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TrenckTech

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Four ways I make businesses faster.

Most engagements start in one of these and end up touching two. The category matters less than the outcome. Bring me the problem, and we'll work out which of these it actually is.

01 · Web Applications 02 · Automation 03 · AI & Machine Learning 04 · Computer Vision & Data
01

Web Applications

Custom sites and web software built to be fast, durable, and genuinely yours. Not a template someone else can buy tomorrow.

Marketing sites that load in under a second, client portals, internal dashboards, booking and payment flows, SaaS MVPs. Built on modern foundations, with the boring parts done properly: accessibility, SEO, analytics, and a deploy pipeline you never have to think about.

  • Marketing sites & landing pages
  • Client portals and dashboards
  • SaaS MVPs and internal tools
  • Rebuilds of slow or fragile legacy sites
02

Automation

The work your team does by hand every week, done by software instead. Usually the fastest money a business ever saves.

I map the process first, find where the hours actually go, then automate the parts that are worth automating. Integrations between the tools you already pay for, scheduled jobs, document and data pipelines, and alerting that only reaches a human when it should.

  • Tool-to-tool integrations
  • Reporting and document pipelines
  • Scheduled jobs and alerting
  • Manual-process elimination audits
03

AI & Machine Learning

Applied AI that solves a named problem, not a chatbot bolted on so the homepage can say it has one.

Retrieval systems over your own documents, agents that take real actions inside your stack, model integration and evaluation, and honest advice about where AI is the wrong tool. I have shipped ML systems in production, and I will tell you when a database query would beat a model.

  • RAG and document intelligence
  • LLM agents and tool integrations
  • Model evaluation and guardrails
  • AI feasibility assessments
04

Computer Vision & Data

Teaching software to see, measure, and make sense of the physical and unstructured world.

Detection, tracking, and classification pipelines, video and image analysis at scale, training data strategy and labeling workflows, and the data engineering underneath all of it. This is where my research background lives, and it is the work I take most personally.

  • Detection & tracking pipelines
  • Video and image analysis
  • Model training and fine-tuning
  • Data pipelines and analytics

Not sure which one you need?

That's what the call is for.

Bring the problem, not the spec. Working out which of these it actually is, or whether it's none of them, is the first thirty minutes, and it costs nothing.

or email dylan@trencktech.com