AI Consulting

AI, LLM and Machine-Learning Consulting

I help teams evaluate, design and build AI capabilities that connect to real products and workflows. This includes determining whether AI is appropriate, selecting an architecture, preparing data and integrating the resulting system with dependable software.

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AI Consulting Areas

LLM-powered application design
Retrieval-augmented generation and vector search
AI agents and workflow automation
Document and expert search
Machine-learning application integration
Computer vision where supported by real experience
Evaluation, observability, privacy and cost controls
Prototype-to-production planning

When AI Is Not the Right Answer

Some problems are solved more reliably with deterministic software, better search, rules, workflow changes or clearer data design. A useful AI engagement should identify those cases early instead of forcing a model into every product decision.

Selected Software and AI Case Studies

Selected examples of product engineering, architecture, AI integration and client delivery across real-world software platforms.

Interface-style diagram representing a real-estate analysis dashboard

Analytics platform · Real estate

Real-Estate Analysis Application

A web application for analysing real-estate data through a structured product interface, with emphasis on maintainable dashboards, data modelling and decision-focused workflows.

Role: Full-stack engineering, architecture support, delivery planning and implementation.
Core technologies: React, Node.js, Python, MongoDB
Outcome: Delivered a maintainable analysis platform as part of client product engineering work.

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Search and LLM application · Knowledge workflow

AI-Powered Expert Search and Retrieval Platform

A search-oriented platform for finding relevant experts and information across structured and unstructured inputs using practical retrieval and AI-assisted product patterns.

Role: Applied AI/ML engineering, vector-search workflow design, product implementation and technical delivery support.
Core technologies: LLMs, Vector search, React, Node.js
Outcome: Delivered expert-search and retrieval workflows as part of real product engineering work.

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Diagram showing form inputs transformed into structured AI-assisted workflow output

Generative AI workflow · Business process automation

GPT-Based Form Workflow Application

A GPT-enabled application that applied large language models to structured form and workflow interactions while keeping normal product validation and review points in place.

Role: LLM integration, full-stack implementation, workflow design support and delivery coordination.
Core technologies: GPT workflows, React, Node.js, FastAPI
Outcome: Delivered an AI-assisted workflow that connected model output with structured application behaviour.

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Frequently Asked Questions

Can you help decide whether an AI feature is worth building?

Yes. The first step can be a practical assessment of the workflow, data, expected value, risks, cost and alternatives.

Do you build only prototypes or production systems too?

Engagements can cover prototypes, architecture, implementation and planning for production concerns such as evaluation, privacy, cost and observability.

Do you work with RAG and vector search?

Yes. Existing work includes LLM applications, retrieval workflows, vector-search systems and expert-search product patterns.

Have a Product, Training Session or Technical Talk in Mind?

Share the problem, audience and expected outcome. I will reply with the most relevant next step.

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