I'm one of the most experienced AI-driven technologists working in UK logistics, with over 20 years in logistics and haulage software behind me. Private AI on my own hardware, askadash, AI route planning and AI in the screens your teams already use, with your data kept off public AI services.
AI is genuinely useful in logistics: drafting, summarising, checking, spotting what doesn't look right.
But most AI tools send your data to someone else's servers. Customer lists, rates, manifests and emails aren't things to hand over and hope. So I run AI privately.
I work at the leading edge of applied AI, and it runs in production in the logistics software I build.
My own private AI server runs local language models so data stays in-house. askadash uses AI to build dashboards, and requests become working builds.
On the same hardware I make long-form AI film from start to finish: 20-minute lip-synced AI episodes, AI music and AI video. If AI can do it, I've probably already pushed it further than most.
Local language models on my own private hardware. Client data is worked on in-house and kept off public AI services.
My own AI dashboard builder: ask for a dashboard in your own words and it is built, usually in minutes.
AI screens beside your live KPIs.
Drafts, summaries and replies, written privately.
Repetitive office jobs handed to software.
Image jobs done in-house, on the same private hardware.
Long-form AI video, lip sync and music, made on the same private hardware.
Route optimisation with AI, built around your depots, your postcodes and your cut-offs.
Drops, time windows, vehicles and drivers, balanced by software instead of by memory and a whiteboard. I build it to connect to the TMS you already run, so the plan and the jobs are the same thing.
I already allocate pallet-network depots automatically from the postcode. Route planning takes that further.
AI is most useful on the screen your team already has open.
On askadash, the multi-tenant dashboard platform I built, AI screens sit alongside the live KPIs. Each screen has its own AI settings, and each company can override them, so one company's choices never change another's.
And askadash itself is AI at work: say what you want to see and it builds the dashboard for you.
On a warehouse KPI dashboard I run, requests are made on the dashboard itself, files attached, and become builds.
It's AI-assisted delivery: the request, the files and the build in one place, with me deciding what goes live.
One real, repetitive task. Not a strategy deck.
Private models on private hardware. Nothing posted to a public service.
In the dashboard, the inbox or the import, not in another app to log in to.
See what it gets right and wrong, then give it the next job.
Tell me which task eats your team's time. I'll tell you whether AI can take it on, privately.
Answers are written by AI and may be wrong - for anything important, use the contact page.