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Branemind
Customer operations

WhatsApp AI agents for sales, support and collections

The short answer

A WhatsApp AI agent runs a business conversation end to end on the WhatsApp Business API: qualifying a lead, answering from your own content, taking an action in a backend system, and handing to a human at defined triggers. Branemind builds these with consent checks, policy guardrails and CRM-aware context.

WhatsApp is where the customer already is, and where nobody is staffed

Indian buyers open WhatsApp and expect an answer in seconds. Most businesses answer in hours, from a shared handset, with no record in the CRM. The usual fix is a keyword bot, which fails on the second message and trains customers to type 'agent' immediately.

What it costs today

  • Leads that go cold between the enquiry and the first reply
  • Conversations that never reach the CRM, so follow-up depends on memory
  • Support load made of the same twenty questions, answered by hand
  • Broadcast tooling used carelessly, risking template quality ratings

What we build, and where we stop

The second list matters as much as the first. A boundary that is agreed in writing before the build is the difference between a system your compliance team signs off and one they discover.

What we build

  • A conversational agent on the WhatsApp Business API, not an unofficial bridge
  • Retrieval over your own catalogue, pricing rules and policy documents
  • Actions in backend systems: create a lead, book a slot, raise a ticket, check an order
  • Human handoff with the full conversation context carried across
  • Template and broadcast hygiene, including opt-out handling
  • CRM writeback so every conversation is a record, not a screenshot

What we do not do

  • Message people who have not opted in
  • Answer from general world knowledge when your own content does not cover it
  • Quote a price or commit a date the backend system has not confirmed
  • Keep a customer in a loop. Unresolved conversations escalate rather than retry

How it works

  1. 01

    Establish consent and identity first

    Opt-in state and any existing customer record are resolved before the agent replies, so the conversation starts with context rather than a menu.

  2. 02

    Answer from your content, or say so

    Responses are retrieved from your catalogue and policies. If the retrieval is thin, the agent says it does not know and offers a human, which is a better outcome than a confident invention.

  3. 03

    Take the action, do not describe it

    Booking a slot, raising a ticket or checking an order happens through your APIs inside the conversation. The agent confirms only what the system returned.

  4. 04

    Hand off on defined triggers

    Escalation fires on explicit request, on a complaint or dispute signal, on repeated retrieval failure, and on any topic your policy reserves for a person.

  5. 05

    Write back

    Transcript, outcome, qualification fields and next action land in the CRM as the conversation closes.

What it connects to

  • WhatsApp Business API
  • CRM systems
  • Order, ticketing and booking backends
  • Payment links and invoicing
  • Catalogue and content sources
  • Analytics and event pipelines

What you need in place

We would rather tell you this before a proposal than during one.

  • A verified WhatsApp Business account and an approved template set
  • A documented opt-in mechanism and an opt-out path
  • Content that is current, since retrieval quality is bounded by it
  • A staffed escalation queue during your published hours

Controls, approvals and what happens when it fails

Consent enforced at send time

Opt-in state is checked in the send path. Opt-out is honoured immediately and permanently, across templates and sessions.

Grounded answers only

The agent answers from retrieved content. Low retrieval confidence routes to a human instead of to a plausible guess.

Action confirmation

Any commitment the agent makes, a slot, a price, a delivery date, comes from a system response, not from the model.

Template and rating hygiene

Broadcast volume, template quality and block rates are monitored, because a degraded rating is a business outage.

The proof

Case studyFintech · Lending·An Indian digital lender

Collections on WhatsApp, run end-to-end by an agent

Recovery calls nobody answers, replaced by a conversation people actually finish. BM Relay negotiates, takes the payment, and knows exactly when to stop.

Contact rate
94%
vs 31% on voice dialer
Promise-to-pay kept
+38%
Cost per recovery
−62%
Read how it was built

What we measure, and what we do not promise

What we measure
First response time, containment rate, escalation rate and reason, qualified leads created, and opt-out and block rate. The last one is a guardrail metric, not a vanity one.
What one engagement measured
The lender collections case study reports contact and recovery movement against a pre-agent baseline over its stated window. Read it for the controls as much as the numbers.
What to expect early
The first month is mostly content repair. Retrieval exposes every gap and contradiction in your existing policy and catalogue documents, which is uncomfortable and useful.

Questions we get asked

What can a WhatsApp AI agent actually automate?

Qualification, frequently repeated questions answered from your own content, and transactional actions your systems expose through an API: booking a slot, checking an order, raising a ticket, sending a payment link. What it should not automate is anything requiring discretion, such as a goodwill refund or a hardship arrangement.

How does human handoff work?

On a defined trigger the conversation moves to a staffed queue with the full transcript, the retrieved context and the customer record attached, so the person does not restart the conversation. The agent stops writing to that thread until the human releases it back.

Is this the official WhatsApp Business API?

Yes. We build on the official API. Unofficial bridges put the number at risk of being banned, which is not a trade worth making for a business channel.

Will it work in more than one language?

Yes, including code-switched messages, which are the norm in Indian WhatsApp threads. Quality depends on having your source content available in the languages you intend to answer in.

Next step

Scope one WhatsApp conversation flow

Tell us the flow. You see the readiness result before any email.