Got Questions?

Will this actually work for our firm?

Most engineering firms believe their workflows are completely unique, but almost every firm has repeatable drafting processes, standards, and production tasks. The goal isn't to automate engineering judgment. It's to automate the repetitive work surrounding it so your team can deliver more with the resources they already have.

Our projects are too complex for automation. Can this still help?

Yes. Complexity is usually where the biggest inefficiencies exist. The system doesn't remove complexity from your projects. It standardises how complexity is handled so your team can produce consistent results every time.

How do I know if we're a good fit?

The best fit is typically an engineering consultancy that relies heavily on AutoCAD, has established workflows, and feels constrained by drafting capacity, inconsistency, or production bottlenecks. The purpose of the CAD Clarity Call is to determine whether automation can realistically create value in your environment before any implementation is considered.

What happens during the CAD Clarity Call?

The call is a structured workflow diagnosis. We'll review your drafting environment, identify where capacity is being lost, assess potential automation opportunities, and determine whether a deterministic Agentic AI system makes sense for your firm.

What do I receive after the CAD Clarity Call?

You'll receive a custom written roadmap outlining the biggest bottlenecks in your current workflow, the highest-value opportunities for improvement, and a prioritised implementation sequence tailored specifically to your firm.

How quickly will I receive my roadmap?

Your custom roadmap is typically delivered within 72 hours of the CAD Clarity Call, followed by a review session where we walk through the recommendations together.

How is this different from standard CAD automation?

Most CAD automation focuses on isolated scripts, templates, or productivity tools. This approach focuses on designing an integrated drafting system that combines standards, workflows, automation, and Agentic AI into a single production environment.

Is this the same as generative AI?

No. Most generative AI systems are probabilistic, meaning outputs can vary from one request to the next. The systems I build are designed to be deterministic wherever possible, producing predictable and repeatable results that are suitable for engineering environments.

What is Agentic AI?

Agentic AI is an AI system that can perform structured tasks, make workflow decisions, and coordinate multiple steps within a process. In this context, it acts as a rule-following drafting assistant that works within defined standards and workflows rather than producing unpredictable outputs.

Will the AI make engineering decisions?

No. Engineering judgment always remains with your team. The system removes repetitive drafting and workflow tasks while allowing engineers to maintain control over design decisions and technical responsibility.

Will this work with our existing AutoCAD environment?

In most cases, yes. The system is designed around your existing standards, workflows, and drafting processes rather than requiring a complete replacement of your current environment.

What if we also use Revit or other software?

Many firms operate mixed environments. During the discovery process, we'll assess how your existing software ecosystem fits into the broader workflow and identify where automation can create the most value.

How disruptive is implementation?

Implementation is designed to minimise disruption. Systems are built and tested outside of live projects first, then introduced in a controlled manner once they have been validated.

What if my team doesn't adopt it?

Adoption is built into the implementation process through training, documentation, real project testing, and live handover. The goal is to make the system feel like a natural extension of how your team already works.

How long does implementation usually take?

The timeline depends on the complexity of the workflow being automated. During the discovery phase, we'll define a clear scope and implementation plan so expectations are clear from the start. (Ballpark 8-16 weeks)

Do we lose control of the system after implementation?

No. Ownership remains with your firm. You'll receive documentation, training, and system knowledge so your team can operate and maintain the solution independently.

What happens when our standards change?

The system is designed around your standards and can evolve alongside them. Standards, workflows, and automation rules can be updated as your business grows and changes.

How do you prove the system actually works?

Every implementation is tested against real project conditions before rollout. You see the system working inside your environment before it becomes part of your production workflow.

Can you show examples of previous results?

Yes. I regularly share real demonstrations, workflows, and automation examples on my YouTube channel so you can see exactly how I approach engineering drafting automation and Agentic AI systems in practice. (youtube.com/@vistruxai)

What I can't do is share client workflows, drawings, or internal processes. Most of the firms I work with operate in industries such as civil, structural, mechanical, electrical, HVAC, process equipment, and pharmaceutical, (to name a few) and their workflows often contain valuable intellectual property. I work under NDA with my clients and take that responsibility seriously. If you were a client, you probably wouldn't want me sharing your engineering IP with someone else either.

That's also why every engagement begins with a proof of concept. Before committing to a full implementation, you'll see the system working against a real workflow. If the proof of concept doesn't demonstrate the value you're looking for, we simply don't move forward. No pressure, no surprises.

Why not build this internally?

You absolutely can. The question is whether your senior engineers and CAD leaders should spend months learning, testing, and refining automation systems while also delivering projects. Most firms find it more cost-effective to leverage existing experience and proven implementation frameworks.

What kind of results can we expect?

Results vary depending on the workflow being automated. In targeted drafting workflows, implementations have achieved significant reductions in manual effort, while also improving consistency, reducing review time, and increasing overall production capacity. My average for now is between 80-90% of specific drafting workflows.

What if we decide not to move forward after the roadmap?

That's completely fine. The roadmap is designed to provide clarity regardless of whether you choose to implement the recommendations with me, internally, or not at all.

What is the biggest benefit of this approach?

The biggest benefit is increased drafting capacity without increasing headcount. By standardising workflows, reducing repetitive work, and improving consistency, engineering firms can often deliver more projects with the team they already have.