AI that handles the paper trail so your team can build
MEP and AEC firms don't have a technology problem. They have a documentation problem. RFIs, submittals, daily reports, version control. AI handles the groundwork on all of it. Your engineers and field crews handle the judgment calls. That's the division that actually works.
Where project teams lose time
The billing rate on RFI coordination and submittal review is real. So is the schedule impact when responses are slow and documents get lost between systems.
RFI volume outpaces your team
On a large commercial or industrial project, RFI counts regularly reach several hundred. Drafting responses requires pulling specs, cross-referencing drawings, and coordinating with design teams. Most of that groundwork can be done by AI in minutes, not hours.
Submittal review creates schedule risk
Manual submittal review is time-consuming and prone to inconsistency, especially across large package batches or when the reviewer changes mid-project. Delays in the review queue compress downstream schedules directly.
Document control breaks down at scale
When teams work across Procore, email, shared drives, and field apps simultaneously, version control becomes a daily problem. Outdated drawings in the field and missed spec revisions are among the most common and costly sources of rework in construction.
Four workflows that deliver measurable ROI
These are the use cases where AI consistently delivers measurable time savings for MEP and AEC teams. Each one is scoped and implemented based on your specific tools and project environment.
RFI response drafting
AI reads the RFI, pulls the relevant spec sections and drawing callouts, and drafts a response for engineer review. Your team reviews and approves. They stop spending hours building the response from scratch on every ticket.
Submittal review screening
AI screens incoming submittals against spec requirements and flags exceptions before they reach the responsible engineer. Routine submittals move faster. Complex exceptions get proper attention instead of getting buried in a growing backlog.
Document control & version management
AI monitors document repositories for version conflicts, flags superseded drawings still in active use, and routes updated documents to the right people automatically. Version errors in the field become an exception rather than a daily risk.
Safety reporting & daily documentation
AI drafts daily field reports, safety inspection logs, and incident documentation from brief voice or text inputs. A foreman who would otherwise write end-of-day reports from scratch can review and sign off an AI draft in a fraction of the time.
Two document products, open to pilot partners
We're building two products on the same document review engine and taking a small number of pilot partners on live projects. Each pilot is scoped to one real project, and your people review every result before it goes anywhere.
TurnoverIQ: GMP turnover package QA
For MEP and process subcontractors, GCs, CMs, and CQV firms on GMP projects. TurnoverIQ checks incoming vendor documents against the owner's turnover package index and the spec, including weld logs, material certs, calibration records, and passivation reports. It cites the page behind every finding, tracks completeness as the job runs, and drafts gap requests to vendors.
BidReady: RFP and RFQ response builder
For A/E principals and GC business development leads. BidReady pulls the requirements and scoring criteria out of an RFP, builds a compliance matrix, gives a go/no-go read, and drafts sections from your own project sheets and resumes, citing the source for each. Where your library doesn't cover a requirement, it flags the gap instead of inventing content.
Engineering rigor applied to AI
Greg Stone built his career in CQV engineering (Commissioning, Qualification, and Validation) inside FDA-regulated pharmaceutical and life sciences manufacturing. It's some of the most documentation-intensive work in industry.
That background translates directly to MEP and AEC. Construction document control, spec compliance, and field reporting have the same core requirements as IQ/OQ/PQ validation: clear scope, documented procedures, and a defensible audit trail. The contexts are different. The discipline is the same.
Every AI workflow QP builds for a construction or engineering firm comes with a full Standard Operating Procedure, documented validation testing, and a handoff package your team can actually use. Not just a demo that works once and breaks six months later.
How a QP engagement works
Discovery & Scoping
We review your project workflows, document environment, and team structure to identify the highest-ROI starting point.
Build & Validate
We build the workflow against a real sample of your project data and validate performance before anything goes to production.
Deploy & Train
Full handoff with SOPs, team training, and 30-day post-launch support. Your team owns it when we leave.
Measure & Optimize
Success criteria are defined before we start. Every engagement tracks against them. If the numbers aren't there, we fix it.
What project documentation is actually costing you
These figures come from AEC industry research. They're baselines for what firms are spending before any automation is in place, not projections of what AI will save.
of construction professionals' time spent on non-optimal activities: looking for project data, resolving conflicts, and dealing with mistakes and rework
FMI / PlanGrid, Construction Disconnected, 2018
in U.S. construction labor costs spent on those non-optimal activities in 2018, rather than on productive project work
FMI / PlanGrid, Construction Disconnected, 2018
of U.S. construction rework, about $31.3B of $65B a year, traced to poor project data and miscommunication
FMI / PlanGrid, Construction Disconnected, 2018
The ROI on AI-assisted documentation comes from recovering a fraction of this time. A project team saving 5 hours per week on RFI and submittal coordination, at a fully loaded rate of $125/hr, covers a typical single-workflow engagement cost within one project cycle.
Is this right for your firm?
QP works with small and mid-size MEP and AEC firms: large enough to have real documentation overhead, lean enough that adding headcount isn't the answer.
- MEP contractors: mechanical, electrical, plumbing, fire protection
- General contractors managing complex subcontractor documentation
- Architecture and engineering firms with high RFI and submittal volume
- Teams already on Procore, Autodesk, or Bluebeam who want AI layered in
- Firms with 20–200 employees where project admin is a recognized bottleneck
- Firms under 10 employees where documentation volume doesn't justify the investment
- Organizations looking for a pre-built SaaS product rather than a custom implementation
- Teams not yet using a project management platform. There's foundational work to do first
- Firms expecting a quick demo. QP builds production systems, which requires real scoping time
Common questions from MEP & AEC firms
Yes. Procore is the most common project management environment we see in MEP and AEC firms. We start without touching it: the workflow produces output your team already knows how to load, such as Procore import templates and bookmarked PDFs. Once that is proven, the next step is read-only access through a service account your Procore admin approves. Writing back into Procore happens only with your process owner's sign-off. Your team keeps using Procore exactly as it does today. If your team is on Procore already, that's a solid starting point.
Bluebeam is where a lot of submittal review and markup work happens in the field. We build AI workflows that run alongside Bluebeam, reading the PDF annotation layer to pull markup comments and cross-reference them against your spec requirements. Your team keeps working in Bluebeam the same way they do today. The time spent manually compiling review notes and chasing spec references goes away.
Yes. Autodesk Construction Cloud has a well-documented API that connects AI workflows directly. Document version monitoring, drawing set management, and RFI workflows all integrate cleanly. If you're still on BIM 360, that works too since Autodesk's underlying platform API covers both environments. We start with whatever your team is actually using.
An AI Readiness Assessment takes 2–3 weeks and gives you a prioritized map of where to start. A focused workflow implementation, like RFI drafting or submittal screening, typically runs 4–8 weeks from scoping to deployment. If someone is quoting you 6 months to automate RFI responses, ask why.
Strict document control is exactly where structured AI performs well. The key is validation: building the workflow against a real sample of your project data, defining the rules it follows, and testing it before any production use. Greg's CQV background means he approaches this the same way a validation engineer would. Define the requirements, test against them, document the results. If it doesn't pass validation, it doesn't ship.
Scope determines cost: the number of workflows, your existing tool environment, and how deep the integration needs to go. Advisory work is available with no long-term commitment for firms that want to start smaller. The best way to get a realistic number is a 30-minute discovery call where we scope your situation directly.