Illustrative use cases
See how scanned files, structured extraction, approved knowledge, and human review can form one controlled document workflow.
This page holds worked workflow examples: illustrative patterns, not published customer results or performance claims. Each follows OCR → validate → RAG → controlled action. For working systems you can open see Applications; for what each sector requires see Industries. Documented client projects will be published here as permissions allow.
Workflow patterns
OCR makes visual information usable, validation checks the fields that matter, RAG retrieves relevant approved evidence, and a person remains responsible for consequential decisions. Controlled automation can then draft, classify, route, or update a system within explicit limits.
Inputs: Invoices, purchase orders, delivery records, supplier details, and approval policies.
Workflow: OCR extracts line items and references. Validation checks required fields and matching rules. RAG retrieves the relevant policy or order context. A controlled step prepares an exception summary for an authorized reviewer.
Intended value: A more consistent queue with evidence attached to each review, without automating payment approval by default.
Inputs: Intake forms, referrals, supporting documents, administrative policies, and routing rules.
Workflow: OCR classifies documents and extracts required fields. Validation identifies missing or low-confidence information. RAG retrieves the applicable administrative guidance. Staff review the evidence before routing or requesting corrections.
Intended value: A traceable intake process that supports administrative work while keeping clinical judgment and sensitive decisions with authorized professionals.
Inputs: Scanned manuals, specifications, drawings, requirements, reports, and project records.
Workflow: OCR recovers text, tables, and page references. Validation checks document identity and metadata. RAG returns answers with citations to the approved version. A controlled step can draft a review note, but an engineer approves technical conclusions.
Intended value: Easier inspection of the evidence behind an answer across fragmented project knowledge.
Inputs: Contracts, amendments, policies, control documents, and approved clause guidance.
Workflow: OCR and document processing identify pages, clauses, dates, and parties. Validation flags uncertain extraction. RAG compares the document with approved language and cites its sources. A controlled action routes issues to the right subject-matter reviewer.
Intended value: A structured first review with traceable source context, not a replacement for legal advice or final approval.
Inputs: Customer attachments, product guides, service policies, troubleshooting material, and prior approved answers.
Workflow: OCR reads attached screenshots, forms, or scanned correspondence. Validation checks key identifiers. RAG retrieves current guidance and citations. A controlled step drafts a response for an agent to verify, edit, or escalate.
Intended value: More consistent access to approved knowledge while preserving human control over the final customer communication.
Inputs: Orders, delivery notes, invoices, inventory records, supplier documents, and operating procedures.
Workflow: OCR extracts references, quantities, and dates. Validation checks formats and reconciles known records. RAG retrieves procedure and supplier context. A controlled action can draft an exception record or route it to operations staff.
Intended value: A clearer path from incoming paperwork to a reviewable exception, with the source documents retained.
Service fit
Use OCR when the workflow depends on text, tables, fields, layout, or classification that is not reliably available as machine-readable data. Design confidence thresholds and review queues around the most consequential fields.
Explore OCR document processingUse RAG when people must ask questions across changing, private, or distributed content. Test retrieval separately from answer quality, preserve source permissions, and provide citations that reviewers can inspect.
Explore RAG development servicesAdapt the pattern
Include normal documents, difficult scans, multiple layouts, edge cases, access restrictions, and examples that should be rejected or escalated.
Specify required fields, acceptable sources, citation needs, schemas, review thresholds, and the systems that receive the result.
Create human-reviewed examples for extraction and retrieval, then test missing information, conflicting sources, uncertain results, and permission boundaries.
Decide what the system may draft or route, what requires approval, what must remain manual, and how exceptions and production changes will be reviewed.
Your use case
Bring representative documents, current process steps, approved knowledge sources, required outputs, and security constraints. We will help define a practical pilot across OCR, validation, RAG, and human-controlled action.