APEX AI · AI systems for B2B and sales teams

Where to start

Two problems, two front doors.

Most people arrive with one of these. Both start with a paid diagnosis, and the fee comes off the build if you go ahead.

Door one

Your CRM and your data aren't pulling their weight

The records are in there somewhere, the reporting nobody trusts, the enrichment that happens when someone remembers. The system exists, it just is not doing any work.

Attio builds, and migrations off HubSpot with history intact
Enrichment and data pipelines that feed the CRM on their own
Reporting your leadership can take to a board meeting

CRM & Data Audit, from £1,000

See how it works

Door two

You know AI should be helping, but not where

Everyone has the raw power now. The hard part is knowing which parts of your business it should be pointed at, and what each one is actually worth.

Two to four weeks inside how your business really runs
Opportunities ranked by hours and money saved, using your numbers
A roadmap you can run yourself, or have me build

AI Audit, from £1,500

See what's involved

How I work

Diagnose, build, then keep it running.

The same three steps whichever door you came through.

1. The audit

A paid diagnosis of what is actually broken, with the build options costed. You get a written roadmap you can act on with me or without me, and the fee comes off any build we start within ninety days.

2. The build

Fixed scope, fixed fee, agreed up front, with the limits written down so a fixed price stays a fixed price. You check in at milestones rather than waiting in the dark.

3. Keep it running

A system nobody owns degrades quietly. A monthly retainer keeps the data clean, the workflows running and the costs honest. It earns its place every month or you stop it.

Proof

Systems in daily use, not slides.

Client names stay off the website on purpose. The work is real and I will walk you through any of it live on a call.

65%

RecruitmentAI agents

A major UK recruitment group

Reduction in manual candidate research time after building an AI sourcing and screening engine that runs the first stage of every placement.

60+ employer communications handled daily by the AI agent
Candidate shortlisting automated, humans only at escalation point
Live and in daily use across the business

300+

B2B SaaSOutbound

An enterprise B2B software platform

Personalised landing pages deployed for target accounts, each built from live signal data, alongside a signal-fed outbound engine for the BDR team.

Account-specific pages generated from funding, hiring and tech-stack signals
BDR team freed from manual account research per prospect
Outreach personalised at scale without additional headcount

247

Professional servicesOutbound

A B2B events and sponsorship business

Target accounts identified, enriched and enrolled into personalised email and LinkedIn sequences in the first automated run. List building went from a manual half-day to fully automated.

Signal-based scoring across funding, hiring and industry fit
Decision-maker contacts enriched and verified per account
Scored prospects delivered weekly for the length of the engagement

Why me

An AI and data engineer who started in sales.

Most people who do this came out of sales, or out of engineering. I did both, in that order. Four years on the phones first: a bank, a recruitment desk, then selling in Gran Canaria and for an events business. At 25 I went back to university and took a first-class Computer Science degree. The decade after that was production data systems at GE, BT, Innovate UK and confused.com, then a solutions engineer seat at Cubed, sitting between the engineers and the sales manager on enterprise deals.

The AI half is not a recent pivot. There are systems of mine in daily use right now: an agent handling the front of a recruitment desk, a public scoring tool that runs four APIs and two models per request, and the assistant answering questions in the corner of this page. All built with real tool access, running against live data, with a defined answer for what happens when a model returns the wrong thing.

That combination is the point. Anyone can call a model. Knowing where the cost lands, what to do when it fails, and how it joins a CRM schema without breaking it, that comes from the engineering. Knowing what a rep will actually open on a Monday morning comes from having been one.

Founder-led. I scope and build the work myself, and bring in specialist help when a project needs it. If a scope outgrows that, I tell you rather than bury it.

The longer version →

Worked with

BTGeneral ElectricInnovate UKconfused.comCardiff Metropolitan University

Official Attio Expert Partner★ Upwork Expert-Vetted · top 1%

Clay Bootcamp graduate

★★★★★5.0 rating · 100% Job Success Score · Expert-Vetted Top 1%

Questions

Straight answers.

Both, and increasingly the two are the same job. For sales teams that means agents which research an account, screen inbound replies and turn a call into a written record. For other teams it is whatever the audit finds, usually the places where someone reads something and types the important parts somewhere else. All of it sits on the CRM and the data layer rather than off to one side as another tool nobody opens.

Often, yes. That is the honest state of the market. The difference is in the parts nobody demos: what the system does when the model returns the wrong shape, where the cost lands at volume, how it gets access to your real data safely, and how you know it is still working in three months. Ask me on the call what happens when a run fails. It is the fastest way to sort the engineers from the wrappers.

No. If you are on HubSpot or Salesforce and want to stay there, I will build on what you have got. The data layer, the enrichment and the automation all work regardless of which CRM you are in. I am a vetted Attio Expert Partner, so for teams starting fresh or already planning a switch it is usually where I would point you, but it is not a condition of working together.

Teams with no CRM and no intention of building proper infrastructure, anyone wanting AI because it is AI, and anyone after a quick one-off fix with no data foundation behind it. If any of those fit, I will say so on the call rather than take the work.

AI systems for B2B and sales teams.