10+
Years in commercial construction
Project management and estimating across Division 26 electrical systems, lighting controls, commercial coordination, vendors, scope, pricing, and the deadlines that make small inconsistencies expensive.
AI + Construction Technology Consulting
$90K surfaced.
I build AI systems for construction teams that protect margin, give teams back capacity, and keep judgment with the people accountable for the work.
More than a decade in commercial construction. Four years building production AI systems. Practical judgment about where automation pays off, where it fails, and where accountable decisions must remain human.
$92,482Missed revenue and estimating errors surfaced
$1.4MApproximate bid value reviewed so far
~100 hrsManual work saved weekly, total across all connected workflows
10+ yearsCommercial construction management and estimating
The uncommon combination
Built inside construction. Not merely sold to it.
Most AI consultants must learn how contractors think. Most construction consultants cannot build production AI systems. The value is knowing where those disciplines should meet. The technology comes second.
4
Years building production AI systems
Agents, retrieval, orchestration, evaluation, automation pipelines, local and cloud inference, privacy controls, and the operational boundaries required when outputs affect real work.
The advantage is not knowing both worlds. It is knowing what deserves to cross between them.
Selected construction work
Evidence before promises.
The portfolio leads with margin protection, validation, and operational capacity. Every case shows where the system stops and accountable judgment begins.
Flagship case study / Margin protection
An automated bid review surfaced $92,482.
The pipeline reconciles internal quotes, manufacturer quotes, bid breakouts, takeoffs, catalog prices, and service rules. It surfaces disagreements with the evidence attached, then leaves correction and approval to the estimator.
Approximately $1.4M reviewedRecovery rate above 6%Estimator approval retained
Read the case study
Bid QA reviewAnonymized
Breakout conflicts with reconciled takeoffReview
Pass-through amount differs from sourceReview
Service rule not carried consistentlyReview
Evidence attached for estimator decisionHuman
Cumulative value surfaced$92,482
Validation / Pricing automation QA
The automation failed its test. So it was not allowed to ship.
An adversarial QA harness showed that an ambiguous fuzzy matching path was wrong in 63 of 66 cases. The path was removed from automatic pricing, while the validated exact match workflow remained in production.
63 / 66 fuzzy guesses wrong · 20 / 20 exact references correct
Read the case study
Workflow automation / Quote assembly
A raw vendor export became an import-ready quote in one pass.
The system transformed a 24-line source into an 88-line structured quote, preserving ERP-critical fields, applying catalog pricing from one shared source, and removing the manual steps where prior transcription errors occurred.
20 / 20 pilot prices correct · 91 / 98 on an unrelated job
Read the case study
100Approximately 100 hours of manual work saved each week, the combined total across all connected workflows.
Data preparationAutomated
Quote assemblyAutomated
ReconciliationAssisted
Exceptions and approvalHuman
Where I help
Consequential workflows, not generic AI.
The engagement begins where construction teams feel the strain: margin leakage, document overload, preconstruction bottlenecks, and operational knowledge trapped in a few experienced people.
01
Preconstruction intelligence
Bid intake, document review, scope gaps, addenda, pricing QA, quote comparison, proposal assembly, and estimate-to-operations handoff.
02
Construction workflow automation
Turn repetitive coordination, reporting, document, and knowledge workflows into reliable systems with explicit exception handling and human review.
03
AI strategy and implementation
Find the highest-value opportunities, define safe operating boundaries, prototype quickly, and build only where the expected return justifies the complexity.
Technical depth
Construction judgment, backed by production systems.
Construction judgment, backed by production systems. These cases show the production discipline behind the construction work.
System 01 / Orchestration
Concurrent multi-agent execution
A dependency-aware orchestrator produced 2.3x realized end-to-end throughput on decomposable work, with fresh contexts and an independent verify-and-resynthesize gate.
View caseSystem 02 / Sovereignty
Code-enforced local and cloud routing
A fail-to-local router and deterministic redaction gate were validated across 1,821 transcripts and 19,124 events with zero confirmed leaks.
View caseSystem 03 / Adversarial review
Case studies from sensitive sources
A four-stage content pipeline used a separate adversarial reviewer to catch four confidentiality leaks across five drafts before human approval.
View caseWorking method
Observe the work before automating it.
A practical sequence for separating true leverage from impressive technology that creates another system to manage.
Step 01
Observe
Map the real workflow, documents, decisions, exceptions, handoffs, and failure points.
Step 02
Find leverage
Estimate where errors, rework, delay, or administrative load create the greatest commercial cost.
Step 03
Build the smallest useful system
Prototype around one consequential workflow instead of attempting a company-wide transformation.
Step 04
Prove it
Measure outcomes, preserve human review, document the system, and expand only when the evidence supports it.
Trust model
Built for confidential and consequential work.
Construction data is not portfolio material. Responsible implementation begins with protecting the business, the people, and the source documents.
01
Anonymized public workNo job names, clients, part numbers, manufacturers, or real project pricing in published examples.
02
Minimum necessary accessUse only the information required to solve the defined workflow.
03
Traceable evidenceImportant outputs point back to their source inputs, assumptions, and failure conditions.
04
Explicit human approvalAutomation assists accountable decisions. It does not conceal or silently replace them.
05
Honest tool boundariesTechnology choices follow the workflow. Expertise is never invented to fit a sales call.
Judgment engineering · Field notes
Ideas from the workbench.
Notes on construction systems, AI reliability, operational memory, and how understanding forms inside complex organizations.
Observatory / Field note 008
The observatory is not where intelligence watches. It is where judgment learns to see.
A visual essay about retrieval, memory, context, and why collecting more information is not the same as understanding.
Systems note / Draft
Automation earns authority only after it survives contact with real outcomes.
The operating principle behind pricing QA, bid review, and every system allowed to influence consequential work.
Build log / 021
Value engineering my agents.
What cost, independence, contamination, and transaction hardening mean in a production AI system.
Start with the workflow
Where is your construction process losing margin or capacity?
Bring one difficult workflow, overloaded process, or recurring document problem. We will determine whether the right answer is process improvement, automation, a focused AI system, or no technology at all.
Direct contact[email protected]
For initial conversations, describe the workflow without attaching confidential project documents.