Data Collection

Collect data anywhere, on any form

Works without internet, builds complex surveys visually, and imports from every tool you already use.

Offline-First

Works without internet.
Zero data loss.

Forms are cached locally the moment they're assigned. Enumerators collect GPS, photos, and responses even in remote villages with no signal — data syncs automatically and securely the instant a connection returns.

  • ✓Full form functionality with no connectivity
  • ✓Photos, GPS, audio — all cached locally
  • ✓Auto-sync with idempotency — no duplicates
  • ✓Works on 2G — text first, media batched
FieldGovern — Enumerator App
Offline — 4 forms saved locally
⟳ Connection restored — syncing…
Respondent Name
Village / Ward
GPS Location
4 submissions synced successfully
Form Builder

Drag-and-drop forms.
No coding required.

Design complex surveys with 14+ field types, visual AND/OR skip logic, form versioning, and nested repeat groups. What you build is exactly what your enumerators see — no surprises in the field.

  • ✓14+ field types: GPS, photo, audio, select, repeat
  • ✓Visual skip logic with AND/OR conditions
  • ✓Form versioning — update without losing data
  • ✓Enumerator hints and instructions per field
Form Builder
Text
Number
GPS
Photo
Select
Respondent Name — Text field
Age — Number (18–99) with validation
GPS Location — auto-capture enabled
⤷ Skip logic: if Age < 18, skip Section 3
AI-Powered · Live Now

Describe your study.
AI builds the form.

Share your study objectives and target population — our AI designs a complete, field-ready form with proper sections, skip logic, field types, sub-questions, and enumerator hints. Complex surveys in 90 seconds.

  • ✓20–45 questions, 4–8 logical sections
  • ✓Correct field types — GPS, select, repeat groups
  • ✓Skip logic and conditional flows auto-wired
  • ✓Runs in background — edit when ready
AI Form Builder
Household survey for MGNREGA beneficiaries in Karnataka. Collect work days, wages, bank account linkage, awareness, grievances. Include caste, gender, landholding demographics.
Designing question structure and sections…
Generated: 38 questions · 7 sections · Skip logic applied
Consent
Demographics
MGNREGA Work
Wages & Payments
Awareness
Grievances
Migration

Already on KoboToolbox?
Migrate in one click.

Import from XLSForm, KoboToolbox, SurveyCTO, or ODK Central with a single upload — your existing forms come in exactly as designed, with all skip logic and field types preserved. No manual re-entry.

  • ✓XLSForm / ODK / KoboToolbox / SurveyCTO
  • ✓Skip logic and repeat groups fully preserved
  • ✓Migrate team, not just the data
  • ✓1/3 the cost of SurveyCTO after migration
Platform Import
XLSForm
KoboToolbox
SurveyCTO
FG
1 form imported — 47 questions, skip logic preserved
Next
Supervisor & M&E
Operations & Oversight

Real-time visibility across your entire field team

Supervisor dashboard, GPS mapping, panel/M&E tracking, live sync, WhatsApp alerts, and Google Sheets — all connected.

Sync Engine

5 MB photos.
200 KB by sync time.

Photos, GPS coordinates, and audio sync securely using a two-phase approach — text fields go first on 2G, then media uploads in background batches when bandwidth allows. Auto-compression included.

  • ✓Auto-compress: 5 MB → ~200 KB photos
  • ✓Two-phase: text first on 2G, media batched
  • ✓Secure presigned S3 URLs for all media
  • ✓Resume interrupted uploads automatically
Media Sync
IMG_4521.jpg
Captured · 2025-03-12 11:24
5.0 MB original
0.19 MB compressed
Uploading to secure storage… 0%
✓ Upload complete — linked to submission #847
Supervisor

Flag. Approve. Reject.
In real time.

Review every submission with GPS map view, full audit trail, and photo evidence. Flag suspicious records, assign back-checks, and export any subset as CSV, Stata .dta, or directly to Google Sheets.

  • ✓GPS map view — see exactly where data was collected
  • ✓Flag → back-check assignment workflow
  • ✓Export: CSV, Stata .dta, Google Sheets
  • ✓Full audit trail on every action
Supervisor Dashboard
Today's submissions 23 pending review
Rajesh Kumar
Bellary, Karnataka
✓ Approved
Priya Devi
Bidar, Karnataka
Flagged
Mohammed Irfan
Gulbarga, Karnataka
✓ Approved
Export: CSV · Stata · Sheets ↗
WhatsApp Alerts

Instant notifications.
No dashboard refresh needed.

MSG91 WABA-powered alerts keep supervisors informed the moment enumerators sync, flag a record, or complete their assignment. Real-time field awareness without any polling.

  • ✓Sync alerts — know when each enumerator submits
  • ✓GPS mismatch and QC violation alerts
  • ✓Daily summary digests to supervisor
  • ✓Powered by MSG91 WABA — reliable delivery
WhatsApp Business
FieldGovern Alerts
Official Business Account · Online
Sync Alert
Rajesh Kumar synced 5 forms from Bellary, Karnataka
11:24 AM ✓✓
QC Alert
GPS mismatch detected on submission #842 — expected Gulbarga, recorded Bidar
11:31 AM ✓✓
Assignment Complete
Block 4 survey completed — 23/23 households done
12:47 PM ✓✓
Google Sheets

Every submission.
Auto-appended live.

Connect once and every new submission is automatically appended as a new row to your Google Sheet — in real time, the moment it syncs. Your data is always current without any manual exports.

  • ✓Live append — no scheduled jobs, no manual exports
  • ✓Column mapping preserved across form versions
  • ✓Multiple sheets per form supported
  • ✓Works alongside CSV and Stata export
Google Sheets — Live
MGNREGA Survey 2025 Total: 847 rows
#
Name
Village
Status
845Lalitha B.YadgirSynced
846Kiran S.RaichurSynced
847Rajesh K.BellaryNew ✦
848Priya D.BidarNew ✦
849M. IrfanGulbargaNew ✦
GPS Map & Geofencing

See every submission.
On a live map.

Every response carries GPS coordinates, plotted in real time on an interactive map inside the supervisor dashboard. Cluster markers by district, filter by enumerator or date, and draw geofence boundaries to catch submissions collected outside the assigned survey area.

  • ✓Live map view of every submission's GPS pin
  • ✓Cluster by district/block, filter by enumerator or date
  • ✓Geofence checks — flag submissions outside the survey area
  • ✓Cached OpenStreetMap tiles work for offline supervisor review
Live Field Map — app.fieldgovern.com
FieldGovern live GPS map showing 545 real submission pins clustered across Karnataka and Andhra Pradesh, color-coded by review status
Actual product screenshot — 545 GPS-tagged submissions, live
M&E / Panel Studies

Track the same respondent.
Across every wave.

Built for monitoring & evaluation work — assign respondents to a panel, run the same questionnaire across baseline, midline, and endline waves, and roll indicators up into a program scorecard without losing the thread between rounds.

  • ✓Panel/cohort tracking — same respondent, multiple waves
  • ✓Program-level indicator scorecards, auto-updated
  • ✓Assign forms to arms (treatment/control) for evaluation designs
  • ✓Attrition & re-contact tracking between waves
Programs — app.fieldgovern.com
FieldGovern Programs dashboard listing real M&E programs including PM-KISAN, MGNREGA Work Monitoring, Jal Jeevan Mission, and an RCT baseline, each with collection progress bars
Actual product screenshot — 14 live M&E programs, real collection progress
Deployment & Data Sovereignty

Runs on any device.
Lives on infrastructure you control.

FieldGovern's PWA runs the same form, offline, on Android, iPhone, and Windows tablets — no app-store install, one codebase. On the backend, run our India-hosted SaaS (Mumbai servers, DPDP-aligned) or self-host the entire stack via Docker Compose on your own Linux server, so your data never leaves infrastructure your organisation controls.

  • ✓Cross-platform PWA — Android, iPhone, Windows, no app store
  • ✓Self-hostable via Docker Compose — full source, your servers
  • ✓India-hosted SaaS option — Mumbai/Hyderabad data centres
  • ✓Data sovereignty — encryption at rest/in transit, row-level tenant isolation
Dashboard — app.fieldgovern.com
FieldGovern supervisor dashboard with 545 total submissions, 16 active forms, 103 flagged records, submissions-over-time chart and top enumerators — the same dashboard runs identically whether hosted by FieldGovern or self-hosted on your own servers
Actual product screenshot — same dashboard, hosted or self-hosted
Next
FG Analyzer
FG Writer

AI report writing, connected to your analysis

Bring your own OpenAI, Claude, or Gemini API key — FG Writer turns Analyzer tables and interpretations into a finished, exportable report.

AI Report Writer

Data in. Report out.
Interpretation-aware.

Connect OpenAI, Anthropic Claude, or Google Gemini using your own API key. FG Writer reads the per-table interpretations you stored in the Analyzer — generating richer, contextually accurate narratives instead of re-summarizing raw numbers. Export to Word, Markdown, or scheduled email.

  • ✓Reads stored Analyzer interpretations — starts with analyst context
  • ✓6 report styles: NGO, Government, Research, Medical, Progress, Field Survey
  • ✓Export to Word (.docx) or Markdown — paste into any doc
  • ✓Version history — save, compare, restore any draft
AI Report Writer
claude-sonnet-4-6 · 847 submissions
Generating report…
## Field Survey Summary
Data from 847 respondents, 12 districts.
73% aware of MGNREGA entitlements.
↓ Export as Markdown · Word · PDF
Scheduling & Versions

Set it once.
Reports land in inboxes automatically.

Schedule any report to regenerate and email itself weekly or monthly — supervisors and donors get a fresh narrative without anyone opening the tool. Every generated draft is versioned, so you can compare, restore, or roll back to an earlier write-up.

  • ✓Weekly or monthly scheduled email delivery
  • ✓Every draft versioned — compare and restore past reports
  • ✓Same report definition reused as data refreshes
  • ✓Export destinations: Word, Markdown, or scheduled email
FG Writer — Schedule
✓
Weekly digest — every Monday 9:00 AMActive
✓
Recipients: 3 supervisors, 1 donorSet
✓
Version 4 savedRestorable
Next
Quality & Security
FG Analyzer

Cross-tabs, statistics, and AI — in one workspace

Build tables with AI, run the right statistical test automatically, and catch data quality issues before you present the results.

Smart Builder

Build tables in two ways.
Both powered by AI.

Column Picker: Search and select specific columns from your dataset. AI sees the real unique values from your submissions, then designs the optimal table structure — groupby, aggregation, chart type, and pre-cleaned column labels in one shot.

Ask a Question: Type in plain English — "average age of beneficiaries per district, broken down by gender" — and AI parses all your column headers to build the full table specification automatically.

  • ✓AI sees real unique values — no guess-work on field content
  • ✓Column labels pre-cleaned by AI before the table is built
  • ✓NL query understands field research intent — not just keywords
  • ✓All tables land in the same shared store — instantly visible in Writer
Smart Builder — Column Picker
✓
district_nameselect
✓
genderselect
beneficiary_agenumber
household_typeselect
district_name
gender
2 selected
Groupbydistrict_name
Cross-tabgender
Chartbar (stacked)
✓ Labels pre-cleaned by AI
AI Interpretation

Every table gets
its own narrative.

Choose from 10 methodology-driven focus templates — Distribution & Spread, High vs Low Performers, Equity & Disparity, Change Over Time, Interaction Effect, Concentration Analysis, Outlier & Anomaly, Program Performance, Group Comparison, or Custom focus. No length restrictions — the AI writes as much as the data warrants.

  • ✓Iterative refinement — AI sees your previous interpretation and improves it
  • ✓Side-by-side compare: Previous vs Refined before you commit
  • ✓Auto-saved 2 seconds after you stop typing — never lose a note
  • ✓Stored interpretations flow into FG Writer for richer reports
FG Analyzer — Interpretation
Focus template
Distribution & Spread
Equity & Disparity
High vs Low
Outlier & Anomaly
Custom…
The distribution across districts reveals a significant equity gap — Bellary records 3.2× the average coverage of the bottom three districts combined. Female beneficiaries are concentrated in urban clusters, suggesting outreach gaps in rural blocks that warrant targeted intervention.
Refine & Compare
Previous
Coverage varies by district. Female beneficiaries are fewer in rural areas.
Refined
Bellary leads at 3.2× average coverage. Female outreach gaps persist in rural blocks — targeted intervention needed.
Statistical Analysis

Cross-tabs and the right test.
Chosen for you.

Build cross-tabulations with a click, then let the built-in test chooser recommend the correct statistical test based on your variables' measurement scale — chi-square for categorical pairs, t-test or ANOVA for group comparisons, Pearson/Spearman correlation for continuous variables. Weighted statistics supported throughout.

  • ✓Auto test-chooser: chi-square, t-test, ANOVA, or correlation
  • ✓Weighted means, SDs, and effective sample size
  • ✓P-values and effect sizes reported alongside every table
  • ✓Likert scoring — mean, sum, or z-score, with reverse-coding
FG Analyzer — Test Chooser
✓
district_name × genderChi-square
✓
income by treatment armt-test
✓
age vs satisfaction scoreCorrelation
✓
score across 4 districtsANOVA
Advanced Analysis

From correlation
to what's actually driving it.

Driver analysis one-hot encodes your categorical predictors and runs regression to show which factors move an outcome. For evaluation designs, difference-in-differences causal analysis compares treatment and control before/after an intervention. Power analysis and a guided study-design wizard help you size the sample before you're in the field.

  • ✓Driver/regression analysis with automatic categorical encoding
  • ✓Difference-in-differences causal analysis (pre/post, treatment/control)
  • ✓Power analysis — Cohen's d, required sample size, MDE calculator
  • ✓Balance tables — standardized mean difference across arms
  • ✓Guided study design wizard for evaluation studies
FG Analyzer — Driver Analysis
✓
Top driver: landholding sizeβ = 0.41
✓
DiD estimate: treatment effect+12.4%
✓
Balance check (SMD)< 0.1
Recommended sample sizen = 384
Data Quality & Geo

Duplicates, straight-lining, outliers.
Caught before you analyze.

Survey quality checks scan every response for full-row or partial duplicates and straight-lining (identical answers repeated down a grid), flagging suspect records before they skew your results. Geo aggregation summarizes responses by district or custom boundary, while verbatim coding and cluster analysis round out qualitative and segmentation work.

  • ✓Full-row and partial (column-subset) duplicate detection
  • ✓Straight-lining detection — flags suspiciously uniform grids
  • ✓Geo aggregation — summarize and map by district/boundary
  • ✓Verbatim coding palette for open-ended responses
  • ✓Cluster analysis for respondent segmentation
FG Analyzer — Survey Quality
Duplicate rows found6 records
Straight-lined responses9 records
✓
Districts aggregated on map12
✓
Verbatim codes applied184 responses
Next
FG Cleaner
FG Cleaner

Deduplicate. Redact. Never touch the original.

A safe, separate cleaning workspace — dedup engine, PII redaction, and version-safe working copies.

Deduplication

Find the duplicate.
Keep the original untouched.

FG Cleaner scans your dataset for exact and partial duplicate rows — same respondent submitted twice, same phone number reused, same GPS point recorded minutes apart — and lets you review and merge or remove them without ever touching your raw export.

  • ✓Exact and partial (column-subset) duplicate detection
  • ✓Side-by-side review before merge or removal
  • ✓Works on any uploaded file or FieldGovern-linked form
  • ✓Runs as a separate step from the raw export — nothing overwritten
FG Cleaner — Duplicates
Exact duplicate rows4 pairs
Partial matches (phone + name)7 pairs
✓
Source file unchangedProtected
Privacy

Share the dataset.
Not the identity.

Every identifier field marked on a form — name, phone, Aadhaar — can be automatically redacted or masked before a dataset leaves your hands. Aadhaar numbers are masked to their last four digits; other identifiers are replaced outright, so external partners and donors only ever see de-identified data.

  • ✓Field-level PII redaction driven by the form's identifier flags
  • ✓Aadhaar masking (last 4 digits only) built in
  • ✓Redact single values or entire columns/rows in bulk
  • ✓Same redaction logic reused in Google Sheets sync exports
FG Cleaner — Redaction
✓
aadhaar_numberXXXX-XXXX-4821
✓
phone_numberREDACTED
✓
respondent_nameREDACTED
✓
Fields protected this export3
Safety

Every edit is a copy.
The original never changes.

Cleaning operations run against a working copy of your dataset, never the source file or the live submissions. Step back through your cleaning history, compare before/after, or start over from the untouched original at any point.

  • ✓Working copies isolate cleaning edits from source data
  • ✓Full history of cleaning operations, reversible at any step
  • ✓Export the cleaned copy without ever touching the original
  • ✓Safe to experiment — nothing is destructive
FG Cleaner — Working Copies
✓
working_copy_v3.xlsxCurrent
✓
original_export.xlsxUntouched
✓
3 cleaning steps in historyReversible
Next
FG Writer
Quality & Compliance

Clean data. Full compliance. Always.

Server-side QC, DPDP consent tracking, field-level encryption, tenant isolation, data rights, and multilingual support — built in from day one.

QC Suite

Catch problems
before analysis begins.

Server-side validation, duplicate detection using idempotency keys, GPS mismatch alerts, and a built-in back-check workflow. Your data is clean before it ever reaches the analysis team.

  • ✓Idempotency keys — zero accidental duplicates
  • ✓GPS-coordinate boundary validation
  • ✓Back-check assignment and re-survey workflow
  • ✓AI-detected outliers flagged automatically
QC Validation Report
✓
No duplicate submissions detected 0 found
✓
GPS coordinates validated 847/847
Back-checks assigned 23 records
Statistical outliers flagged 4 records
✓
Idempotency checks passed 100%
DPDP 2023

India's data protection law.
Built into every form.

The Digital Personal Data Protection Act 2023 is baked into the platform — consent tracking per respondent, full audit logs, a data erasure endpoint, and a purpose field on every form. No custom compliance work needed.

  • ✓Per-respondent consent captured and stored
  • ✓Purpose field on every form (DPDP §6)
  • ✓Data erasure endpoint — right to be forgotten
  • ✓Full immutable audit log on all data access
Compliance Dashboard
DPDP 2023 Aligned · Audit Active
Recent Audit Log
Data accessed — Supervisor Meena K.11:24
Export requested — CSV · 847 rows11:31
Erasure request fulfilled — Record #31212:05
Multilingual

English. Hindi. Kannada.
Telugu. And more.

Four languages available out of the box for the enumerator interface. AI-powered label translation lets you add new languages to any existing form in minutes — no developer needed, no strings file to manage.

  • ✓EN · हिन्दी · ಕನ್ನಡ · తెలుగు built-in
  • ✓AI translation — add any language in minutes
  • ✓Per-enumerator language preference
  • ✓Enumerator hints and labels both translated
Enumerator App — Language
EN
हि
ಕ
తె
What is the household's primary source of income?
Select one option — or "Other" to specify
Agriculture
Daily wage
MGNREGA
Other
Encryption

Sensitive fields.
Encrypted at rest.

Personally identifiable fields are encrypted at the database layer using field-level AES encryption — not just disk-level encryption. Public survey responses and per-tenant AI API keys are encrypted with their own dedicated keys, so a database compromise alone doesn't expose respondent identities or credentials.

  • ✓Field-level AES encryption for identifier data, independent of disk encryption
  • ✓Dedicated encryption for public (anonymous) survey submissions
  • ✓Per-tenant AI API keys encrypted separately from respondent data
  • ✓Encryption keys never stored alongside the data they protect
Field Encryption
✓
respondent_phoneAES-encrypted
✓
public_survey_responseAES-encrypted
✓
tenant_ai_api_keyAES-encrypted
Multi-Tenant Isolation

Your data.
Invisible to every other tenant.

Database-level Row-Level Security enforces tenant isolation at the PostgreSQL layer itself — not just in application code. Even a bug in a query can't leak one organization's submissions into another's results, because the database refuses the row before it ever reaches the API.

  • ✓PostgreSQL Row-Level Security enforced per tenant, at the DB layer
  • ✓Isolation holds even if application-layer filtering is missed
  • ✓No shared tables without a tenant boundary
  • ✓Hardened specifically for DPDP-grade data separation
Tenant Isolation — RLS
✓
Tenant A queryTenant A rows only
✓
Tenant B queryTenant B rows only
✓
RLS policies activeAll tables
Data Rights

Access, correction, erasure.
On demand, with a certificate.

Respondents' DPDP rights are handled as first-class workflow: search a request across every form and submission, act on it (redact, export, or delete), and close it out with a generated deletion certificate for your compliance records.

  • ✓Search any request across all forms and historical submissions
  • ✓Act: redact, export, or fully delete matched records
  • ✓Deletion certificate generated automatically on closure
  • ✓Overdue-request tracking keeps compliance SLAs visible
Data Rights Requests
Erasure request — Record #312In progress
✓
Deletion certificate issuedClosed
✓
Overdue requests0