Prove it. Then build it.
Almost every engagement starts with an AI audit, because knowing what not to build is worth more than any single feature. Once we know what's real, here's what I build to deliver it.
AI Audit
Find out where AI actually pays before you spend a dollar building.
A fixed-fee assessment of how your business really operates. I interview the people doing the work, follow the data, and score every AI opportunity on business value against implementation effort. You get a prioritised roadmap with cost and payback estimates, and you keep it whether or not I build anything. Full detail on the AI audit page.
- Workflow & data mapping
- Opportunity scoring
- ROI & payback estimates
- Risk & readiness review
- Phased roadmap
- Findings walkthrough
AI Strategy & Roadmap
A plan your finance director will actually sign off on.
Turning findings into a sequence you can fund. Each phase is scoped, priced, and tied to a measurable outcome, ordered so early wins pay for later ambition. It includes the things to deliberately not do yet, which is usually the most valuable page in the document. Where you need it, this extends to a build-versus-buy assessment and a sober read on vendor quotes.
- Phased delivery plan
- Build vs buy analysis
- Vendor quote review
- Budget & sequencing
- Success metrics
- Team & skills gaps
AI Agents & Assistants
Software that reads, decides, and acts, inside guardrails you set.
An agent is only useful if it can reach your real systems, and only safe if it can't reach the wrong ones. I build agents that triage inboxes, draft quotes and replies, pull records, and complete multi-step work, with explicit limits on what they can touch and human approval in front of anything consequential. Every action is logged, so when something goes wrong you can see exactly what happened.
- Inbox & ticket triage
- Drafting & summarisation
- Multi-step task agents
- Retrieval over your docs
- Permissions & guardrails
- Full action logging
Workflow Automation
The cheapest return in the building, and it rarely needs AI at all.
A good share of what people want AI for is really just work that was never wired together. Intake, onboarding, approvals, invoicing, reporting, and reminders can run accurately and around the clock on plain deterministic automation, which is faster to build, cheaper to run, and doesn't hallucinate. I use a model only where judgement is genuinely required.
- Client onboarding flows
- Automated invoicing
- Document generation
- Scheduled reporting
- Approval routing
- Reminders & follow-ups
AI Voice & Messaging
Every call answered. Every lead replied to. Nothing to voicemail.
A voice agent that picks up around the clock, answers the questions it should, books appointments straight into your calendar, and escalates anything urgent to a person. Paired with instant text-back so a missed call or a web form gets a real reply within seconds, qualified by AI and handed to your team once there's something worth their time.
- 24/7 call answering
- Live appointment booking
- Missed-call text-back
- Web-lead instant reply
- Smart escalation to humans
- Call summaries & logging
Custom AI Development
When nothing off the shelf fits the way you actually work.
The bespoke end: extracting structured data from messy documents and email, internal copilots that answer staff questions from your own policies and history, classification and routing, and drafting tuned to how your business talks. Built and evaluated against your real examples, not a demo dataset, so you know the accuracy before it touches a customer.
- Document & email AI
- Internal knowledge copilots
- Data extraction & entry
- Classification & triage
- Evaluation & accuracy testing
- Model selection & cost tuning
Integration & Data Readiness
AI can only be as good as what it's allowed to reach.
The unglamorous foundation, and the reason a lot of AI projects quietly fail. Most businesses run on a patchwork of apps that don't share data, so people become the integration. I connect your CRM, email, calendar, forms, billing, and spreadsheets, then get the underlying data clean and consistent enough that a model can be trusted with it.
- CRM & pipeline sync
- Custom API connections
- Data cleanup & deduplication
- Knowledge base structuring
- Dashboards & reporting
- HubSpot · GoHighLevel · more
Good to know
Not always. If you already know exactly what you want built and why, we can go straight to a build engagement. But if the goal is still vague, the audit pays for itself by killing the ideas that would have wasted a much larger budget.
An audit takes two to three weeks. After that, first builds typically go live within another two to four weeks, because I sequence the work so the highest-value, lowest-risk win ships first rather than saving everything for a big-bang launch.
No. I build around the systems you already use: CRM, email, calendar, accounting, and the rest. Ripping out working software to accommodate AI is almost always the wrong trade, and I'll say so if a vendor suggests it.
Whichever fits the problem and your constraints. I'm not a reseller for any vendor and I take no referral fees, so the choice comes down to accuracy, cost, latency, and where your data is allowed to go. Often the right answer for a given step is no model at all, just deterministic code.
No. Teams of roughly five to two hundred are the sweet spot. They have clear, repetitive bottlenecks, real money at stake, and no appetite for an eighteen-month enterprise programme.
Audits are a fixed fee agreed before work starts. Build work is scoped from the roadmap into fixed-price phases, each with defined deliverables and an expected return, so you can stop after any phase rather than being locked into the whole programme.
AI systems drift in ways ordinary software doesn't, so I monitor accuracy and cost after launch, tune prompts and guardrails as your business changes, and report on what the system actually returned rather than what it was projected to return.
It's part of every engagement, not an add-on. That means deciding what data can reach a third-party model, keeping sensitive workloads on infrastructure you control where necessary, logging what the system did and why, and putting human review in front of any decision that carries real consequences.
Not sure where
to start?
That's exactly what the audit is for. Book a free call and I'll tell you honestly whether you need one, and what I'd look at first.