AI Product Strategy
& Delivery

Most enterprise AI programmes fail between proof-of-concept and production. The technology works in the sandbox; it stalls when it meets a procurement committee, a compliance review, or an infrastructure team that was not involved in the design. AmehX works specifically at that gap.

We have shipped RAG pipelines that cut analyst reporting time by 60%, fine-tuned LLMs on Vertex AI and OpenAI endpoints for regulated B2B SaaS platforms, and built MLOps infrastructure that a client's internal team can actually maintain after we leave.

In regulated environments — FCA-supervised firms, Gambling Commission licensees, GDS-assessed government services — AI deployment requires a governance architecture that most organisations have not built yet. We design that architecture before we write the first line of production code.

• —LLM evaluation, selection, and production architecture for regulated contexts
• —RAG pipeline design with vector database integration (Pinecone, Weaviate)
• —Prompt engineering and model fine-tuning on Vertex AI and OpenAI
• —MLOps infrastructure, monitoring, and observability
• —AI product roadmap and board-level reporting layers
• —AI governance frameworks compliant with FCA, GDS, and Gambling Commission requirements

Google Gemini · Vertex AI · OpenAI · Microsoft Azure AI · Pinecone · Weaviate · Jupyter · Python · LangChain · LlamaIndex