dView.ai
Document intelligence for field operations
The problem
Field staff photographed forms on phones in poor light; back-office staff retyped them. The retyping was the bottleneck and the source of most errors.
How we approached it
We treated confidence as a first-class output. Anything below threshold goes to a review queue rather than silently entering the system — the pipeline is judged on how little it needs a human, not on pretending it never does.
Architecture
Capture
Mobile capture with on-device quality checks before upload.
Preprocess
Deskew, denoise and region detection.
Extract
Field-level extraction with per-field confidence scores.
Validate
Cross-field rules catch internally inconsistent documents.
Review
Low-confidence fields queued for human confirmation.
Outcome
- Manual data entry reduced by roughly nine tenths.
- Error rate fell because humans now check flagged fields instead of retyping everything.
94% — fields extracted without review.
Other systems we have shipped
VistaCloud
Multi-entity payroll with a statutory compliance engine and an approvals workflow that finance teams actually trust.
ai · United StatesVueMotion
Pose extraction and joint-angle tracking that turns a coach's phone into a motion-capture rig, with reporting they can read.
platform · AustraliaNovel Aquatech Portal
Site monitoring, service scheduling and client reporting for a water treatment company running dozens of installations.
Tell us the hard part. That is the bit we want.
A 20-minute call, no deck. Bring the problem you have not been able to hand to anyone else.