AI Development

Practical AI that actually works. I build custom AI products, workflow automation and agentic systems for businesses that want to use AI properly. Not just bolt on a chatbot. From intelligent search and content pipelines to multi-step reasoning agents, built with real guardrails and production reliability.

Capabilities

What I Build

AI-Powered Products

Custom applications with AI at the core. Intelligent search, content generation, classification, summarisation and recommendation systems built to solve real problems.

Workflow Automation

Automate repetitive business processes using AI. Document processing, data extraction, email triage and lead scoring. Freeing up your team to focus on higher-value work.

Agentic Systems

Multi-step AI agents that reason, plan and execute tasks autonomously. From research assistants to complex decision-support tools. Built with proper guardrails.

API Integrations & RAG

Connect OpenAI, Anthropic or open-source models to your existing systems. Retrieval-augmented generation (RAG) pipelines that ground AI responses in your actual data.

Use Cases

AI that solves actual business problems.

Not every business needs AI, but when you do it should be built properly. These are the kinds of problems I help solve:

Internal knowledge bases with AI-powered search
Automated document processing and data extraction
Customer support chatbots grounded in your business data
Content generation pipelines with human-in-the-loop review
Intelligent lead scoring and CRM enrichment
AI-assisted code review and development tooling
Personalised recommendation engines
Multi-agent systems for complex research and analysis
Approach

Built for reliability, not just demos.

Anyone can wire up a ChatGPT API call. The hard part is making AI systems that are reliable, accurate, cost-effective and genuinely useful in production. That's where my focus sits.

I build with proper output validation, structured error handling, token optimisation and fallback logic. AI systems that gracefully handle edge cases rather than hallucinating through them.

Where it makes sense, I implement human-in-the-loop review. Keeping a person in the decision chain for high-stakes outputs. The goal is always AI that augments your team, not AI that creates more work to clean up after.

Models

Providers I Work With

Model-agnostic development. I pick the right model for the task, balancing capability, latency and cost.

OpenAI

GPT-5.4, Sora 2, gpt-realtime

Anthropic

Opus 4.6, Sonnet 4.6

Google

Gemini Pro, Nano Banana

Hugging Face

Open-source models

Ollama

Local inference

Replicate

Custom models

LMStudio

Local models

Groq

Fast cloud inference for mid tier models

FAQ

Common Questions

What kind of AI development do you offer?

I build custom AI-powered applications, workflow automation, agentic systems and integrations using large language models (LLMs) from OpenAI, Anthropic and open-source providers. The focus is always on practical, reliable systems that solve real business problems.

How much does AI development cost?

It varies significantly based on complexity. I always scope clearly before any work begins.

Do I need a massive dataset to use AI?

Not necessarily. Modern LLMs are powerful out of the box. With RAG (retrieval-augmented generation), I can connect AI to your existing documents, databases or knowledge bases without needing to train a custom model. Your existing data is often more than enough.

Is AI reliable enough for production use?

With the right architecture, yes. I build AI systems with proper error handling, output validation, fallback logic and human-in-the-loop review where it matters. The goal is useful and dependable. Not a demo that falls apart under real conditions.

Can you integrate AI into my existing application?

Absolutely. Whether it is adding intelligent search to an existing platform, automating a manual workflow or building an AI layer on top of your current systems. I work with what you have.

What models and providers do you work with?

I typically work with SOTA models such as GPT-5.4, Opus 4.6, Gemini and media models such as Nano Banana, the Flux series of models, Kling, Sora 2 to list a few. I pick the model that best fits the use case, balancing capability, cost and latency.

Want to use AI properly?

Tell me what problem you're trying to solve. I'll tell you honestly whether AI is the right approach. And if it is, how to build it well.

Get in touch

Free quote · No obligation · Usually reply within a day