Field-service intake
Use a customer-supplied equipment photograph to draft a parts enquiry, with identification checked by a technician.
Capability catalogue
ANNA OS powered ASAMIA AI · Intelligence
Vision model selection
Choose image understanding around the things your team needs to inspect, extract or explain.
Documented capability
Purpose and business value
Vision selection considers image quality, document layout and the consequences of a mistaken interpretation. Photographs, scanned forms and technical diagrams need different acceptance tests. A visual result should distinguish what is observable from what is inferred, and route low-confidence or safety-sensitive cases to a qualified person.
A focused review can reduce manual sorting and transcription while preserving human responsibility for consequential judgements.
Business use cases
Document extraction
Extract fields from an authorised scanned form and flag unreadable or inconsistent values for review.
Quality-check assistance
Compare product images with approved reference examples and prepare an inspection queue—not an autonomous safety certification.
Technical requirements
- 01
Authorised sample images and consent where required
- 02
Image-resolution, format and extraction-schema requirements
- 03
Error thresholds and a qualified review path
- 04
Approved model modality and endpoint access
Functional specification
Evaluate against representative lighting, angles, layouts and missing-detail cases. Record field-level accuracy, unsupported inferences and conditions that require resubmission or human inspection.
Operating controls
This is a planning capability. This page does not activate camera access, image analysis or automated inspection.
Model choice & ANNA LLM
Proprietary base-model policy
ASAMIA model catalogue review
Reasoning model selection
Image model selection
Video model selection
Cost and region evaluation
Model evaluation records
Data retention review
ASAMIA AI access controls
Human-approved model changes