Deep dive · Support

AI Customer Support Automation

FollowAI builds an AI support agent that answers from approved company information, connects to your support tools, and passes exceptions to a person with the conversation intact. Account access and customer-facing actions follow agreed permissions.

All solutions Chat on WhatsApp

Human approval built inOwnership definedWritten build scope

Operating direction

Grounded answersRoutine support uses approved company knowledge

The exact scope, controls, providers, and operating costs are defined before development begins.

Define the project

Build an AI customer support agent with a reliable human handoff

Start with recurring questions your team can answer from approved policies or product information. Add permitted customer lookups and actions when they are useful. Unclear requests, missing evidence, and sensitive exceptions go to your team with their context preserved.

An approved knowledge source and agreed answer boundaries
Connections to the chosen helpdesk, channels, and permitted account data
Human escalation, quality checks, monitoring, and staff training

Does AI support replace our helpdesk or support team?

It can work alongside the existing helpdesk. Staff remain responsible for exceptions, policy decisions, source updates, and cases that need a person. We agree where the agent answers, drafts, routes, or acts.

How much does AI customer support automation cost?

Budget for setup, knowledge preparation, integrations, vendor seats or usage, hosting, and ongoing review. Conversation volume and permitted actions affect the recurring cost. We scope these separately instead of treating a chatbot subscription as the complete implementation budget.

What happens when the agent cannot answer?

The system should explain the next step and transfer the case with the conversation and relevant sources. The team defines available hours, queue ownership, and fallback behaviour before launch.

Seamlessly integrates with

HubSpotHubSpotCRM records, deal stages, and approval queues
SalesforceSalesforceCRM records and pipeline sync for larger teams
SlackSlackWhere the system asks a human to approve or edit
GmailGmailInbound capture and outbound drafts held for review
QuickBooksQuickBooksWhere processed invoices land, already coded
WhatsAppWhatsAppBusiness API for customer conversations
n8nn8nThe workflow layer you own outright
AlbatoAlbatoUniversal MCP access to the long tail of apps
MakeMakeAlternative workflow runtime where it fits better
+ your stack

The workflow

Every step visible. The important decision stays human

The system moves routine work forward and stops at the exact moment judgement, policy, or customer trust requires a person.

01
Arrive
Chat, email, or WhatsApp — one queue regardless of where it came from.
02
Understand
Matched against your documentation, not general internet knowledge.
03
Resolve
Routine requests answered with the source attached to the answer.
Handover
You decide
Anything unclear, angry, or high value goes to a person with the full thread.
05
Log
Outcome written back, so next month you can see what people actually ask.

Slack · #support-reviewDraft

To: Ticket #4192 · marcus.webb@fieldlinehvac.com
Subject: Refund request outside the 30-day window

Draft prepared. This one sits outside policy, so it has not been sent. Customer bought 41 days ago, first contacted support on day 12 about the same fault. Suggested reply offers a replacement unit rather than a refund, and cites the earlier ticket.

Written from

Policy: 30-day returns
Prior ticket #3907, day 12
Order value $1,240
Sentiment: frustrated

Waiting on a person

Before / after

The operating change in plain language

Now

Questions pile up overnight and land as a morning backlog
The same six answers retyped every week
Answers differ depending on who replied
No record of what customers keep asking about

With a system

Routine questions answered when they are asked
One current answer, sourced from your own docs
Hard cases reach a person with the full thread
A monthly view of what actually drives contact

What is delivered

A complete support workflow, ready to run

An agent grounded in your documentation, with sources on answers

Coverage across chat, email, and WhatsApp Business

A handover path that carries the whole conversation to a person

Escalation rules for value, sentiment, and policy exceptions

Answer coverage reporting, so gaps in your docs become visible

Vendor usage and ongoing operation defined before launch

Commercial frame

Scope, controls, and operating costs made visible

Grounded answersRoutine support uses approved company knowledge

Usage scopedModel and vendor costs are listed before launch

Defined stepsRepeating work moves inside explicit rules and approvals

Common questions

Ownership, accuracy, and the failure cases

Will the AI hallucinate?

It can, which is why nothing it writes reaches a customer unreviewed. Drafts are held for approval, answers are generated only from sources you supplied, and anything the system is unsure about is routed to a person instead of guessed at.

Do I own the workflows?

Yes. Everything is built inside your own n8n, Albato, or Make account, and the prompts and documentation are handed over with it. If we stop working together the system keeps running, and you can hand it to any other developer.

What stops it from promising something we do not offer?

It answers only from the documentation you supply, and refunds, discounts, and policy exceptions are configured as approval-required. Those replies are drafted and held, never sent automatically.

How is ongoing usage priced?

Model, hosting, automation, and channel costs depend on the selected providers and volume. We show those assumptions before launch and scope ongoing operation separately from the build.

Can it work outside English?

Yes, in the languages your documentation supports. Coverage is only as good as the source material, so the Diagnostic checks that before we promise a language.

Next step