AI Development & Deployment — Red Grey Solutions

Service Overview

Most AI projects in construction stall because the data isn't ready. The second most common reason is that the workflow the AI is supposed to improve isn't documented well enough to automate. We don't start with the model. We start with the data and the workflow — and we don't deploy AI until both are ready for it.

AI Development & Deployment is the workstream that takes a construction operation from AI-curious to AI-operational. We assess readiness, build the data foundation if it's missing, identify the highest-ROI use cases, develop or configure the AI tools, integrate them into your workflows, and measure the result every month against a baseline we establish in Discovery.

A Red Grey Principal Advisor owns this workstream for the term of your retainer. They staff it internally across AI engineering, data engineering, and construction domain expertise. You define the business problem. We tell you whether AI is the right answer and what it would take to deploy it correctly. You approve every deployment before it touches a live workflow.

Start with a Discovery Engagement Talk to Us First →

What This Delivers

Outcomes you can measure. Every month.

Every Engagement begins with an AI readiness assessment and use case evaluation. At the end of Discovery, you have a scored readiness report, a ranked use case list with ROI estimates, and a sequenced deployment roadmap. Every month after that, the outcome review measures what the deployed AI is doing against the baseline.

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Working AI Deployments

AI tools running in your live workflows — not in a demo environment, not in a pilot that never converts. Estimating automation that your estimators actually use. Document processing that runs on real submittals. Field reporting that captures data your PM actually needs.

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Measured ROI

Every deployment baseline-measured before it goes live. Monthly outcome reviews that put a number on what the AI is recovering — hours, error rate, margin. If it's not moving the metric it was deployed to move, we fix it or remove it.

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Safe Deployment

AI deployed with human review at the decision points that matter. No AI making final cost estimates, final change order decisions, or final safety determinations without a qualified person in the loop. Guardrails documented in the SOW.

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Documented AI Operations

Every deployed AI tool comes with documentation: what it does, what it doesn't do, what data it runs on, how to monitor it, and how to know when it's degrading. Your team operates it. We don't hold the keys.

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Construction-Specific Models

AI configured and fine-tuned against construction workflows, construction documents, and construction cost data — not generic enterprise prompts that sort of work. MasterFormat cost codes, CSI document categories, construction contract language. The domain is built in.

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Automation That Holds Up

Automations designed to handle the edge cases that break generic workflows — partial documents, inconsistent naming, mid-project scope changes, multi-tier subcontractor structures. Tested against your data before deployment.

How We Work

Common workstreams under this service.

These are the most common workstreams we build under AI Development & Deployment. The specific use cases depend on your data readiness, your workflows, and your highest-cost operational problems. Discovery defines which ones to pursue and in what order.

AI Readiness Assessment ⚙

→ Evaluate your data environment, your workflow documentation, and your infrastructure.
→ Assess against the specific requirements of the AI use cases you're targeting.
→ Score readiness across six dimensions: data quality, system connectivity, process maturity, staff readiness, infrastructure, and leadership alignment.
→ Deliver a scored report and a sequenced readiness roadmap.

Estimating & Preconstruction AI ⚙

→ Deploy AI-assisted tools for takeoff review, historical cost modeling, bid cleanup, and subcontractor analysis.
→ Configure models against your cost history, your trade coverage, and your bid formats.
→ Deliver automation that reduces estimating hours on routine bids and improves accuracy on complex ones.

Document Processing & Extraction ⚙

→ Deploy AI tools that read construction documents, submittals, specifications, RFIs, change orders, contracts, and extract structured data.
→ Build the extraction pipeline, define the output schema, and integrate with your document management and PM platform.
→ Deliver processing that runs on real documents at scale.

Field Reporting & Safety AI ⚙

→ Deploy AI tools for field reporting, voice-to-text daily logs, photo-based progress documentation, safety observation capture, and checklist automation.
→ Build the mobile interface, the data extraction layer, and the integration with your PM platform.
→ Deliver field reporting that your supers and foremen actually complete.

Cost Forecasting & Variance Detection ⚙

→ Deploy AI models for cost-to-complete forecasting and variance flagging.
→ Train against your historical project data. Build the integration with your field actuals and cost model.
→ Define the variance thresholds and the alert routing.
→ Deliver a forecasting layer that surfaces problems before they compound.

AI Operations & Monitoring ⚙

→ Every deployed AI tool requires monitoring.
→ Monitor data drift detection, performance measurement, output quality review, and retraining schedules.
→ Build the monitoring infrastructure for each deployment.
→ Define the health metrics, the alert thresholds, and the review cadence.
→ Deliver an AI operations framework your team can run without specialized support.

The Engagement Process

From the first call to retained delivery. Here is exactly how it works.

Every engagement follows the same sequence. No surprises. No ambiguity about what you're agreeing to before you agree to it.

Scoping Call — 30 Minutes

You describe the challenge. We ask the questions that tell us where the problem actually lives. By the end of the call we tell you which workstream addresses it, what Discovery looks like for this specific problem, and what the first 30 days produce. You leave with a verbal scope and a clear picture of what comes next. No pitch deck. No follow-up sales cycle.

Mutual Non-Disclosure Agreement

Before we review any project data, financials, or internal systems, both parties execute a Mutual NDA. This is a standard two-way confidentiality agreement — it protects your data and our methodology equally. We send it, you review it with your counsel if needed, and we execute before anything substantive is shared. Typical turnaround is one to two business days.

Master Service Agreement

The MSA governs the overall relationship — intellectual property ownership, liability, payment terms, dispute resolution, and termination provisions. It is executed once and covers every Statement of Work issued under it. We provide the standard Red Grey MSA. You review it, propose any changes, and we agree before any work begins. The MSA is the legal foundation. The SOW is the operational scope.

Discovery Engagement — 30 Days

Month one is always Discovery. For AI Development, Discovery is a 30-day readiness assessment and use case evaluation. We assess your data environment across six dimensions, evaluate the AI use cases you're targeting against your actual data and workflows, and score feasibility and ROI for each. We identify what's ready to deploy now, what needs data preparation first, and what belongs further down the roadmap. At the end of 30 days, we deliver a written findings report: a scored AI readiness assessment, a ranked use case list with ROI estimates and feasibility scores, and a sequenced deployment roadmap.

Statement of Work

The SOW is issued after Discovery findings are reviewed and accepted. It defines the specific workstreams to be delivered, the success metrics for each, the systems in scope, the communication cadence, and the term. It is signed before month two begins. The SOW is not a proposal — it is the execution document built directly from the Discovery findings. If the Discovery findings don't support a particular workstream, it doesn't appear in the SOW.

Retained Term — Monthly Delivery

The retainer runs on a monthly cadence from SOW execution. Weekly working sessions move each workstream forward. Monthly outcome reviews measure what moved against the baseline established in Discovery. Every month produces a working artifact — a tool, integration, workflow, or process that exists in your operation. Your Principal Advisor signs off on every deliverable. You approve outcomes and success metrics. You do not manage the engineering work.

Scaling Engagements — Scope Change Engagement

The number of concurrent Engagements is set at contract signing and fixed for the term. If your priorities shift mid-term and you need to add or remove a workstream, that requires a Scope Change Engagement — a structured rescoping process that produces updated findings, a revised SOW, and a clear transition plan. The Scope Change Engagement is priced at your original Discovery rate and billed in addition to your current monthly retainer. Changes take effect at the start of the next engagement cycle after the Scope Change Engagement is complete. At contract renewal, your Engagement count can be adjusted with no Scope Change Engagement required.

Runbook & Adoption Handoff

Every workstream closes with a Runbook & Adoption Pack. The runbook documents how the tool or workflow operates, who owns which step, how data quality is maintained, and how to know it is being used. The adoption pack covers staff training, role-level instructions, and what a healthy versus degraded state looks like. The handoff is documented, reviewed, and signed off before the Engagement is marked complete. This is not a PDF filed away. It is the operating manual for the artifact we built.

Systems Access & Security

How we access your systems. What we touch. What we don't.

This work requires access to your systems and data. We take that access seriously. Here is exactly how it works.

What We Access

Read access to your data environment, your platform stack, and the workflows the AI will operate in. We need to assess data quality, volume, and structure for the specific use cases being evaluated — cost data for forecasting models, document samples for extraction pipelines, field reporting data for automation candidates. No production system write access is required during Discovery.

How Access Is Granted

We request the minimum permission set required for the workstream in scope. Where possible, we use read-only credentials for data review and analysis work. Write access is requested only for the specific systems we are building into. We do not request admin or owner-level access unless the workstream explicitly requires it — and if it does, that is documented in the SOW and requires your written approval before access is granted.

Credential Management

Credentials are stored in a dedicated password manager, never in email or shared documents. Access is provisioned to the named Red Grey engineer assigned to the workstream. Access is revoked at the end of the Engagement or immediately on request. We do not retain credentials after an Engagement closes. If you prefer to provision temporary access per working session, we accommodate that without adding friction to the delivery cadence.

Data Handling

Your data does not leave your systems unless a specific integration or export is part of the workstream scope. Working files used during analysis are stored in a Red Grey client workspace, not in personal accounts or shared drives accessible outside the Engagement team. The NDA governs confidentiality. The MSA governs data ownership — your data is yours. We build on it. We do not retain it.

Communication Security

All client communication runs through a dedicated Slack workspace. Red Grey maintains its own workspace with per-client channels. Your team connects via Slack Connect — you see your channel only, not any other client's. Sensitive documents are shared via a secure link, not as email attachments. We do not use SMS for anything substantive. We do not discuss project data on open channels.

Access Offboarding

When an Engagement ends — whether at term, by mutual agreement, or by early termination — we initiate access offboarding within 24 hours of the final engagement date. All credentials are revoked, all working files are either returned to you or deleted per the offboarding checklist in the SOW, and a written confirmation is issued. You do not need to chase us for this.

Where to Start

Every engagement begins with a 30-day Discovery.

Discovery is not a consulting engagement you buy hoping it leads somewhere. It is month one of a retained workstream. It produces a written findings report. It becomes the foundation of your SOW. If the findings don't support moving forward, you have a clear picture of why and what to do about it — and you are not locked into anything.

AI Development & Deployment — Discovery Engagement

30 days. An honest readiness score and a sequenced deployment roadmap.

The Discovery Engagement for AI Development covers three areas: AI readiness assessment across six dimensions, use case evaluation and ROI estimation for your target deployments, and deployment sequencing based on readiness and business impact. We review your data quality, your workflow documentation, your infrastructure, and your team readiness. We evaluate every AI use case you're considering against what your data and workflows can actually support. At the end of 30 days, you have an honest picture of where you stand and what to build in what order.

Written AI readiness report — scored across six dimensions with gap analysis

Use case evaluation — each target use case scored on feasibility and ROI

Data readiness assessment — what's clean enough to run AI on and what isn't yet

Deployment roadmap — sequenced by readiness and business impact

Infrastructure assessment — what you need to deploy and host AI workloads

Baseline metrics — current workflow performance we'll measure AI impact against

Start a Discovery Engagement → See How Engagement Pricing is Structured →

Discovery-Only Hold Policy. If you complete a Discovery Engagement and do not immediately convert to a retainer, your findings remain valid for 90 days. If you return within that window, you convert directly to a retainer with no additional Discovery required. After 90 days, a new Discovery Engagement is required before a retained term begins.

Not sure which service to start with? The scoping call is the right place to figure that out. Tell us what you're dealing with and we'll tell you where to start.

AI Development& Deployment