AI that knows your business
Same team. Better work from AI.
Your AI tools are only as useful as the context they can reach about your business. We turn your scattered knowledge into a company brain your teams can use from Claude, ChatGPT, Copilot, or Cursor.
The real bottleneck
How you price, what good looks like, why your markets work differently — it all lives in meetings, Slack threads, and people’s heads, where no agent can reach it. That’s why the output still feels generic.
Every useful prompt needs another wall of company background.
Decisions, policies, customers, and edge cases are scattered across tools.
The best AI work comes from a few power users. When they're away, the leverage goes with them.
Leadership bought the tools. Your company still works the same way.
How it works
Those layers run on the operating loop covered in the playbook: capture the raw material, curate it into trusted context, let agents use it, then write approved learnings back.
Approved company context plus shared skills: strategy, decisions, workflows, meeting digests, repo knowledge, and your approved ways agents should do recurring work. Built through curated ingestion — not a bulk dump.
MCP servers, APIs, Slack bots, CLIs, webhooks, cron jobs, and optional connector layers connect agents to the brain and live source systems. The runtime runs the work; the Company Brain stays the trusted context layer.
Real operating loops redesigned around the brain — support, weekly reviews, PRDs. AI changes how work happens, not just how documents get drafted.
Decisions and learnings flow back into the brain through review, with owners and freshness dates. The system improves instead of rotting.
Curated ingestion
The hard part is not connecting Slack or Jira. It is deciding which thread becomes a decision record, which epic updates product context, which meeting transcript becomes a digest, and which live facts should stay in their source system.
Shared skills
When one operator finds the best way to prep a trading meeting, write a PRD, or turn a decision into a record, it becomes a reviewed skill the whole company can reuse from whichever agent they already use.
Agent runtime
A company agent runtime is the operating surface around the brain: chat assistants, CLI agents, webhooks, scheduled jobs, and recurring workflows that load approved context, use tools, and propose reviewed updates.
Once the brain and access layer are in place, this is the day-to-day — from whichever agent or runtime each team already uses: Claude, ChatGPT, Cursor, Slack, CLI tools, scheduled workflows, or internal assistants.
“Prep me for Monday's trading meeting.”
A brief with your open commitments, what changed, and what to push for. Five minutes, not forty-five.
“What did we decide about pricing?”
The decision, the reasoning, and the date — from the decision log, not from whoever happens to remember.
“Draft the PRD for this feature.”
A first draft in your house style, grounded in the product's real constraints and prior decisions.
Four ways to work together
For CEOs, COOs, and operations leaders turning AI activity into gains your company can measure — from free diagnosis to self-install, low-friction audit, and done-for-you implementation.
Free guide
Turn scattered company knowledge into agent-ready context: what to capture, how to curate it, and how agents access it. Start here if you are still learning the model.
Get the free playbook →Self-install · £299
The implementation repo: templates, filled examples, starter skills, ingestion guides, MCP spec, rollout assets, and the install skill your agent runs with you.
See the kit →Lowest-friction consulting · from £4.5k
A mostly-async two-week diagnostic for leaders who need the path clarified before anyone starts building: first team, source boundaries, owner model, business case, and next-step recommendation.
See the audit →Done-for-you
We build the first usable version of your company-wide AI context layer in 30 days: brain, access, skills, QA, owners, and rollout rhythm. From £12,000.
Explore the sprint →The main commercial path is simple: learn the model, self-install if you have an owner, use the audit if the shape is unclear, or go straight to the sprint if the need is clear. Build Week stays as a lighter hands-on option for kit buyers or audit leads who have one team ready to work.

Who’s behind this
I spent six years as COO of a multi-market commerce group, scaling it from 50 to 1,000 people with £100m+ P&L responsibility. Today I lead Product & AI Implementation for the same group — doing exactly what this page describes, team by team, across 50+ consumer sites.
10xyourteams is that system, installed in your company. It is based on the playbooks I run every week, with the trial and error already paid for.
50 → 1,000
people scaled as COO
40%
manual operational work removed with AI
15+
AI workflows in production
It shows you what context to capture, how to make it agent-ready, and what to do next — fix it yourself, get the gaps diagnosed (the audit), or have it built with your team (the sprint).