AI Solutions
Generative and agentic AI are moving quickly from CAD copilots into task-specific agents that read your parameters, apply your standards, and act inside your CAD, PDM and PLM systems. We build that layer for you: agents scoped to a real workflow, connected to your data, and supervised by your own engineers.
Where the industry is heading
Analysts covering manufacturing technology describe 2026 as the year engineering organizations move from AI tools that respond when prompted, to AI agents that carry out multi-step work inside existing CAD, PDM and PLM systems — with a human still setting the goals and reviewing the result.
Two ways we apply AI
AI shows up in our work in two distinct ways — and we keep the two clearly separated.
We use AI-assisted development tools ourselves to move faster on the module, macro or integration you've asked for — from scaffolding automation code to reviewing it against your CAD API's conventions. This shortens delivery time on a workflow review or module build without changing what you receive: code your team can read, own and maintain.
Where it fits, we design and deploy AI agents that run as part of your engineering process itself — reading your Excel-driven configuration rules, flagging exceptions a Standardizer-style check would miss, drafting the routine parts of a change order, or summarizing an engineering release for a non-technical stakeholder. This is the offering described below.
Agent types we build
Every agent we deploy is scoped to one part of your workflow, connected to the systems it needs, and reviewed by your engineers before its output is used. None of these run unsupervised in production without your team's sign-off on the initial rollout.
Reads incoming order or spec data, proposes the configuration values an Auto-Configure-style workflow needs, and flags anything outside your defined limits before generation runs.
Drafts routine drawing notes, revision summaries and change-order descriptions from the model and its history, for an engineer to review and release.
Works across your PDM or PLM data to fill gaps, flag inconsistent metadata, and surface duplicate or reusable parts before a new one is created.
Assembles status across CAD, PLM and Microsoft systems — release progress, open approvals, exceptions — into a summary your team doesn't have to compile by hand.
A concrete example
CADPilot, our voice assistant for SOLIDWORKS, is a working example of this philosophy. Today it maps spoken design intent directly to SolidWorks commands — deterministic, with no AI involved in execution. We are now developing an on-premise learning layer inside it that observes how a user or organization actually works over time, and surfaces relevant suggestions — without any design data or usage pattern leaving your own infrastructure.
How we work
We identify one workflow where an agent would remove real, repetitive effort — not a general-purpose assistant, a specific task with a clear input and output.
The agent is connected only to the data and systems that task requires — your CAD files, PDM/PLM records, or Microsoft platforms — through the access your team approves.
Early runs are reviewed by your engineers before output is used. We build in logging and clear escalation, so it's always visible what the agent did and why.
Once the agent is trusted on that one task, we extend it — or scope the next one — rather than widening its authority all at once.
Frequently asked
Not by default. Every agent we deploy starts with human review of its output, and we agree with you where, if anywhere, that oversight can later be reduced for a specific, well-tested task.
Only what its specific task requires. We scope access deliberately — a drawing-documentation agent doesn't need write access to your PLM release workflow, for instance — and agree the access model with your IT and engineering leadership before anything connects to production data.
No. These agents take on repetitive preparation and drafting work so your engineers spend their time on judgment calls, not on the mechanical steps around them.
Yes. Agents are a natural extension of the same configuration and standardization logic those products already apply — the agent layer adds judgment on top of rules that are already in place.
Related, not identical. CADPilot is a packaged product — a voice assistant for SOLIDWORKS, with an on-premise learning layer now in development. The AI agents described on this page are typically custom-built around a specific client workflow, often spanning more than just CAD.
Agents run within access boundaries your team defines, and we document exactly what each agent can read, write and call before it goes near production data.
We'll tell you honestly whether an agent is the right fit, or whether a simpler automation module gets you the same result.
Auto‑Configure