Services

Problems I Solve.
Solutions I Build.

Six focused services built around the engineering problems that actually cost businesses time and money. Fixed scope, honest pricing, no retainers unless you want one.

Full‑Stack Performance Optimisation

The problem: Your app is slow, users are bouncing, and your team has been too busy shipping features to dig into why. PageSpeed is red. The database queries are a mess. Nobody knows what the bundle size is doing.

My approach: I run a structured audit across every layer — frontend bundle analysis, network waterfall review, database query profiling, server response times, and caching strategy. I don't guess; I instrument and measure first, then I fix the highest‑impact issues in priority order and measure again.

  • Written audit report with every bottleneck ranked by impact — yours to keep regardless of next steps
  • Implemented fixes: query optimisation, caching layer, bundle splitting, image pipeline — wherever the gains are
  • Before/after benchmarks and a monitoring setup so the gains don't silently erode

AI Feature Integration

The problem: You know your product needs AI features — smarter search, a chatbot, content generation, document analysis — but every vendor wants to replace your stack and every freelancer wants to bolt on a GPT wrapper that breaks in three months.

My approach: I start by understanding your data, your users, and your existing architecture. Then I design the integration to fit your stack, not replace it. I use LangChain, LangGraph, OpenAI, Anthropic, or open‑source models depending on what your use case actually needs — not what's trending on Hacker News this week.

  • A scoped technical design document before any code is written — so you know exactly what you're getting
  • Production‑ready AI feature with error handling, fallback logic, observability, and cost controls baked in
  • Handover documentation and a 30‑day support window so your team can own it confidently

MVP to Production Upgrade

The problem: Your MVP got you to product‑market fit, which is great — but now it's choking under real load, your dev velocity has collapsed because the codebase is a mess, and you're scared to deploy on Fridays.

My approach: I do an architecture review first — understanding what's there, what's brittle, and what can be salvaged versus rewritten. Then I work in phases: stabilise the critical paths, add proper test coverage, introduce CI/CD, and systematically refactor the worst debt. No big‑bang rewrites that take six months and miss the point.

  • Architecture review with a written assessment of risks, tech debt priority, and recommended migration path
  • Refactored codebase with CI/CD pipeline, environment parity, and automated test coverage on critical flows
  • Staging environment, deployment runbook, and rollback procedure — so your team can deploy with confidence

Automation Pipeline Build

The problem: Your team is burning hours on tasks that should be automatic — data entry, report generation, content processing, client communications, file handling. You've looked at Zapier but it doesn't quite do what you need, and hiring a developer for six months feels like overkill.

My approach: I map your current manual workflow end‑to‑end before writing a line of code. Then I design the simplest reliable pipeline that eliminates the manual steps — using n8n, custom Python scripts, or LLM agents depending on what the task requires. I build for reliability over cleverness: clear logs, failure alerts, and manual override paths.

  • Workflow map documenting every step, decision point, and edge case — valuable even if you don't proceed
  • Deployed automation with error handling, logging, failure alerts, and a simple admin UI or dashboard where needed
  • Time‑saved report after 30 days, showing actual hours recovered versus the pre‑automation baseline

Code Rescue & Stabilisation

The problem: Your previous agency or developer delivered something that half works, is completely undocumented, and has left you with production bugs you're afraid to touch. You need someone to step in, understand the mess, and make it stable — without burning it down and starting over.

My approach: I've inherited enough bad codebases to know that the first job is understanding, not judging. I read the code systematically, map how the pieces connect, identify what's actually broken versus what just looks bad, and document as I go. Then I fix the critical bugs, shore up the fragile parts, and give you a codebase you can safely hand to another developer.

  • Full codebase audit — architecture diagram, identified bugs, security issues, and a prioritised fix list
  • Critical bug fixes and stabilisation of the highest‑risk paths, with regression tests to prove they stay fixed
  • Developer handover documentation — what the system does, how it's structured, and what to watch out for

AI Product Consulting & POC

The problem: You have an idea for an AI‑powered product — or you know your existing product needs AI — but you're not sure which technology to use, what's actually feasible, what it would cost to build, or whether the idea makes sense before you commit $50k to it.

My approach: I run a focused consulting engagement: understand your use case, map the technical options, identify the risks, and build a minimal proof‑of‑concept that answers the key feasibility question. You'll know within a week whether the idea is viable, what the production path looks like, and what it will actually cost — without committing to a full build.

  • Tech selection memo: which models, frameworks, and architecture make sense for your specific use case and why
  • Working POC demonstrating the core AI interaction — enough to show stakeholders, test assumptions, and derisk the build
  • Production roadmap with phased milestones, realistic timeline, and cost estimates for the full build

Not sure which service you need?

Describe your problem and I’ll tell you honestly whether I can help, which service fits, and what to expect. No obligation, no sales pitch.

Let’s Talk