Support that can find the answer

Give customers an answer before they need to open a ticket.

A customer service chatbot uses your help content and connected systems to answer routine questions, track orders, handle simple requests, and send the hard cases to the right person.

Demo preview

Support chatbot

See the workflow in action

Placeholder link ↗
Where it fits

For support teams dealing with repeat questions, long first-response times, or a growing queue that keeps pulling experienced staff away from complex cases.

Interactive workflow

Follow one request through the system.

Pick a step to see what happens and where your team stays in control.

Step 01

A customer asks

The conversation begins on your site, app, or support channel.

System: Web / app
What it handles

The work your team should not have to repeat.

Product and policy questions
Order-status and account enquiries
Returns and simple service requests
Knowledge-base answers with sources
Ticket triage and agent handoff
Conversation tagging for support review
Integrations

It needs to work with the tools your team already opens every day.

I

Intercom

Z

Zendesk

S

Shopify

H

HubSpot

#

Slack

Implementation

Start with a business problem, not a feature list.

01

Choose the first questions to solve

We begin with a contained set of high-volume requests instead of asking a chatbot to know everything on day one.

02

Prepare the source of truth

Your approved content, policies, and system data determine what the assistant can confidently answer.

03

Measure before expanding

Resolution rate, escalations, and customer feedback show where the system is useful and where it needs work.

ROI estimator

Estimate the time in your support queue

Answer three quick questions. You can tune every assumption after you see the first estimate.

McKinsey estimates 30–45% productivity value in customer care. The default below uses 30%, not a guaranteed result.

Read the McKinsey customer-care benchmark source ↗
Questions people ask before building

FAQ

It should be built to use approved sources, state uncertainty, and hand off when it cannot find a reliable answer.

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