AI implementation for startups
Your team already has AI. Most of what it writes still gets rewritten, because it doesn't know your company. I set companies up to run on AI: I teach it your business, connect it to the tools your people already open, and train each team to use it in their real work. The system I install is called Cadence, and you keep it.
You didn't build your company with AI in mind. It's not too late.
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What makes a company AI-centric
Your business is probably missing one of these four things. Each depends on the one before it.
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01
Codified
The company is written down, outside people's heads, where a machine can read it.
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02
Current
Someone owns keeping it accurate as the business moves.
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03
Governed
You've decided in writing what the company may claim and what it may not.
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04
Connected
Your people reach it inside the tools they already open.
AI output that sounds like your company, carries only approved claims, and needs approving rather than rewriting.
What changes once it's built
- First drafts come back right.
- Your AI workflows build assets in your language, brand-aligned, speaking to exactly the right person.
- Every team uses AI in its daily work.
- Once a register decides what may be claimed, a junior can draft something a customer will read without anyone policing every sentence for invented numbers.
- The company stops living in people's heads.
- When the person who holds your positioning leaves, the positioning stays, and so does the reasoning behind it.
- Each asset generated costs less than the last.
- Your tenth page doesn't need the research your first one did, because the answers are already written and every asset draws on the same set.
What I set up
Five pieces, built in order. Each one makes the next one work.
- A company your AI knows. Your positioning, offer, buyers, voice, and market, written down once so every tool draws on the same answers.
- Guardrails on what it says. What your company may claim and what it may not, so nothing goes out with an invented number or a credential you don't hold.
- Your tools, connected. ChatGPT or Claude, your docs, whatever your engineers code with. Your people keep the tools they already use, and those tools stop guessing.
- Teams that know how to use it. Each team learns the prompts and habits that fit its own job, on its own work.
- The first workflows running. We pick the jobs where AI saves the most time and build those first: drafts, research, reporting, follow-up.
How an engagement runs
Free consultation
We discuss your AI-readiness and score your company's context-layer management within your workflows.
Build your company's brain
We take in your data, interview your team to fill in gaps, and create a comprehensive brain built collaboratively and approved by you.
Workflow connections
We connect your company's brain to your workflows and train your team on how to better use AI in their work.
Your team runs on it
I keep your company's brain current as the business moves, and we keep building the workflows that drive the most value for your business.
Let's work together
Start free. Add the pieces you need, when you need them.
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Start here ยท Free
Consultation
An educational discussion on your business's AI-adoption challenges and successes.
- Where your AI performs and fails
- Score your business against the Cadence framework
- Current needs and opportunities for improvement
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One-time project
Build
Create your company's comprehensive context layer with company and industry data.
- Intake from your data, interviews to fill gaps, comprehensive industry research
- Comprehensive registers and documentation, written
- Human-focused website and AI-optimized retrieval, in place
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Monthly retainer
Context Management
Maintain and expand the use cases of your AI's context layer.
- Reconciling what your teams hand me
- Every document kept current
- Finding the workflows worth building
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Retainer or project
Execution
The work built out of the documents.
- Pages, campaigns, playbooks, decks
- Briefed and checked against the documents
- Runs with Context Management or on its own
Common questions
What do you need from my team?
Your existing data to start with, then interviews only on what that data doesn't cover, so nobody spends an hour telling me something the files already say. You read and approve each document as it lands, while it's still cheap to change.
Do my people have to learn new software?
No. Every team keeps the workflow it already has and points it at the same context layer, because what they interact with is the writing, not my software. A consultant leaves with the knowledge in their head. I leave it installed in your company.
What happens after the build?
I keep your company's brain accurate as the business moves, and keep building the workflows that drive the most value. Part of keeping it true is settling what your teams disagree about, which is strategic work wearing administrative clothing. You rule on it, I write down what you decided, and we name the executive who makes those rulings in the agreement.
Do I own what you build?
Yes, from the first day. The context layer sits in a repository you own, and the site that renders it is password-protected. Nothing about the deliverable depends on software I run. I'm one person, which is a real risk to weigh before an ongoing relationship, so whenever you stop working with me, you leave with:
- Every document, and the full dated history of how each one changed.
- The index: one file that tells any AI what's in the folder, which document answers which question, and what it may never claim.
- A guide written for your team, including the prompts that only work because this exists.
- A short manual for keeping it accurate, a report on what's current and what's stale, and an honest note on what rots first.
- What to look for in whoever you hire to take it over.
How is this different from a knowledge base, a chatbot, or AI licenses?
Each of these helps, and each one stops at the same wall: the model still doesn't know your business.
| What you can buy | What you get | Where it stops |
|---|---|---|
| Licences for everyone | Access | Everyone can log in, and the output doesn't change |
| Prompt training or a prompt library | Better questions | Your team asks better questions and the model still doesn't know your business |
| A knowledge base or wiki | Pages people can browse | It stores what people wrote, with no register of what the company may claim |
| A chatbot over the wiki | Search | It answers confidently out of pages nobody checked |
| A CRM | A record of every customer and deal | It holds your customer records, and not your positioning, voice, or what you may claim |
| A fine-tuned model | Your house style | It picks up how you sound and still doesn't know your facts |
| Cadence | A company the model actually knows | Somebody has to sit down and write it |
Buy the last one first and everything above it gets more out of your money.
Playbooks
- What Is an AI Operating System for a Company?
- AI Agent Operating System: The Context Layer Your Team Needs
- AI Governance Framework for a Small Company
- How to Build an AI-Native Operating System for a Startup
- AI Readiness Assessment: Score Your Company in Eight Questions
- AI Knowledge Base vs. AI Operating System: What Startup Teams Need
Start with a call.
Let's have a free consultation on your AI usage and company workflows.