Bespoke Software & Operational AI

Real builds for AEC teams. Zero fluff. 100% deployed.

We engineer custom software, governed AI pipelines, and agentic infrastructure for contractors, suppliers, and industrial operators. You own the code. No generic wrappers. Built directly inside the systems you run daily.

Stop paying \$50k/year for generic SaaS shelfware your team avoids. We diagnose the acute friction points costing you payroll and margin, and deploy working production tools in weeks.

Diagnose Your Bottleneck Explore 5 Production Builds

100% Client Owned

Full IP, database schemas, and codebase transferred directly to your organization.

Zero Data Retention

Enterprise API endpoints with explicit zero-training guarantees. Your data stays private.

Deep Workflow Integration

Connects directly into Procore, Deltek, OneDrive, ERPs, and legacy databases.

Fully Governed & Isolated

Human-in-the-loop sign-off gates, deterministic citations, and private cloud deployment.

Operational Failure Modes

Three operational bottlenecks we eliminate permanently.

We don't build software for hypothetical use cases. We engineer systems specifically to remove the acute, labor-intensive bottlenecks where operational knowledge gets trapped, delayed, or lost.

Bid & Spec Friction

Senior estimators lose 15–25 hours per tender reading 200-page specification books and hand-keying compliance matrices. Rushed deadlines cause missed requirements, unpriced risk, or disqualified bids.

Solved in Build 01: AI Proposal & RFP Pipeline

Catalog & Data Scatter

Over 10,000 architectural SKUs, pricing sheets, and ASTM certificates are scattered across OneDrive, local PDFs, and sales reps' heads. Quotes take 48 hours to assemble and junior reps make costly spec errors.

Solved in Build 02: Enterprise Catalog & Spec OS

Contract Scope Drift

Project managers assemble trade subcontracts by copying and pasting unvetted clauses from old desktop files. Obsolete language and scope gaps create costly change order disputes, backcharges, and litigation.

Solved in Build 03: Scope Governance Database

Strategic Evaluation

Build vs. Buy: Why custom operational software wins.

Before signing another \$50k annual SaaS agreement or a 9-month agency contract, evaluate the true trade-offs in ownership, velocity, and alignment with your real workflows.

Dimension	Off-The-Shelf SaaS	Traditional Dev Agency	POLR AI Custom Build
Intellectual Property (IP)	0% Client Ownership (Vendor owns all data models & platform)	100% Owned, but often bloated with endless billable hours	100% Client Code & IP Ownership (Transferred to your private repo)
Time to Production	Instant setup, but 6–12 months low team adoption	6 to 12 months minimum discovery and dev cycles	3 to 6 Weeks from discovery to live production deployment
Pricing & Cost Model	$30–$150/user/month recurring seat tax (grows with headcount)	$150k–$500k fixed bid or open-ended hourly T&M	Fixed Sprint / Milestone Delivery (Zero per-seat recurring fees)
Data Isolation & Security	Shared multi-tenant cloud environments	Custom, but variable security governance and setup	100% Private Cloud (Client's Supabase/AWS/Vercel with strict RLS)
Domain Workflow Match	Rigid, generic templates requiring manual workarounds	Requires client to train agency engineers on AEC industry nuances	Native AEC & Operations Depth (CSI MasterFormat, RFPs, scopes, specs)
Underlying Architecture	Closed proprietary black box you cannot inspect	Monolithic, difficult-to-maintain legacy frameworks	Modern Modular Stack (Next.js 16, Supabase, pgvector, MCP, Claude/Gemini)
Maintenance Burden	High configuration drift; forced vendor feature updates	Heavy ongoing agency retainers required for simple changes	Zero-Shelfware Architecture (Clean TypeScript your internal team can run)

Proven Systems in Production

Five production builds. Real operational ROI.

Explore how we have engineered custom data extraction pipelines, intelligent agent workflows, and internal tools to solve acute operational bottlenecks across commercial contracting, product distribution, and executive ops.

Build 01 / AI Proposal PipelineCommercial Contracting & AEC Firm

Next.js 16SupabasepgvectorClaude 3.7Gemini 2.5TypeScript

Autonomous RFP Ingestion & First-Draft Pipeline

The Operational Bottleneck:

Senior estimating and precon teams spent 15–25 hours per tender reading 200+ page specification books and hand-keying Excel compliance matrices. Past winning qualifications were buried in old PDFs, causing rushed proposals, unpriced risk clauses, and disqualified bids.

The Engineered Build:

A deterministic RFP ingestion engine that parses multi-document PDF packages, normalizes addenda revisions, auto-extracts every mandatory requirement into a structured compliance matrix, queries historical winning proposals in Supabase with vector embeddings, and drafts citation-locked responses with human sign-off gates.

Deconstructs 200+ page solicitation specs into actionable matrices in under 4 minutes
Vector retrieval matches project scope against verified historical winning bids
Mandatory human-in-the-loop review checkpoints before final submission assembly

Pipeline Architecture

1. 200-page RFP PDFUpload

↓ Layout-Aware Parser

2. Requirement Matrix100% Extracted

↓ pgvector Similarity Search

3. Grounded DraftCited

70%+

Faster Proposal Turnaround

0 Missed

Compliance Requirements

[+] Inspect Technical Architecture & Data Isolation

Storage & Vector Engine: Supabase PostgreSQL instance with pgvector extension. Bids and qualifications vectorized with text-embedding-3-small.

Model Orchestration: Vercel AI SDK managing Anthropic Claude 3.7 and Google Gemini 2.5 with operator default keys and workspace-level BYOK.

Security & Privacy: Zero Data Retention (ZDR) commercial API endpoints. Proprietary client RFP data is never used to train public foundation models.

Build 02 / Catalog & Spec OSLuxury Architectural Finishes Distributor

Next.js 16React 19MS Graph APIFirecrawlpgvectorPostgreSQL

Multi-Source Catalog Sync & Sales Spec OS

The Operational Bottleneck:

Over 10,000 architectural SKUs, pricing cut-sheets, and high-res installation photos were fragmented across 20+ manufacturer websites, OneDrive folders, and disconnected PDFs. Assembling client spec sheets took 2–3 days per quote.

The Engineered Build:

A unified internal sales operating system with automated web scraping workers (Firecrawl/Playwright) and Microsoft Graph API OneDrive sync. Combines relational and vector search with an internal contextual assistant for instant product matching and automated PDF submittal generation.

Continuous synchronization between manufacturer web portals and internal catalog database
Automated PDF spec-sheet and client quote generator with verified high-res installation imagery
Sub-second hybrid search across technical attributes (STC, ASTM ratings, finish codes, dimensions)

Sync & Retrieval Architecture

Vendor Portals + OneDriveMS Graph

↓ Firecrawl & Ingestion Workers

Unified SKU & Vector DB10,000+ SKUs

↓ Submittal Assembly Engine

Live Spec Sheet / Quote<15 min

< 15 min

Quote Assembly (from 3 days)

10,000+

Unified Material SKUs

[+] Inspect Technical Architecture & Ingestion Workers

Cloud Document Sync: Microsoft Graph API with app-only authentication via @azure/identity, watching designated shared OneDrive/SharePoint libraries.

Web Scraping Worker: Firecrawl API for automated HTML-to-markdown extraction, supplemented by Playwright workers for dynamic JavaScript vendor portals.

Database Architecture: PostgreSQL on Supabase with pg_trgm (for exact SKU matching) combined with pgvector (for semantic specification search).

Build 03 / Contract GovernanceCommercial General Contractor

Next.jsPrisma ORMPostgreSQLSupabase AuthNode.js Ingestion

Standardized Subcontract Scope Database

The Operational Bottleneck:

Project managers assembled trade subcontracts by copying and pasting clauses from previous project files saved on local desktops. Obsolete safety clauses, missing indemnification language, and conflicting trade boundaries routinely contaminated signed contracts, triggering costly disputes and change orders.

The Engineered Build:

A centralized, role-governed scope ingestion platform. The system ingests legacy Word (.docx) files, deconstructs them into standardized clause blocks categorized by CSI MasterFormat division, and allows estimators to assemble verified trade scope packages in minutes with zero manual copy-pasting.

Automated parsing of historical .docx trade scopes into structured master clauses
Admin governance workflow ensuring only approved, vetted contract terms can be published
Session builders for fast, error-free trade package generation and redline tracking

Governance Pipeline

Hundreds of .docx FilesLegacy Data

↓ Document Clause Ingestion Parser

Master Scope Clause LibraryAdmin Governed

↓ Dynamic Package Assembler

Verified Trade ScopeZero Gaps

100%

Scope Standardization

Zero

Copy-Paste Scope Gaps

[+] Inspect Technical Architecture & Governance Logic

Ingestion Pipeline: Node.js AST parser deconstructing unformatted Word document paragraphs into structured clauses keyed by trade division.

Database Layer: Prisma ORM on PostgreSQL with session-only working views ensuring draft edits never overwrite master approved templates.

Role-Based Access: Only executive administrators can approve and publish master clauses; estimators assemble read-only project packages.

Build 04 / Multimodal AIConstruction Management & Field Operations

Next.jsGemini 2.5/3Claude 3.7PDF Coordinate IndexingTypeScript

AEC Domain Copilot & Document Analyzer

The Operational Bottleneck:

Field engineers, project managers, and superintendents lose hours daily cross-referencing submittals against architectural drawing specs, drafting RFIs, and analyzing CPM schedule delay notices.

The Engineered Build:

A specialized multimodal SaaS assistant powered by Gemini and Claude models. The system parses uploaded blueprint drawings, specifications, and schedules to flag compliance deviations, draft code-referenced RFIs, and detect schedule critical-path impacts.

Direct document analysis across blueprint drawings, spec PDFs, and contracts
Automated contract risk identification and schedule delay claim generation
Persistent conversation context retention across complex multi-week field issues

Multimodal Processing

Drawings + Specs + SchedulesPDF / CAD

↓ Multimodal Vision & Embedding

Cross-Reference Reasoning99.4% Verified

↓ Code-Compliant Output

RFI Draft / Deviation Flag< 15 sec

Faster RFI Drafting

< 15 sec

Drawing Cross-Referencing

[+] Inspect Technical Architecture & Multi-Tenant Boundaries

Multi-Tenant Data Isolation: Row-Level Security (RLS) in PostgreSQL partitions project documents across organizations.

Multimodal Processing: Google Gemini 2.5 Flash / Pro and Anthropic Claude 3.7 vision capabilities for direct plan sheet coordinate inspection.

State & Token Optimization: Dynamic sliding-window context compression maintains session memory without runaway LLM inference costs.

Build 05 / Agentic InfrastructureExecutive Leadership & Operations

TypeScriptModel Context ProtocolPostgreSQLHubSpot APIQuickBooks API

Enterprise Model Context Protocol & Decision Tools

The Operational Bottleneck:

Leadership spent 12–16 hours every week manually checking dashboards, pulling revenue figures from QuickBooks, reconciling deal stages in HubSpot, and acting as human routers between disconnected software silos.

The Engineered Build:

Custom Model Context Protocol (MCP) servers and modular agent plugins that connect autonomous AI agents directly to live internal databases. The system prepares automated morning briefs, monitors operational anomalies, and enables natural-language executive queries under strict permission boundaries.

Secure natural-language interface directly into live production databases
Automated daily executive briefings synthesized across pipeline, accounting, and task queues
Strict human-in-the-loop permission gates: read queries execute autonomously; state changes require approval

MCP Security Layer

CRM + Accounting + ERPInternal APIs

↓ Governed Model Context Protocol (MCP)

Autonomous Decision AgentZero Leakage

↓ Executive Synthesis

Daily 6:30 AM BriefingLive Data

14+ hrs

Saved Weekly per Leader

100%

Deterministic Tool Execution

[+] Inspect Technical Architecture & MCP Tooling

Protocol Architecture: Model Context Protocol (MCP) TypeScript SDK exposing typed, validated tools with Zod schema validation.

Execution Sandboxing: Agents execute inside a private Node.js runtime with granular read/write ACLs. No direct arbitrary SQL execution.

Audit & Compliance: Every tool execution logs inputs, outputs, timestamps, and caller identity for comprehensive enterprise compliance auditing.

Engineering Standards

Sovereign infrastructure. Zero data leakage.

AEC and complex industrial businesses run on sensitive trade data, pricing formulas, and proprietary contract terms. We engineer systems with institutional-grade governance built in from day one.

Zero Training on Your Data

We strictly integrate commercial enterprise API endpoints backed by Zero Data Retention (ZDR) agreements. Your proprietary bids, drawings, contract terms, and financials are never retained or used to train public foundation models.

Deterministic Citations & Grounding

No hallucinated boilerplate. Every AI generation in our systems cites the exact source document, page number, and clause ID. Unverified statements are flagged for human sign-off before leaving the staging environment.

100% Client-Owned IP & Codebase

You own the software from day one. All application source code, database architectures, vector embeddings, and documentation are transferred directly into your organization's private GitHub/GitLab repository. Zero vendor lock-in.

No Proprietary Wrapper Lock-In

We build on open, industry-standard modern stacks: Next.js 16, TypeScript, Supabase, PostgreSQL, and open protocols like Model Context Protocol (MCP). Any competent full-stack engineer can maintain and extend what we build.

The Engineering Protocol

From bottleneck to production in 3 to 8 weeks.

We don't spend 6 months writing strategy decks. We work with senior engineers directly on your codebase and data to deliver working production software rapidly.

Phase 01Weeks 1 – 2

Bottleneck & Data Audit

Interview actual estimators, PMs, and operators who live in the workflow
Inspect source files, OneDrive structures, ERP endpoints, and legacy databases
Draft exact technical architecture, data isolation schema, and quantified ROI baseline

Phase 02Weeks 3 – 6

Rapid Staging Build with Real Data

Deploy functional prototype into a private staging environment by Week 3
Ingest messy historical documents, test vector matching, and train agent pipelines
Weekly review sessions with your workflow owner to iterate on real screen recordings

Phase 03Weeks 6 – 8

Production Hardening & Handover

Rigorous edge-case testing, SOC2 alignment, and security sign-off
Hands-on operator training and complete technical documentation
100% repository transfer into your private GitHub organization with zero vendor lock-in

Executive Due Diligence

Questions owners ask before building.

Who owns the code, data, and intellectual property?

You do, 100% from day one. All application source code, database architectures, vector embeddings, and configurations are transferred directly into your organization's private GitHub/GitLab repository. There are zero recurring platform licensing fees, proprietary lock-ins, or hostage code.

How fast does a custom build ship to production?

Production delivery typically happens in 3 to 8 weeks. Because we build problem-first tools focused exclusively on high-leverage operational bottlenecks without agency discovery bloat, functional staging prototypes are live in weeks, with hardened deployment following shortly after.

How do you handle proprietary company data and client confidentiality?

We enforce enterprise data sovereignty. All AI integrations utilize commercial API endpoints backed by Zero Data Retention (ZDR) agreements, ensuring your proprietary drawings, bids, and contracts are never used to train public models. Data is encrypted at rest and in transit, isolated inside your private cloud or dedicated Supabase instance.

How does custom software integrate with our existing ERP, Procore, or OneDrive?

We build direct connectors using official APIs such as Microsoft Graph API for OneDrive/SharePoint, REST/MCP endpoints for ERPs (Deltek, Procore, QuickBooks, Sage), and webhook pipelines. We replace manual file downloads with automated background synchronization.

What is the difference between POLR Development and the 90-Day AI Sprint?

The 90-Day AI Sprint is an advisory and enablement engagement that diagnoses bottlenecks and builds agentic workflows inside software you already own. POLR Development is standalone custom software engineering for teams needing a proprietary web application, custom database, or bespoke multi-agent architecture.

No Sales Reps • No Pitch Decks

Tell me what's breaking.

I review every submission personally and reply within one business day with a direct, honest engineering assessment of whether custom software or AI is the right answer for your operation.

Response within 1 business day

Strict confidentiality • Zero data sharing

Direct founder access: bg@polrai.com

Brennan GerleFounder & Lead Engineer, POLR AI

“If an off-the-shelf tool solves your problem, I will tell you to buy it. We only build when commercial software fails your real workflows.”

Still exploring where AI creates the most leverage in your business?

Discover our structured 90-day implementation framework or explore our multi-agent operational guide.

The 90-Day AI Sprint|AI Agent Team Guide