# Your company already knows _more than it can use_. somai is the context engine that connects the intelligence already distributed across your business, giving people and AI the context to understand, decide and act. [see what changes when it connects →](#missing) [take the diagnostic · 10 min (opens in a new tab)](https://benchmark.somai.studio) § 01 The problem + insight The intelligence is already there. It is the connection between the pieces that is missing. ## Your business has intelligence. It just isn’t connected. Your company already knows a huge amount. But that intelligence is distributed across people, teams, systems and increasingly AI. Your sales team sees one part. Finance sees another. Operations sees another. Every AI tool sees the context it has been given. As AI moves from helping people to making decisions and taking action, those disconnected pieces become a bigger problem. ### The missing layer between your business and your AI tools is what we call the company brain. #### See what connected context changes. Explore the questions your business asks every day, and see what happens when the relevant context across your company is connected. The question Where are we leaving money on the table? What looks normal but isn't? What changed, and why? What does everyone else know that I don't? What should I know before I make this decision? What somai reveals The information was already there. The insight emerges when the context connects. --- § 02 The somai solution Nothing is ripped out. The systems stay where they are; what changes is that they finally share a context. ## Connect your company. Give AI the context to act. somai connects the information, knowledge and relationships already distributed across your business. It creates a shared company context that people and AI can work from. Then, on top of that context, somai provides the intelligence and controls to help AI understand, decide and act within your rules. your systems and the rest of what you run the company brain store · graph · context engine your people and their AI tools and whatever you move to next ### Connect Connect your existing systems, data, documents, knowledge and communications. [see the connectors →](/ai-native-company/#connectors) ### Understand Turn those disconnected pieces into a shared context that reveals relationships, meaning and insight. [see the framework →](/ai-native-company/#framework) ### Act Give people, AI and agents the context, permissions and rules they need to make decisions and take action. [see the use cases →](/blocks/#use-cases) Your systems stay in place. Your context becomes connected. Your AI becomes more capable and more controlled. --- § 03 Future-state stories Not features. Four ordinary moments in a company that has its context, and what each one is worth. ## What becomes possible when your company has context? ### what if Everyone had a company-aware personal assistant? Find answers, context and expertise instantly. Less searching. More doing. Example. who owns the Northgate renewal? Priya Raman, Operations. It renews on 14 March. * contract * meeting note * crm what it changes human benefit Find answers, context and expertise instantly, without searching across systems or chasing colleagues. business benefit Less time finding information. More time making decisions, serving customers and getting things done. commercial outcome Faster decisions, better customer interactions and more productive teams. ### what if Every decision came with the context you need? See what happened, what changed, what others know and what might be missing. Less guesswork. More confidence. Example. * what changed margin down 4 points since March * who knows finance, support * what’s missing the renewal terms what it changes human benefit See what has happened, what has changed, what others know and what might be missing before you decide. business benefit Make faster, better-informed decisions with less risk. commercial outcome Better decisions at greater speed and scale. ### what if Every AI understood your business? Give AI your company’s knowledge, relationships, policies and history. Less prompting. More understanding. Example. without context I don’t have information about that account. with context Northgate renews on 14 March, owned by Priya, with two issues still open. what it changes human benefit Give AI access to your company’s knowledge, relationships, policies and history rather than starting from scratch every time. business benefit Deploy useful AI faster, across more of the business, with greater consistency and control. commercial outcome More capable AI across the business, without creating disconnected pockets of intelligence. ### what if Your AI agents knew when to act? Give agents the context, permissions and rules they need before they take action. More automation. More control. Example. 1. understand 2. check 3. act 4. escalate what it changes human benefit Let agents understand the situation, follow your rules, know what they are allowed to do and bring in the right human when needed. business benefit Automate more work without giving up control. commercial outcome Scale AI-driven action with confidence and governance. [see the use cases →](/blocks/#use-cases) --- § 04 Trust and control Trust is not a promise here. It is what you can see, what you can set, and what you can take back. ## Intelligence you can trust. You control what AI can reach, what it is allowed to do, and you can see why it answered the way it did. ### Your data stays yours. somai works with your existing information without taking ownership of it. ### Your systems stay in place. Connect the systems and tools you already use. No rip-and-replace. ### Your rules govern AI. Set the permissions, policies and boundaries that determine what AI and agents can see and do. ### Every insight has context. Understand where an answer came from, what it is based on and what might be missing. We do not publish client names, logos or quotes. The engagements themselves are set out in full, with what was installed and what the team was left running. [Where it’s proven →](/blocks/#engagements) --- § 05 How it lands Four stages, ending in handover. Bounded engagements measured in weeks. ## How it lands ### 01 - Blueprint. We start with a discovery call. Next comes the question audit. We collect about two hundred actual questions from your business, and we tell you which ones a company brain answers well, which need a different tool, and which nothing can answer until the outstanding work has been completed. You get that in writing before you commit to anything. ### 02 - Build. The brain is installed: your knowledge organised, your systems connected, and relevant, genuine answers being provided. Engagements are bounded, with their duration measured in weeks. Senior people, working with your team. ### 03 - Handover. Your team is in charge of it: the files, the connections, and the knowledge to run it without us. Ownership is the design, not a provision. ### 04 - Grow. Add blocks. Each block causes the brain to carry out one task - the accounts that you serve, the cash that you are owed, the obligations that you have. Every block reads the same brain, so each one you add makes the others sharper. [book a discovery call →](mailto:hello@somai.studio?subject=Book%20a%20discovery%20call) --- § 06 Questions we hear The six that come up first, answered plainly. ## Questions we hear ### “We have a shared drive and an AI copilot. Isn’t that a company brain?” Not at all - and this is evident when the first difficult question arises. A copilot on a shared drive searches whatever is stored: drafts, duplicates, the version that was withdrawn in March. A company brain holds what someone has decided is true, with an owner and a source on every entry. One is a search box over your mess. The other is a single source of truth. ### “Who can see what?” You decide, and the brain enforces it. Who may see what is built into the system, not into a polite instruction the AI is asked to follow. And some things should never go in at all; we agree that list before anything is captured, not after. ### “Are we too small for this?” The honest test is not headcount. It is whether the same questions get answered from scratch every week, whether knowledge leaves when people do, and whether AI tools you’ve paid for have quietly disappointed. If none of that is true yet, you don’t need us - and we’ll say so. ### “What happens in week one?” The twenty answers your business needs most, written down properly and connected. Not an import, not a crawl. It is deliberately unglamorous, and it is the step that decides whether everything after it works. ### “Which AI tools does it work with?” The ones you already use, and the ones you’ll switch to next year. The connection layer speaks the open standard AI assistants understand, so the brain outlives any one tool choice. ### “Where does it run?” In the cloud, with a provider, or on your own servers. Either way it is yours: plain files, an index that rebuilds from them, and nothing trapped in anyone’s platform - ours included. --- § 07 Studio What we are, what we are not, and the constraints we hold. ## A studio of senior operators. No juniors, no offshore, no associates in the room. somai is a team who have run the kinds of companies we work in: heads of operations, engineering leaders, CFOs, chiefs of staff, and founders - most of the bench with scars earned under regulators, auditors and risk committees. We take the principle that the studio installs and the client operates seriously. We do not sell retainers, managed services, or ongoing seats. Our job is to make sure your team runs it without us. [Meet the team - company context →](/context/) --- § 08 Thinking Our thoughts from the studio. Shared when we have a lesson or example to build on. ## Essays from inside the build. Lessons we’ve found worth writing down. [RSS](/rss.xml) 1. 06.09 18 August 2026 ### [Automation makes the wrong work faster](/thinking/automation-makes-the-wrong-work-faster/) Automation makes work faster. It does not ask whether the work should happen - and in most organisations the larger cost is not work done slowly, but work that should never have started. [read more ](/thinking/automation-makes-the-wrong-work-faster/) 2. 06.08 30 July 2026 ### [Why every company will build a brain](/thinking/why-every-company-will-build-a-brain/) On the company brain - why twenty years of trying to build one failed, what changed, and what it means for the shape of the firm. [read more ](/thinking/why-every-company-will-build-a-brain/) 3. 06.07 21 July 2026 ### [Models compress. They cannot invent your company.](/thinking/compression-not-invention/) A language model is brilliant at turning many facts into one clean answer, and unreliable at turning too little into the truth. That asymmetry - not the model's cleverness - is the real constraint, and it is why grounding matters more than scale. [read more ](/thinking/compression-not-invention/) 4. 06.06 26 June 2026 ### [Most AI spend never reaches the P&L](/thinking/most-ai-spend-never-reaches-the-pnl/) The failure rate isn't a model problem. It's an operating-model problem - and it has a specific cause. [read more ](/thinking/most-ai-spend-never-reaches-the-pnl/) 5. 06.05 23 June 2026 ### [What ai-native actually means](/thinking/what-ai-native-actually-means/) The market defines ai-native by birth certificate - the firms born with the model. The truer definition is structural, not chronological, and it is fully available to the company you already run. [read more ](/thinking/what-ai-native-actually-means/) 6. 06.04 14 May 2026 ### [What stays human](/thinking/what-stays-human/) As working intelligence becomes abundant, the scarce thing is no longer analysis. It is judgement, taste, and the will to mean it. [read more ](/thinking/what-stays-human/) 7. 06.03 16 April 2026 ### [Decisions with the model in the loop](/thinking/decisions-with-the-model-in-the-loop/) AI as a tool you pick up, or an agent that replaces you. Both pictures miss the real change. The shift is to the loop. [read more ](/thinking/decisions-with-the-model-in-the-loop/) 8. 06.02 12 March 2026 ### [A company your model can read](/thinking/a-company-your-model-can-read/) A company knows far more than it can say. Until that knowledge is made legible, a model cannot do anything useful inside it. [read more ](/thinking/a-company-your-model-can-read/) 9. 06.01 10 February 2026 ### [The end of scarce intelligence](/thinking/the-end-of-scarce-intelligence/) Every company alive today was built around the assumption that working intelligence is scarce. That assumption has quietly stopped being true. [read more ](/thinking/the-end-of-scarce-intelligence/) [all thinking →](/blog/) --- § 09 Start The value is already there. The diagnostic shows you where it is trapped. ## How much of your company’s intelligence can you actually use? Your company contains more intelligence than you can currently see. The AI-Native Diagnostic measures one thing: how much of how your company runs a model can actually reach and act on today. Not how much AI you already use. the diagnostic, in outline 25 questions · 10 minutes * What your company knows * Your market * How the work gets done * How you decide * How you stay in control Your result is your own. Nothing is filled in until you take it. An audit, not a quiz. Twenty-five plain-English questions about your business. No technical knowledge needed, one question at a time, and your progress saves as you go. It reads the five systems every company runs on and names the one holding the most value out of a model’s reach - your biggest block. Then it puts a number on the prize: what an AI-native rebuild could be worth for a firm your size, modelled from public benchmarks. That is a population estimate, not a forecast for your business. You end with a one-page brief, emailed to you and yours to keep. No licence, no retainer hook. The diagnostic is itself AI-native: a model reads your situation in your own words and writes your brief, while a calibrated instrument keeps the score honest. Private by design - banded inputs only, never your raw financials. [take the diagnostic · 10 min →(opens in a new tab)](https://benchmark.somai.studio) Or [book a discovery call](mailto:hello@somai.studio?subject=Book%20a%20discovery%20call), or write to [hello@somai.studio](mailto:hello@somai.studio).