Everything your company knows, in one place. AI with a brain.
Your company's knowledge is scattered across chats, meetings, tickets and systems, and in the heads of a few people. Brain brings it together into a single memory that your team and your AI query in plain language, with a reference to the source in every answer. Nobody depends on someone remembering, and the AI stops making things up about your company.
Watch the video · 1:59It connects to every system in your company: GitHub, Jira, Slack, Confluence, Google Drive, meeting recordings, CRM, KYC, digital signature, Google Analytics, Google Ads, Meta Ads, email marketing, push notifications, cloud, Google Workspace, Figma, Clarity and more.
Any given day at your company. With and without Brain.
Two minutes of office chat: the question nobody can answer, and the same question with Brain.
The everyday chat
The question nobody answers, and the person who knew is gone.
The same situation, with Brain
The answer with its source, in seconds.
The numbers from the real case
What was measured in an implementation in production.
Illustrative dialogues · 1:59 · plays without sound
What Brain is
A company memory that your team and its AI query in plain language, with a reference to the source in every answer. It's not another app: it installs into the AI you already use.
Docs
Chats
Meetings
Tickets
Tools
Systems
this decided?
The problem
Knowledge is scattered across many places and in the heads of a few people.
A key person leaves and takes what they knew
The files stay. The why behind each decision leaves with the person.
Nobody knows why something was decided
The answer is scattered across chats, meetings, documents, tickets, tools and systems.
Everything depends on who's around that day
The same question gets a different answer, or no answer at all.
You pay for things nobody uses
Services and licenses that keep billing because nobody cross-checked the data.
The AI makes things up about your company
It confidently answers what it doesn't know, and there's no way to check.
New hires take months to get up to speed
They learn by asking whoever has time to explain.
Manual tasks that keep repeating
People with years of experience stuck on repetitive work that could be automated.
Decisions run on gut feeling
Conclusions and decisions based on assumptions, not hard data.
No time left to improve
The team lives putting out fires: nobody spots what can be automated or knows where to start.
Competitors are already moving faster
Whoever works with AI lowers their operating costs and passes it on to their prices.
Brain doesn't replace your team. It replaces depending on someone remembering, and it makes your team stronger.
AI on its own
An isolated AI fails in eight predictable ways. Each one has a control.
The solution
Brain takes the AI from the context of a single task to the context of all of your company's information.
Everything in one memory
All your sources, connected and searchable.
For the team and for its AI
Everyone queries the same source, in plain language.
Your expertise isn't left out
The AI brings the information; the judgment and the decision stay with your team.
First organize, then automate
With the context connected, repetitive processes can be automated with control.
Tap AI with Brain to see the difference.
Illustrative example with made-up data.
The AI only sees what you paste into the chat: a file, an error, a question.
It can query everything your company has already written down, and brings what each question needs.
source for everyone
For the whole company
Each area asks about its own work, with a citation for every answer.
Leadership
Why did we decide to switch providers last year?
Operations
What's the actual procedure for onboarding a customer?
Finance
Which services are we still paying for that nobody uses?
Sales
At which step of the process are we losing customers?
Technology
What breaks if we touch this service?
Legal
What terms did we sign with this provider?
Where it shows the most
Product and technology: that's where all its tools work, including the coding ones.
What it has already done in the case
Audit the cloud, find unused licenses, cross-check contracts and payments, read the sales process.
In any industry
It connects your information by the key your company already uses. An initial interview shows what information you have and how it connects.
Start small
A single area or a single source is enough to try it; the rest is added later.
Where it pays off
Situations almost any company will recognize.
You inherited someone else's system
What was delivered, finally readable.
Many roles, none sees everything
Ask once and it cross-checks the sources.
You're short on specialists
An agent that knows your real system.
Audit what you have running
And find out whether something was left there on purpose.
a person approves
In technology
Where it shows the most: AI delivers and a person approves.
Understand what you inherited
What a vendor who's no longer around built, explained through its tickets and its changes.
Estimate with your own data
How long something similar took, how many systems it touched, how many people it needed.
Deliver more, with control
The AI prepares the change. A person reviews and approves it: there's always a human in the loop, bringing their experience and knowledge to validate it.
Diagnose incidents
When something fails, it cross-checks alerts, deployments, tickets and changes to get to the cause.
How it works
Three steps, without touching your systems. You start on one machine and move to a server when the team needs it.
Connect your sources
Documents, chats, recorded meetings, tickets, repositories, tools and systems, with read access to your data.
Bring them together in one memory
A knowledge base on your own infrastructure, rebuilt from the sources.
Ask in plain language
Your team and your AI. If something isn't there, it says so instead of filling it in.
| Two ways to use it | On your machine | A server for the whole company |
|---|---|---|
| Who it's for | One person, with their own memory. The fastest way to get started and try it. | The whole team: one shared server where what the team knows lives, and everyone queries the same source. |
| Installation | Minutes: it installs with a single command. | Minutes as well: the server installs with the same procedure. |
| Loading the data | Then your sources are loaded and linked to each other. How long it takes depends on the volume of information, how well documented it is and how it relates across systems. | It's loaded once for everyone. The time depends on the volume, how well documented the information is and how it relates across systems. |
| Where it lives | A local file on your disk, with no server or cloud in between. | On a company server. |
| The AI | The one you already use: no extra key needed to install it or to query it. | No AI on the server: it doesn't consume tokens. Each person queries from their own AI. |
| What it cross-checks | Your own sources. | Everyone's, with what's approved kept separate from what's a proposal. |
| How it grows | It connects to the server later, and your own memory keeps running alongside. | Sources and people are added on the same base. |
under your roof
Your data
The information stays in your company.
On your infrastructure
The memory lives on your machine or in your cloud, with your logs.
Only what's needed goes to the AI
Nothing travels in full: only the fragments the search found for that question are sent, and the answer says which ones.
You decide what goes in
You choose which sources get loaded and what stays out of the answers, and an automatic review detects personal data.
Read-only first
Connections start by reading your systems. Later, writing can be enabled so the AI can start managing things, with a person approving.
The case · a 4-year-old fintech
The longest-tenured person on the project was leaving, the one who had been there since it was built. In about six weeks, what they knew was in the Brain, and operations continued without interruption, while output and the speed of developing and delivering new products went up: releases to production went from ~4 to 33 per month.
Product releases that reached production, by month
2026 · January through October 11 (* October, partial month)
Note: January–June average: 25 releases in 6 months, 4.2 per month; September (33) is 7.9 times that average. Includes full and partial releases. Since August it counts deployment batches closed in production; changes ship in smaller, more frequent batches. The number counts deliveries, not volume of work. What's comparable in volume is changes per business day.
Changes delivered per business day
3-week pace, as of Aug 21, 2026. It compares two ways of working, not the people.
Changes traced to their ticket
The gray arc marks the range between 50% and 87%. No AI change was merged without a person's approval. Measured across all PRs, as of Aug 21.
Case figures measured on the project and anonymized. They came from production, mistakes included, not from a demo.
Why now
The idea of a second brain for AI isn't ours. Bringing it to a company, with controls, is.
The personal second brain, popularized by Tiago Forte, author of Building a Second Brain (source).
Anthropic publishes an open standard for connecting AI to your data, now adopted by ChatGPT, Gemini and Copilot (source).
Andrej Karpathy, co-founder of OpenAI and now at Anthropic: what matters is giving the AI just the right information (source).
The “company brain” becomes a startup category.
Brain by Placedium, built while operating a real fintech, with controls so a company can trust what it answers.
And it keeps learning
The initial load is just the beginning. Your Brain grows with use: every new piece of data, every correction and every rule make it more useful for your company.
Living information
You keep loading what's new: tickets, chats, meetings and changes go into the memory and become available to everyone.
Cross-checks that used to be unthinkable
Knowledge and systems in the same query: analyses, statistics, projections, audits and sales opportunities that used to require gathering data by hand.
Rules that add up
Every rule and every correction you add, your Brain takes in and applies from then on.
The repetitive gets automated
Whatever is done twice becomes a procedure that the AI runs and a person approves.
Ask.
Decide.
“With AI, the demo is the easy part. The hard part is keeping it running on Monday.”
Let's talk. First step.
Find out how much of what your company knows can be recovered. A short conversation is enough to learn what sources of information exist.