DOCUMENT WORKFLOW
jobs every document workflow needs
The Challenge
Important work gets buried inside messy documents
Many teams still depend on PDFs, forms, scanned documents, care packets, invoices, contracts, emails, notes, spreadsheets, and uploaded files. The information exists, but it is hard to find, compare, trust, and move into the next step of the workflow.
A staff member opens a packet. Someone else copies details into a spreadsheet. A manager checks for missing information. Another person compares a new version against an old one. A request waits because nobody knows which details are complete, which details conflict, or where the answer came from.
Keystone builds AI document automation systems that extract useful details, organize them into structured fields, summarize what matters, flag missing or conflicting information, and route the result to the right person for review.
Deliverables
What's included
Strategy
We identify the documents, fields, review needs, source rules, risks, and workflow goals before anything is automated.
- Document inventory
- Field and extraction map
- Review and risk planning
Build
We build the document intake, extraction, summary, comparison, flagging, and routing logic around real examples from your workflow.
- Document processing flow
- AI extraction/summary logic
- Structured output design
Handoff
Your team gets clear guidance on how to review results, check sources, handle exceptions, and use the system safely.
- Reviewer instructions
- Source-checking guidance
- Operational runbook
Support
We monitor quality, improve prompts and rules, add document types, and refine the system as real usage reveals edge cases.
- Quality review
- Prompt and rule refinement
- Additional document workflows
How we work
How we build AI document automation
We do not just run documents through AI and hope for the best. We map the document workflow, define what should be extracted, keep sources visible, and build review points around the information your team needs to trust.
Map the Documents
We identify the document types, formats, fields, sources, versions, and people involved in the review process.
Define the Outputs
We define what the system should extract, summarize, compare, flag, route, and never decide on its own.
Build and Validate
We build the document workflow, test real examples, check accuracy, and make source trails visible before launch.
Improve Over Time
We review usage, improve prompts and rules, add edge cases, and expand the system to more document types when it proves useful.
DOCUMENT AUTOMATION EXAMPLES
Common document workflows we automate
A few practical examples of document-heavy workflows Keystone can organize, summarize, flag, and route for review.
INTAKE
RECORDS
Packet Intake Extractor
INPUTS
PDFs / Forms / Assessments
SYSTEM
RESULT
- Large packets become cleaner profile sections with missing or conflicting information
FINANCE
APPROVAL
Invoice Capture & Approval
INPUTS
Invoices / POs / Receipts
SYSTEM
RESULT
- Invoice details are captured, checked against records, and routed for approval with fewer manual handoffs.
CONTRACTS
REVIEW
Contract Review Prep
INPUTS
Contracts / NDAs / Policies
SYSTEM
RESULT
- Important terms, dates, missing fields, and review items are prepared without replacing professional judgment.
FAQ
Common questions
- Still have questions?
We’re happy to help. Reach out to discuss your document workflow, review needs, and where AI can safely reduce manual work.
What is AI document automation?
AI document automation uses AI and workflow logic to extract, summarize, organize, compare, flag, and route information from documents. It can work with PDFs, forms, packets, contracts, invoices, records, notes, and uploaded files. The goal is to make document-heavy work easier to review and act on.
What kinds of documents can Keystone help automate?
Common examples include intake packets, client forms, invoices, receipts, contracts, NDAs, claim documents, policies, field reports, care records, applications, assessments, and document sets that need review before the next step.
Is this just OCR?
No. OCR can turn an image or scan into text. AI document automation goes further by organizing the information, extracting specific fields, summarizing key points, flagging missing or conflicting details, and routing the result into a workflow.
Can the system show where an answer came from?
Yes, that is an important part of the design. For review-heavy workflows, Keystone aims to keep source references visible so staff can check where a fact, summary, or flagged issue came from before relying on it.
Will AI make final decisions from the documents?
That is not the goal. Keystone builds systems that prepare work for review. Important decisions, approvals, legal judgment, clinical judgment, hiring decisions, claim decisions, and financial approvals should stay with qualified people.
Can this work with messy or inconsistent files?
Often, yes. Messy documents are common. We test with real examples, including incomplete forms, duplicate entries, conflicting information, poor formatting, and unusual files. The system should flag uncertainty instead of pretending every result is perfect.
Can document automation connect to our existing tools?
Yes. Document workflows can connect with storage tools, forms, CRMs, databases, email, task boards, approval queues, and internal dashboards. The goal is to move document information into the place where your team already works.
Where should we start if we have many document problems?
Start with one repeated document workflow that takes time, creates delays, or requires review before the next step. Good first projects usually have clear document types, repeated fields, frequent handoffs, and a person who already knows what a good review should look like.
- Still have questions?
We’re happy to help. Reach out to discuss your needs, challenges, and how AI can fit your business.