AI for Engineering

AI is useful in engineering when it is connected to real engineering data and constrained by real engineering rules. Neilsoft builds AI applications in three related areas.​

Generative AI in design covers two things that are often confused. Generative design — the optimisation-driven approach in tools like Autodesk Fusion — produces geometry from goals and constraints such as loads, materials, and manufacturing method. Generative AI, based on large language and diffusion models, produces design options, specifications, documentation, and layouts from prompts and existing data. Both have a place, and both need domain grounding to be trusted.​

Agentic AI and custom AI agents go beyond single answers. An agent plans a task, uses tools and data sources, and carries a multi-step workflow to completion — checking a model against standards, extracting and compiling data, drafting a submittal, or triaging RFIs. The engineering is in giving the agent reliable access to the right systems and clear limits on what it can do.​

MCP (Model Context Protocol) is the open standard, introduced by Anthropic, for connecting AI models and agents to external tools and data in a consistent way. An MCP server exposes a system — a PLM database, a Vault, a BIM model, a document store — to an AI agent through a standard interface. It is what lets an agent query your actual engineering data instead of guessing.​

Neilsoft's capabilities

Applications in engineering

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