Major Indian FMCG manufacturer
AI-driven Data Collection Platform
A mobile-first survey and data collection platform for field teams, designed around offline workflows and AI-assisted validation.
Improved field-data quality and gave managers faster visibility into incoming survey signals.
Challenge
The problem that had to be made measurable.
Field teams needed to collect high-quality survey data under mobile and offline constraints while managers needed faster visibility into incoming signals.
Workflow
Offline field data
Validation
AI-assisted checks
Visibility
Realtime dashboard
Primary risk controlled
Low-quality submissions
Approach
Designed around mobile-first data capture and intermittent connectivity.
Added validation logic to catch inconsistent or low-quality entries earlier in the workflow.
Created a manager-facing dashboard for monitoring incoming field data.
Separated operational reporting from raw collection so teams could act without waiting for manual consolidation.
Project timeline
Field workflow map
Mobile capture
Offline sync
Validation rules
Dashboard rollout
Case study packet
Downloadable evidence brief.
Generated packet for sales follow-up, client review, and future replacement with approved screenshots, raw artifacts, and final metrics.
Evidence cards
4
Risk items
4
Canonical page
/case-studies/field-data-platform
Manifest
/reports/case-study-packets/manifest.json
Risk register
Consulting pattern
Prototype quickly, then turn the demo into an evaluation surface.
The reusable Edxperimental pattern is to make the workflow measurable: inputs, expected output, acceptable failure, operational risk, and a repeatable benchmark before production expansion.
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