AI Live Chat for Customer Support
AI live chat is a website conversation channel where AI answers visitors’ questions in real time, using information your business provides. For customer support, it can answer common questions and route requests it cannot resolve to a person. If your team keeps answering the same shipping, returns, and product questions, the important choice is how the chat handles uncertainty and gets a person involved.
I can help with the return policy. If your question depends on an order or needs a person, I can pass it to the support team.
A practical guide
AI live chat for customer support: what it is and who it suits
AI live chat is a customer-support channel for real-time text conversations with website visitors. Unlike a general-purpose AI assistant, a support tool is set up to answer from business information; unlike a scripted widget, it can draft conversational answers rather than offering only fixed choices. It also differs from staffed live chat: a person does not need to type every first reply. Routine policy and product questions may be suitable for automation, while unusual, sensitive, or account-specific requests still need a clear route to a person.
This can suit an online store with repeated questions about delivery, returns, sizing, or product details, and a support team that needs an AI front line without losing human ownership. If you are asking which AI has the best live chat, compare how each tool uses your business information and handles questions it cannot answer; there is no universal best-tool decision. The right fit depends on what customers ask, which systems the team needs to use, how handoffs work, and how the vendor charges.
Why AI live chat needs a source, a handoff, and a real support inbox
Quick replies can make it easier for visitors to get help while browsing, but speed alone does not show whether an answer is safe to send. A bot that invents a refund promise or treats an old policy as current can create more work for the team. Start with the material the AI is allowed to use, and decide what should happen when that material does not answer the question.
A support-ready workflow pairs answers with human ownership. If you are looking for an AI live chat bot for a business website, assess both the answer quality and how conversations reach the team. For example, a return-window question may be answered from the published returns policy. A request to change an order is different: it may require current order data, permission, and a recorded change in the order system. Do not assume that an AI chat tool can look up or alter orders just because it can discuss store policies. List the actions your team actually needs, and verify them separately.
A shared inbox matters because unanswered or uncertain questions still need a destination. Unlike a free AI chat website for general conversation, business live chat needs a clear path from an automated reply to accountable support. When comparing tools, check what details are collected before handoff, whether a teammate can take over a live conversation, and how the team keeps track of who needs to reply. For an evaluation, use a consistent sample of recent support questions. Review grounded answers, incorrect answers, and handoffs separately, then consider the total cost at your expected usage rather than comparing headline plan prices alone.
How a support-ready AI chat workflow works
Evaluate the path from a visitor’s question to either a source-backed response or a useful human handoff.
- 1
Add the knowledge the AI may use
Choose current customer-facing material such as delivery and returns policies, product information, and answers to common questions. Keep policy wording clear, and check that the content reflects what your team will honour.
The answer has a business-specific source to draw from.
Retrieve
Find relevant passages for the question
A support AI needs to connect the visitor’s request to information in the approved knowledge, rather than answer from general knowledge alone. For a return question, check that the response uses the right policy rather than a similar product page or an outdated instruction.
The drafted answer should reflect the return terms in the selected policy.
Returns policyHand off
Give the team the conversation to resolve
A request that needs a person should create a ticket in the support inbox. Check the information collected before the handoff, then have a teammate take over and answer in context. A policy question can often be answered from knowledge; an order change should go to a person unless the required data access and action are verified.
The support team can handle the request that the AI did not resolve.
Why momo suits teams that need a human backstop
The practical fit is a knowledge-based first reply with an inbox for questions that need a teammate.
Answers draw on your own content
Add a website crawl, PDFs, Word files, plain text, or Q&A pairs so the AI can retrieve relevant knowledge, draft an answer, and check it against those sources.
Confident answers go out with citations.
Uncertainty has a defined next step
When the AI is not confident, it tells the visitor it is not sure and opens a ticket for the team instead of presenting a guess as a supported answer.
The team can pick up questions the knowledge does not settle.
The inbox is part of every plan
Teammates can take over any conversation live, and the handoff collects the details your business chooses before the request reaches a human.
Unanswered conversations have a place for human follow-up.
Compare plans by usage and team needs
Plans have a flat fee with an included number of AI conversations, not a per-resolution charge or credit packs; yearly billing is eleven times the monthly price.
Included: The helpdesk inbox is included, and teammates can take over conversations live. · Paid plans allow up to 25 AI replies in a conversation; Free allows up to 10. · The AI model is chosen through OpenRouter; self-hosting uses your own key.
Free
Try momo with real visitors.
€0€0 forever
- 30 AI conversations, one-time
- 1 agent, 1 team member
- Website widget
- Helpdesk inbox
- Basic analytics
- 2 MB of knowledge, 10 sources
Starter
One agent, steady traffic.
€29€27per month
- 500 AI conversations / month
- 1 agent, 2 team members
- Website widget and email
- Helpdesk inbox and Help Center
- Basic analytics
- No momo badge
- 20 MB of knowledge, 50 sources
Growth
More agents, more channels.
€129€118per month
- 2,000 AI conversations / month
- 3 agents, 5 team members
- Slack, Shopify, WhatsApp, Instagram, Messenger
- API, Zapier and webhooks
- Advanced analytics
- 100 MB of knowledge, 200 sources
Scale
High volume, every channel.
€399€366per month
- 6,000 AI conversations / month
- 10 agents, 10 team members
- Every channel
- API, Zapier and webhooks
- Advanced analytics
- 500 MB of knowledge, 1,000 sources
Need more resources or custom solutions? Contact us for Enterprise plans
Frequently asked questions
Use these checks to distinguish support chat from general-purpose AI and set expectations before launch.
How is AI live chat different from a general-purpose AI chatbot?
AI live chat is a support channel for real-time conversations with visitors, configured around a business’s customer information and support workflow. A general-purpose chatbot may answer broad questions, while a support setup should make clear what knowledge it uses and how a request reaches the support team when it cannot answer.
Can an AI live chat agent answer from my store’s website and documents?
With momo, knowledge can come from a website crawl, PDFs, Word files, plain text, and Q&A pairs. It retrieves relevant passages, drafts an answer, and checks the draft against those sources; confident answers go out with citations.
What should an AI agent do when it cannot find a reliable answer?
It should not turn uncertainty into a confident-sounding guess. momo tells the visitor it is not sure and opens a ticket for the team, where a teammate can take over the conversation.
Can AI live chat look up or change a customer’s order?
Do not assume that a tool can access or change orders just because it can answer questions about store policies. Shopify is in preview for momo, and no Shopify order lookup or order action is being claimed here. Verify the exact data access, permissions, and actions your workflow requires before relying on them.
How should I compare AI chat pricing when vendors charge by different usage units?
Compare the billing unit, what counts as usage, included volume, and what happens when an allowance is reached. A conversation, message, and resolution are different units, so use your own expected support volume to estimate cost rather than comparing plan prices by themselves.
How can I test an AI live chat tool before putting it on my store?
Use a consistent set of real support questions, including policy questions and requests that need a person. Review answers against their cited content, test what happens when knowledge is missing, and check the handoff details and team inbox. Keep the current support process in place while you assess whether the new workflow is ready.
Start free and test the support flow
Add current policies and product knowledge, then review cited answers, uncertainty responses, ticket details, and human takeover before customers rely on the chat.