Document and field automation
Turn documents, job walks and field notes into structured data
A lot of construction information still lives in PDFs, scans, photos, voice notes and spreadsheets someone retypes. We build the pipelines that read those inputs, pull out the fields that matter, flag what needs a person to check, and route the result to the system or report that uses it.
The value it creates
Time saved
Less retyping
OCR and extraction pull fields out of PDFs, scans and images, so staff review and correct values instead of keying them in from scratch.
Standardization
Same structure every time
Job walks, meeting notes and monthly registers are captured against a defined checklist or list schema, so every project reports the same fields the same way.
Cost saved
Fewer entry errors to chase
Validation at the point of capture catches missing or malformed values before they reach accounting or reporting, which cuts the rework of finding them later.
Visibility
Field information tied to the project
Photos, video, transcribed audio and checklist answers from a job walk are linked back to the project, so the office sees what the field saw.
Early warning
Gaps flagged, not dropped
Fields the extraction could not read with confidence, and inputs that are still missing, are flagged for review rather than silently filled or skipped.
Collective intelligence
One record for office and field
Structured notes and extracted data land in the same place reporting and agents read from, so finance, operations and the field work from one set of facts.
What we build
OCR and document extraction
Pipelines that read PDFs and images and extract the fields you need, built on OCR services such as our open-source Mistral OCR MCP server.
Job-walk and meeting transcription
Audio captured on a walk or in a meeting is transcribed and turned into structured notes tied to the project, as in Connect.
Field data capture
Editable checklists with photo, video and audio capture that store what was observed against the right project.
Structured manual inputs in SharePoint lists
Versioned SharePoint lists with validation for the data no system holds, such as risks, wins, attestations and baseline dates, feeding reporting directly.
Document indexing with citations
Project files stored in a predictable folder structure, read with OCR and indexed, so agents and people can point to the file each fact came from.
Routing to downstream systems
Workflows that send extracted and captured data to the system that owns it, such as Procore, accounting, a SharePoint list or the reporting lakehouse.
Review queues for low-confidence values
A place where unreadable or out-of-range values wait for a person to confirm, with the source document alongside.
How it works
1.Capture
Upload, email, photo or audio from the field.
2.OCR / transcription
Turn scans and recordings into text.
3.Classify & extract
Identify the document type and pull out key fields.
4.Validate & human review
Checks flag low-confidence fields for a person to confirm.
5.Route & archive
Send to the right system and keep a searchable archive.
- 1
Inventory the inputs
We list the documents, forms and field notes involved today, who produces them, and where the information ends up.
- 2
Define the fields and rules
We agree which fields to capture or extract, what makes a value valid, and what happens when one is missing or unclear.
- 3
Build capture and extraction
We build the OCR, transcription, checklist or SharePoint list inputs, with validation at the point of entry.
- 4
Route and reconcile
Clean values flow to the target system or lakehouse; flagged values go to a review queue with the source attached.
- 5
Measure and tune
We track extraction accuracy, review volume and completeness from the first run, and fix recurring problems at the source.
Systems we work with
- Mistral OCR
- Model Context Protocol (MCP)
- SharePoint lists
- Microsoft Power Automate
- n8n
- Procore
- Microsoft Fabric
- PDFs, scans and photos
How we measure the value
We agree a baseline before we build and measure the same things after go-live. Use the monthly report cost calculator to put your own numbers on it.
| What we measure | How baseline and after are captured |
|---|---|
| Time spent keying in document data | We time a sample of documents entered by hand today, then the same document types processed through extraction, including review and correction time. |
| Extraction accuracy by field | We compare extracted values against a hand-checked sample before launch to set a baseline, then re-check samples as document types or models change. |
| Share of values sent to review | The review queue records every flagged value from day one, so the rate is tracked against the first weeks of use. |
| Completeness of manual inputs | Before go-live we count which required inputs arrive complete and on time in today's spreadsheets; after, reporting shows which required list entries are filled for each project and period. |
| Time from job walk to shared notes | We compare how long walk notes take to reach the team today against the time from walk end to structured notes after transcription is in place. |
Use cases
- We design and build this
Invoice and document OCR extraction into Procore and accounting
OCR reads incoming invoices and documents, extracts the fields you need, validates them against your systems and sends anything uncertain to a person.
- Built and shown
Meeting and job walk transcription tied to the project record
Meetings and job walks are recorded, transcribed, summarized and attached to the project, so what was said and seen becomes searchable project context.
- Built and shown
Field data capture app for checklists, photos and site notes
A mobile screen built for one field job, such as walks, checklists or quantities, that files data straight to the project and onward to your systems.
- Built and shown
Structured manual inputs in SharePoint for data no system tracks
Wins, risks, safety, and QC registers move from loose spreadsheets into SharePoint lists with defined fields that flow through the same quality checks.
- Built and shown
AI assistant for project drawings, specs and documents
Ask questions of a project's drawings, specs and meeting notes and get answers that cite the file and passage they came from.
- We design and build this
AP invoice approval routing by job, cost code and amount
Vendor invoices routed to the right project manager by job and amount, checked against the commitment, and passed to accounting once approved.
- We design and build this
Certificate of insurance expiry tracking and vendor reminders
Expired and expiring certificates of insurance flagged by vendor and project, with renewal requests sent before coverage lapses.
- We design and build this
Daily log reminders that chase only the jobs that are missing one
A scheduled check that finds active projects with no daily log for the last workday and reminds the person responsible, not the whole company.
Proof
- BuildConnect: file intelligence and job-walk transcription (Production)
- WalkthroughConnect agentic scheduling walkthrough
- BuildConstruction reporting with SharePoint list inputs (Production)
- ArticlePlaybook: replacing a monthly Excel report, manual inputs included
- CodeMistral OCR MCP server (open source)(opens in a new tab)
Ways to start
Frequently asked questions
What kinds of documents can you extract data from?
PDFs, scanned pages and images, such as invoices, certificates, forms and logs. OCR turns the page into text, then extraction rules or a model pull out the specific fields you need. Which fields and how they are validated is agreed during discovery for your document types.
What happens when OCR gets a value wrong?
We design for that. Values that fail validation or come back with low confidence go to a review queue with the source document alongside, instead of flowing straight into your systems. We also check accuracy against a hand-verified sample before launch and keep sampling afterward.
How does job-walk transcription work?
In Connect, a job walk gives the user an editable checklist plus photo, video and audio capture. Audio is transcribed automatically, and when the walk ends everything is tied back to the project so the agents can use it. We can build the same pattern for your walks and meetings.
Why SharePoint lists for manual inputs instead of Excel?
Some data, like risks, wins or attestations, exists in no system. Keeping it in loose spreadsheets makes it hard to validate and report on. Versioned SharePoint lists give each input a defined structure and validation, and the reporting platform reads them directly; our production construction reporting build uses 17 of them.
Where does the extracted data go?
Wherever it belongs: Procore, your accounting system, a SharePoint list, or the reporting lakehouse in Microsoft Fabric. We build the routing with Power Automate, n8n or code, depending on what you already run.
How do we start?
Pick the one document type or field process that costs the most retyping. An integration sprint or AI readiness review scopes it, and the build runs at a fixed scope and price, agreed after discovery.
Next step
Which report or workflow would you like to improve?
Tell us what your team does today, which systems are involved, and what you want to change. We'll discuss whether there is a practical fit.
Prefer email? charley@buildflows.ai