Our estimating data is in spreadsheets, not a structured system — can you still use it?

Yes. Spreadsheet-based job histories are one of the most common starting points. We structure the extraction process during the initial scoping phase.

How does the model handle material price volatility?

The model is trained on historical cost patterns, not live pricing. For current material costs, the knowledge layer can be updated with current price sheets from your vendors on a defined cadence.

Can the system handle multiple trades under one GC?

Yes. Each trade or subcontractor has its own data scope within the system. The general contractor's project data can include or exclude subcontractor-specific knowledge based on data rights agreements.

Our company does both commercial and residential — do we need separate models?

Typically yes. Commercial and residential work have sufficiently different cost structures, code environments, and documentation conventions that separate models perform better than a combined one.

What does onboarding a new estimator look like with this system?

New estimators can query the full project history and code reference corpus from day one. The system accelerates the ramp-up from years to months by making institutional knowledge accessible without relying on mentorship alone.

Construction & Skilled Trades

AI that knows how your trade prices and performs work.

Job history, material costs, labor patterns, and code requirements — structured into knowledge infrastructure that supports estimating, field operations, and compliance.

Construction and skilled trades companies operate on project-by-project knowledge that is rarely captured in a form anyone else can use. Estimating expertise, preferred vendor relationships, hard-won knowledge about material lead times and labor productivity — all of it lives in people's heads and individual project files. RonanLabs builds the infrastructure to make that knowledge queryable.

The data problem in construction & skilled trades

Estimating accuracy in construction depends on institutional memory that is difficult to transfer. Senior estimators carry implicit knowledge about which subcontractors are reliable, which project types run over budget, and how material prices have moved — knowledge that new estimators take years to develop and that the company loses when senior staff retire or depart.

Project documentation is voluminous but rarely structured. RFIs, change orders, submittals, inspection reports, and closeout packages accumulate over the life of a project in formats that don't support cross-project search. Finding a relevant precedent from a prior job requires knowing it exists and knowing where to look.

Building codes, specifications, and standards vary by jurisdiction, project type, and owner requirements. Staying current across a project portfolio that spans multiple jurisdictions and owner standards is a compliance overhead that scales with portfolio size. A missed specification reference early in a project can drive costly change orders late.

Workforce knowledge concentration creates operational risk. Companies where the senior engineer or lead estimator is the single point of failure for critical project knowledge have a continuity problem that becomes acute when that person is unavailable or leaves.

What we deliver

Synthetic data

Synthetic project datasets with realistic cost structures, schedule profiles, and labor patterns for estimating model training and project management system testing without using real project financial data.

Custom models

Estimating and project intelligence models trained on your own job history — capturing your company's specific cost patterns, vendor performance data, and the signals that predict project outcomes in your market.

Knowledge & retrieval

A queryable index of your project documentation, specifications, and applicable code references — so estimators and project managers can retrieve relevant prior work and current code requirements without manual search.

See the full architecture for how these layers fit together.

Common deployments

Estimate review and gap detection

Model trained on the company's project history that reviews new estimates against historical cost patterns, flagging scope gaps and cost line deviations that predict budget overruns.

Specification cross-reference

Retrieval system over project specifications and relevant code sections that answers specific requirement questions with citations to the governing specification or code section.

Change order documentation

Model that drafts structured change order packages from field reports and approved scope changes, formatted to the owner's documentation requirements.

Institutional knowledge capture

Structured interview and document ingestion process that captures senior estimator knowledge into a queryable format accessible to the full estimating team.

Frequently asked

Discuss your construction & skilled trades deployment

Tell us about your data, your constraints, and your workflows. We'll design the layers around them.

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