# AI-driven Data Collection Platform

Client: Major Indian FMCG manufacturer
Canonical path: /case-studies/field-data-platform

## Summary

A mobile-first survey and data collection platform for field teams, designed around offline workflows and AI-assisted validation.

## Outcome

Improved field-data quality and gave managers faster visibility into incoming survey signals.

## Challenge

Field teams needed to collect high-quality survey data under mobile and offline constraints while managers needed faster visibility into incoming signals.

## Evidence

- Workflow: Offline field data
- Validation: AI-assisted checks
- Visibility: Realtime dashboard
- Primary risk controlled: Low-quality submissions

## Approach

1. Designed around mobile-first data capture and intermittent connectivity.
2. Added validation logic to catch inconsistent or low-quality entries earlier in the workflow.
3. Created a manager-facing dashboard for monitoring incoming field data.
4. Separated operational reporting from raw collection so teams could act without waiting for manual consolidation.

## Timeline

1. Field workflow map
2. Mobile capture
3. Offline sync
4. Validation rules
5. Dashboard rollout

## Risks

- Offline sync conflicts
- Survey fatigue
- Noisy validation
- Manager adoption

## Stack

- Flutter
- Firebase
- Custom analytics
- Realtime data processing

## Next Evidence Step

Replace provisional metrics with client-approved screenshots, raw artifacts, and final numbers when available.