Document automation · Field-to-system intelligence

Documents are the bottleneck in most operations. We close the gap.

Every operations-heavy business runs on documents the office didn’t generate — BOLs from drivers, inspection reports from the field, intake forms from customers, photographs from foremen, scanned invoices from vendors. Today most of that data gets retyped, scanned-and-emailed, or lost in inboxes. We build the capture, extraction, and report-generation layer that turns field documents into structured records, automatically.AI-enabled where it makes sense. Deterministic where it doesn’t. Production-grade for the operations that actually run on this.

Schedule a 14-day audit →Watch the BOL extractor in action →+1.602.815.5600· East-Valley office · same-day reply on weekdays
01. The work

The office shouldn’t be retyping what the field already captured.

Three scenes that repeat across every operation we’ve worked with. A driver hands a signed BOL to a receiver, photographs it, emails it from the cab— and an office coordinator types six fields into the dispatch board two hours later. Six fields that were already on the page.

A coatings inspector finishes a tank job at 6am at a refinery, writes notes in a field tablet, and on Monday spends ninety minutes reformatting those notes into the AMPP-grade report the owner requires. The work was done at 6am. The report exists at the end of the week.

A foreman submits a daily report as a PDF attached to an email; the data never enters Procore as structured records, so the project manager can’t search across reports for the one mention of the broken hose three weeks ago. The report exists. The data doesn’t.

Documents are how operations talk to themselves. Today most of that talking happens in formats systems can’t read. The fix isn’t more discipline; it’s software that meets the field where it actually is— on a phone in a parking lot, on a tablet at a refinery, on a clipboard in a yard. Below: what we build to close that gap, and how it gets shipped.

02. What we build

Four categories of document work. Production-grade.

Each category ships as its own engagement or as part of a full pipeline. Most operations need two or three of the four; the audit produces the named scope.

01 · CAPTUREField document capture
Native mobile and tablet capture for the people generating documents at the source — drivers, inspectors, foremen, technicians, field reps. Photos with EXIF and GPS metadata, structured form fields, electronic signatures, offline-aware queueing.The driver app or inspector app that respects how they actually work — no signal at 3am, no patience for a sync error.
Stack:iOS · Android · Web · Offline-first
02 · EXTRACTExtraction & structuring
OCR and LLM-based extraction from PDFs, photos, scans, and emails. Bills of lading, paint inspection reports, invoices, intake forms, signed documents. Structured field-by-field outputs validated against business rules, with confidence scores and exception flagging for human review. Built on Bedrock, Anthropic, or whichever provider fits the data residency requirements. See the broader Bedrock implementation work for platform-level context.
Stack:Bedrock · Claude · OCR · Validation
03 · GENERATEAutomated report generation
Structured data in, finished documents out. AMPP-grade coatings inspection reports, customer-facing project summaries, compliance documentation, regulatory filings, settlement statements. Template-driven where the format is fixed, generative where the narrative needs to read like the inspector wrote it. The reports your customer, your regulator, or your CFO actually wants.
Stack:Report engine · Templates · Generative · Audit trail
04 · INTEGRATESystem-of-record integration
Documents don’t matter until they land in the system that runs the business — Procore, NetSuite, QuickBooks, Sage, Salesforce, ServiceNow, your custom dispatch board. We build the integration layer that posts extracted data and generated documents as structured records, not as PDF attachments. The customer self-serves what used to require an email to the office. See our Procore work for one example.
Stack:REST · Webhooks · EDI · Custom

Got documents flowing through email and spreadsheets today?

The 14-day audit maps where they start, where they get retyped, and where the gap between field and system actually sits. Output: a written 90-day plan with named workflows, candidate models, and a real estimate.

Schedule a 14-day audit →Book a 30-min call
03. Where this fits

The operations that need this most.

Every industry has documents. A handful runon documents — and that’s where this work earns its keep. The pipelines below are the ones we’ve shipped in production, often more than once.

Construction & coatings

Daily reports, inspection records, AMPP-grade quality control documentation, RFI photo evidence, change-order paperwork. The DocuPaint platform has been running this work in production for 200+ organizations. See our construction practice for the broader build.

Logistics & freight

BOLs, PODs, lumper receipts, rate confirmations, customer invoices, carrier compliance packages. LoadQuest captures and reconciles documents end-to-end. The BOL & POD verification spoke goes deep on the freight-specific pipeline.

Industrial receiving & manufacturing

BOL intake from inbound trucks, weight tickets, material certifications, quality inspection reports. Structured workflows for shop floors that still receive paper. The Apache Junction industrial steel finishing operation referenced below runs this exact pipeline.

Field services

Service tickets, inspection forms, equipment certifications, customer signatures, photo evidence. Mobile capture that posts cleanly to the back-office system the dispatcher actually uses. Same engineering pattern as DocuPaint, applied to HVAC, electrical, MEP, and pest-control verticals.

04. Proof

Document automation we’ve shipped to production.

Three named proof points. Each one is the engineering pattern this page describes, running at production scale, in industries that don’t forgive bad software.

200+
DOCUPAINT
Industrial coatings organizations running an AMPP-grade report engine. Inspectors capture field data on tablet; the platform generates the AMPP reports the asset owner requires. Multi-year engagement, production scale. Read the case study →
4yrs
LOADQUEST
Bill-of-lading capture from email, scan, and driver app. Automated invoice generation, carrier settlement, QuickBooks reconciliation. Years of freight running through the pipeline across multiple operating companies. Read the case study →
1shop
APACHE JUNCTION STEEL
BOL photo intake from inbound trucks at an industrial steel finishing operation. Structured extraction via the Claude API, output to the client’s existing tracking workbook. Closes the gap between paper BOL and the shop’s system of record without disrupting how receiving actually works.
05. How we work

Three engagement modes. Audit, build, retain.

Same engagement model as every other Sytepoint service. Fixed-fee audit, scoped-quote build, capped-hours retainer. Adjusted to the document-automation context but structurally identical — if you’ve engaged us before, you already know the rhythm.

01

The 14-Day Audit

Fixed fee· 14 days

We map the documents flowing through your operation. Where they start, where they get retyped, where they get lost, where the gap between field and system actually sits. Output: a written 90-day plan with named workflows, candidate models, integration points, and a real estimate. More on the audit →

02

The Build Engagement

Scoped quote· 8–16 weeks

Implementation. Field capture apps, extraction pipelines, report engines, system-of-record integrations. Built and shipped to production with audit-grade observability and governance. Code in your repo. Infrastructure in your cloud. Eval suite published before any model goes live.

03

The Retainer

Capped hours· Monthly

Document workflows evolve. Forms change, regulations update, models drift, edge cases emerge. We retain a fractional engineering presence to keep the pipeline accurate as your operation changes. Capped hours, monthly billing.

Want to see the BOL extraction pipeline on a live document?

The 30-minute call walks through capture, extraction, variance check, and posting on a real BOL. Bring a sample or use ours.

Book a 30-min call →See the live demo
06. What we don’t do

The honest list. In case you’re shopping integrators.

01

We don’t do generic “AI strategy.” Every engagement ships running software. Strategy without implementation is the failure mode of this industry.

02

We don’t resell document automation SaaS.If DocuSign, DocuSign Insight, or ABBYY is the right answer, we’ll tell you and refer you. Our work is custom integration and custom pipelines — the work the SaaS doesn’t do.

03

We don’t do consumer document scanning.Our work is operational, not personal. If you’re looking for a Scannable competitor, we’re not the right firm.

04

We don’t ship without evals.Extraction accuracy isn’t a vibe; it’s a measured outcome. Every Build Engagement includes a representative eval set and a published accuracy baseline before any model touches production traffic.

05

We don’t do compliance-only work. Document automation that exists purely to check a box is bad engineering. The pipelines we build are used by the operation, not stored for auditors.

07. FAQ

The questions we get asked first.

How accurate is AI document extraction in practice?

Depends on the document, the model, and the eval methodology — vendor marketing claims of 99%+ accuracy almost always evaporate on real-world inputs. We baseline accuracy on a representative sample of your actual documents before any production rollout. Typed PDFs (rate confirmations, structured invoices, EDI-adjacent forms) routinely hit 97–99% field-level accuracy with current frontier models. Photographed BOLs, handwritten field notes, and faxed documents land lower (high 80s to mid 90s depending on quality) and almost always need a human-in-the-loop step for fields where confidence drops below a configurable threshold. We publish the baseline and the threshold; you decide what's safe to route automatically.

Can we run this on our own AWS or do we have to use a vendor?

Your own AWS is the default. The extraction stack runs on Amazon Bedrock (Claude, Llama, or whichever frontier model fits the data-residency requirement) inside your account, with the orchestration in your VPC and the documents staying in your S3. We do the integration and the pipeline; you keep the cloud account, the IAM, and the audit logs. For broader Bedrock platform work — Codex, Connect, Quick — see our broader build at /services/agentic.

What about handwritten documents — signed BOLs, field notes, inspector annotations?

Handwriting is where naive OCR falls over and where the engineering matters most. Our approach: a vision-capable LLM does the first pass and produces a structured extraction plus a confidence score per field. Anything below threshold (and signatures, always) lands in a human-in-the-loop queue with the source image side-by-side. The human approves, corrects, or flags. The model isn't allowed to silently get it wrong. For coatings inspectors writing field notes on a tablet, we usually replace handwriting with structured form capture upstream — easier than fixing it in extraction.

How does this integrate with our existing system of record?

Documents don't matter until they land in the system the business actually runs on. We build against the public APIs of Procore, NetSuite, QuickBooks (Online and Desktop), Sage 300 CRE, Salesforce, ServiceNow, custom dispatch boards, and EDI 204/210/214/990 where applicable. Extracted data lands as structured records — invoices, daily logs, observations, custom-tool records — not as PDFs stapled to an RFI. See /integrations/procore for one worked example.

What does a document automation build typically cost?

The 14-Day Audit is a fixed fee in the low five figures. Build engagements are quoted against the audit's written plan; typical mid-market scope ranges $80K to $400K depending on document volume, model and infrastructure choices, integration count, and whether a mobile capture app is in scope. Retainers run monthly with capped hours. Every engagement starts with a written quote and a fixed deliverable — no time-and-materials creep.

Do you also build the field capture app, or only the extraction backend?

Both, depending on what your operation actually needs. The DocuPaint platform we built for industrial coatings is the canonical full-stack example: native tablet and mobile apps for inspectors to capture structured field data, the extraction and report-generation backend, and the integration layer that posts to the asset owner's system. React Native for the mobile side, Next.js or NestJS for the backend, Bedrock or Claude direct for the extraction. The audit covers which pieces you actually need vs. which ones you already have.

08. Begin
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Have documents flowing through your operation today that shouldn’t be?

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