Stop typing up the conversation:
the agent writes the CRM for you
Every sales conversation ends with the same chore: open the CRM, remember what was said, type it into the right fields before it is forgotten. An agent reads the conversation as it happens and writes the structured fields straight into the CRM. A rep's day ends when the chat does.
The chore that comes after the actual work
A sales or support conversation that goes well still leaves one more job. Someone has to open the CRM and type up what was actually said, before the details blur into the next five conversations of the day. Teams that measure this usually find reps lose a meaningful chunk of their working day to this kind of after-the-fact entry. It was already spent once, talking to the customer, and now it gets spent again, writing it down.
Accuracy is the second cost. Notes typed from memory an hour after the call drop detail, and a rep juggling several chats at once sometimes just does not get to it. That leaves a CRM record with a name and a date and nothing useful in between. A manager reviewing the pipeline later is working from whatever fraction of the conversation actually made it into a field.
Consistency is the third. Different reps log different things in different fields. A sales lead trying to build a report across the team ends up with data that was never captured the same way twice. Fine for lookup, far less useful for analysis.
What the agent writes down, as it happens
The agent reads the conversation, live in Telegram, WhatsApp or web chat, or already logged. It extracts the fields your team actually uses: budget mentioned, objection raised, next step agreed, product discussed, whatever the CRM tracks. The field mapping is built with your team from your real CRM structure, not a generic contact-form guess.
As the conversation progresses, the agent writes the extracted fields into the CRM record directly, close to real time instead of waiting for the chat to end. If a field is ambiguous, say the customer mentioned two possible budgets, the agent flags it with a confidence marker instead of picking one silently. A rep confirms it with one glance rather than re-reading the whole thread.
The agent never overwrites a field a rep already filled in by hand. It only adds what is missing or flags a conflict for a human to resolve. A team running the same conversation across several channels gets the same extraction logic on each one. The CRM ends up with the same fields filled the same way, no matter which channel the customer picked.
Where the rep still owns the judgment
Any field tied to a commitment, a quoted price, a contractual term, is written as detected but flagged for a rep to confirm before it counts as final. Reps keep full edit control over every record the agent touches, and a rep’s own manual entry always wins over what the agent extracted. The agent removes the typing, not the judgment.
How a wrong entry gets caught
Every field written is logged against the message it came from, so a rep or manager can trace any entry back to its source in seconds. Low-confidence extractions are flagged rather than written silently. The agent runs in a shadow mode against real conversations for a few days before it is allowed to write live. A kill switch turns off live writes instantly if the field mapping needs rework.
Price and timeline
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| Single automation | from $600 | One CRM, one channel, fixed field map | 4 to 8 days |
| Department package | from $2,500 | CRM data entry plus call summaries and pipeline hygiene alerts | 2 to 4 weeks |
Running cost is typically $20 to $60 a month in model usage, depending on conversation volume.
Related
Pair this with call and meeting summaries for the voice side of the same problem. Sales pipeline hygiene alerts keep a CRM current and flag it when something stalls. See the full package breakdown on the AI agents service page. For how this worked at real lead volume, see the real estate lead routing case study and the seven-channel sales agent case study.
Tired of typing up the same conversation twice? Get in touch and we will map your CRM’s fields against a real chat first.
Tired of doing this by hand? We can take the whole routine off your team, not only this step: Routine takeover, from $400 →
FAQ
How much does CRM data entry automation cost?
From $600 for one CRM and one channel with a fixed field map, live in 4 to 8 days. Multiple channels feeding the same CRM, or CRMs with heavily customized fields, usually run $1,200 to $2,800.
How long before it is live?
4 to 8 days once we have your CRM's field structure and a sample of real conversations to test against. Most of the time goes into getting the field mapping right, not the plumbing.
Which tools does it connect to?
amoCRM, HubSpot, KeyCRM and Pipedrive, plus most CRMs with an API. On the chat side: Telegram, WhatsApp, Instagram Direct and your site's chat widget.
What if the AI gets it wrong / is wrong?
Anything the agent is not confident about is flagged for a rep to confirm instead of written silently. The agent never overwrites a field a person already filled in by hand. Every write is logged with the message it came from, so a wrong entry is easy to trace and fix.
Is conversation data safe?
The agent reads conversations it already has access to for the sales or support work itself. It writes only structured fields, not raw transcripts, into your CRM unless you ask for both. Every write is logged for audit.