LLM application development
Retrieval, tool use, and structured output built on top of your data, with prompt and context design that's actually maintainable.
Mpaukwu Trading builds LLM-powered apps, AI agent and MCP integrations, and workflow automation with human review and data-control guardrails, so the AI layer holds up once real users and real data hit it.
Talk about your projectAn engineer who has shipped AI systems into production, including an MCP gateway that lets AI agents discover and transact with real businesses, not a demo that breaks the first time it meets messy input.
Retrieval, tool use, and structured output built on top of your data, with prompt and context design that's actually maintainable.
Model Context Protocol tools and gateways that let agents like Claude, Gemini, and GPT find, verify, and act on your data safely.
AI assistants for research, content operations, and support, with human review checkpoints where the cost of a wrong answer is high.
Scoped access, audit logs, and policy checks so an AI feature can't quietly do more than it was supposed to.
A defensive audit of your AI surface: prompt injection exposure, data leakage paths, and abuse cases, before an attacker finds them first.
Fixed-scope AI features, monthly retainers, or embedded work alongside your team, depending on what the problem actually needs.
Don't take a pitch deck's word for it.