has a citation. Every reader sees only what they are cleared for. Stale content is flagged and either updated or archived. No source, no answer.

Yours

Open formats, your own storage, no lock-in to a single vendor or model. The memory outlives the tools that read it. If we disappeared tomorrow, the second brain would keep working.

How we start: Discovery, two to three weeks

Week one: where the knowledge is

Interviews with the people who hold it, a walk through your systems (email, chat, drives, CRM, ERP, tickets, meeting notes) and a map of what is written down, what is in heads and what contradicts itself.

Week two: what it must answer and who may see it

We write the fifty questions your company should be able to answer, test how many it can today, and audit permissions so you know what an AI would surface before you connect anything. GDPR and AI Act obligations are checked against the data you want to use.

Week three: the plan

An architecture that fits your size and systems, the first use case worth prototyping, a budget and a timeline. A plan you can run with us or without us.

Then: a working prototype, four to eight weeks

If Discovery shows it is worth it, we build the first slice as an innovation sprint: one use case, one or two integrations, a working assistant in the tools your people already use, measured against the question set every week.

You end with something people use, a number on how well it answers, and a clear recommendation: scale it, change it or stop.

What we check before any AI touches your data

  • Who can see what today, and whether that matches who should
  • Which personal data is in scope, and the legal basis and retention for using it
  • How the system refuses when it does not know, rather than guessing
  • Where the data is processed and under whose terms
  • How answers are cited so people can check them
  • What has to be disclosed to users under the EU AI Act

Where it goes next

A prototype that works creates a backlog: more sources, more teams, agents that act rather than answer. We carry that on with our other services. Developer support builds and integrates: connectors, retrieval, governance, evaluation, agents. AI transition support makes it stick: training, the weekly rituals that keep the memory current, and rollout team by team.

Many clients then keep a small knowledge-ops retainer: a few hours a month to curate, add sources, upgrade models and report on how well the second brain is answering. Or your own people do it. Either way, it stays yours.

Want to know what your company could remember?

Questions people ask before they call

Isn't this just Notion, SharePoint or Copilot?
Those are places where knowledge can live, or tools that read it. A second brain is the layer that decides what is true, who owns it, who may see it and how it is kept current. Without that layer, Copilot answers from whatever it can reach, including the wrong version. We often build on the tools you already pay for; the difference is the governance and the curation around them.
How long does it take?
Discovery takes two to three weeks. A first prototype takes four to eight. A company-wide second brain is a programme of months, but it is done in slices you can stop after, and every slice has to prove itself against real questions before the next one starts.
What does it cost?
Discovery is a fixed price agreed before we start. The prototype gets a fixed price from Discovery, based on how many sources and systems are involved. We do not sell open-ended hours. Email us and we will give you a figure after one conversation.
Are we locked in to a vendor or a model?
No. We prefer open formats and your own storage, and the retrieval layer is model-agnostic, so you can switch between providers or run models privately as the market moves. The memory should outlive the tools that read it.
How do you handle GDPR and the EU AI Act?
It is part of Discovery, not an add-on. We classify the data you want to use, establish the legal basis and retention, run an impact assessment where one is needed, audit permissions before anything is indexed and map the transparency duties that apply to AI assistants. We follow the Swedish Authority for Privacy Protection's guidance on generative AI.
Do we need our own engineers or data people?
No. For a company of twenty people the first version can be structured documents and the AI tools you already have, maintained by the people who own the knowledge. Larger or messier estates need retrieval infrastructure; we build it and hand it over so your own team can run it.
How big does a company need to be for this to make sense?
From about ten people. Below that, one person's notes usually suffice. The sweet spot is twenty to five hundred people: knowledge has spread beyond what anyone holds in their head, but the company is still small enough to build one memory rather than many.

Want to know what your company could remember?

You talk to the people who do the work. The first conversation is free and usually happens within a day.

Request a meeting

Office
Stockholm

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