Know what it may use
Approved collections, currency, ownership and access are designed before the interface.
AI assistants / Documents
Turn incoming documents into reviewable structured information.
AI-assisted document intake can classify an incoming file and propose fields, summaries or next steps for a person to verify. GA Applications designs secure upload, document handling, extraction confidence, validation screens and workflow integration so uncertain values remain visible and no consequential record is silently changed from an unreviewed model output.
Bounded requestWhich extracted fields need a person to verify?
RequestRetrieveDraftReview
Draft with evidence
The assistant has prepared a response, but it is not an approved decision.
1Document schema / required evidenceapproved source
2Intake policy / confidence rulecheck currency
Pending review. No external action is available in this demonstration.
Approved sourcesVisible evidenceRole permissionsHuman reviewEvaluationDisable path
Useful because the job is bounded. Trustworthy because the boundaries are visible.
AI assistance belongs inside a designed operating process. It does not replace accountable people, authoritative records or competent professional judgement.
Let people inspect support
Citations, source context and uncertainty travel with the draft.
Keep decisions attributable
Permissions, review, escalation, logging and shutdown routes match consequence.
01
Control how documents enter the system.
Upload, email intake or supported integrations need file limits, malware controls, source context, duplicate handling and a server-confirmed receipt.
Acceptance
Allow only justified formats and sizes with clear failure messages.
Identity
Connect sender, customer, job or case where reliably known.
02
Show each proposed value beside its document evidence.
Reviewers can compare extracted fields with the page or region that supports them, correct mistakes and mark information as absent.
Confidence
Use confidence as a review aid, not a truth score.
Correction
Capture the approved value without overwriting the original file.
03
Route verified information into the appropriate workflow.
Only approved fields create or update CRM, job, finance or document records; exceptions remain in a visible queue.
Validation gate
Require key identifiers and consequential values to be confirmed.
Destination
Record what was written, where and by whose approval.
04
Protect document contents and retention.
Files may contain personal, financial, health or commercial information, so provider use, access, storage, logs and deletion require explicit design.
Minimise
Send only necessary content to approved processing components.
Retention
Separate original-file, extracted-data and diagnostic-log lifecycles.
05
Evaluate with representative layouts and difficult cases.
Testing covers scans, handwriting where considered, missing pages, tables, conflicting values, poor images and adversarial content.
Ground truth
Use human-verified samples and field-level scoring.
Fallback
Route unsupported or low-confidence files to manual handling.
Questions worth answering
What teams ask before they commit.
Can AI read every document accurately?
No. Results vary by layout, scan quality, handwriting, language and field type. Human validation and a manual fallback remain part of the workflow.
Can it update our CRM automatically?
Verified low-risk fields may flow into a CRM under approved rules. Sensitive or consequential information should remain subject to explicit review.
Extract, then verify
Test one representative document journey.
We can map intake, proposed fields, reviewer decisions and the approved destination.