Voice-to-data capture, AI Solutioning, Indian Insights Company

The problem on the ground

The people closest to your customers rarely sit at a keyboard. Field officers, route salesmen, service technicians, distributor reps. They talk for a living, they walk for a living, and they speak a language that is almost never English.

Ask them to fill a form at the end of every visit and three things happen. Half the visits go unreported. The other half come back in shorthand only the writer understands. And the one piece you actually needed, the reason a customer was unhappy, the SKU that went missing from the shelf, the price the competitor quoted, never makes it into a system you can query.

So we did the obvious thing. We let them speak, in whichever language they speak, into the chat app they already use, and we built the pipeline that turns those voice notes into clean rows in your database.

The architecture, in one picture

From a voice note in a group chat to a matched, actionable record.

The note is transcribed and structured, then married to your existing data, so it stops being a sentence and becomes something you can act on.

Field capture

The rep speaks

A voice note, any language
Hands-free, mid-visit

Transcribe

Speech to text

In the source language
Flagged per group

Translate + extract

Into structure

Rendered into English
Entities pulled to JSON

Match + validate

Married to your data

Tied to the right customer, route, order
Now an actionable record

Your records

Existing data

Customers, routes, orders, history

★

Insight

A new, insightful dataset

Every field visit becomes structured data
Patterns and inferences you couldn't see before

How it begins

A voice note, into a chat the field team already uses.

WhatsApp groups and Telegram channels are the de facto interface for Indian field operations. We do not ask anyone to install a new app, or learn a new flow. The salesman finishes a call, taps the mic, speaks for thirty seconds, and moves on.

How the AI takes over

Wispr Flow transcribes. Claude translates and extracts.

The audio is picked up the moment it lands. Wispr Flow handles speech-to-text in the original language, preserving names and places. Claude then translates to clean English and pulls out the structured fields you actually wanted: customer, location, outcome, the lot.

What lands in your hands

A row in your database, ready to query.

The extracted record is mapped to your schema and written to your operational database. By the time the rep walks to the next shop, the previous visit is already a structured row, already in your morning dashboard, already chasing the next decision.

The blueprint

What makes it work.

The pipeline is small on purpose. Fewer moving parts means fewer places to fail, and a system the team can actually maintain after we hand it over.

The intake bot sits on a service number inside WhatsApp Business or a dedicated Telegram bot. Voice notes are auto-pulled the moment they arrive. Webhook
Audio normalisation handles the ten formats WhatsApp will throw at you (opus, m4a, ogg, the lot) and converts to a canonical sample rate before transcription. FFmpeg
Transcription runs on Wispr Flow with the source language flagged per group, so a Tamil group is transcribed as Tamil, a Hindi group as Hindi, and so on. Wispr Flow
Translation and extraction happen in a single Claude call with a tuned system prompt. The prompt is given your schema, your field domain, and a handful of golden examples. Output is forced to JSON. Claude
Schema validation happens before write. A failed extraction (unrecognised customer, missing required field) is bounced back into the group as a polite clarifying question, and the loop reruns when the rep replies.
Database write goes through a thin adapter so it works against Postgres, MongoDB, SQL Server, or a REST endpoint into whatever operational system you already run.
Audit trail. Every transcript, translation, and extraction is logged with the original voice file, so you can always go back to source when a number looks off.

Voice-to-data capture