One AI for calls and chats: why combine them
· Updated
What Leksta offers. Call speech analytics works and connects in one step. AI chats and the voice bot are soon: get demo access and test them for your business.
It makes sense to combine calls and chats in one AI because each customer is one person with several channels. In Leksta the voice bot and the chatbot answer from one knowledge base and work in one console, so customers get the same answers on the phone and in messengers, agents see the whole history, and managers see the full picture without stitching together reports from different systems.
Below we look at what breaks when the tools live apart, what combining them gives you and how AI and people share the work. Product overviews are on the AI calls and chats pages, and you can test chats and the bot with demo access.
Two systems, two sets of answers
A typical picture: a company has a phone menu or bot plus a separate Telegram chatbot set up by another vendor. Each was trained separately. A couple of months later the rules change: new opening hours, a new price, a new service. One bot gets updated, the other is forgotten.
The customer calls and hears one thing, writes in a messenger and reads another. Trust drops faster than it would from an honest "I don't know, let me connect you to a manager".
The second problem is history. The chat agent has no view of yesterday's call and what was agreed. The customer repeats everything.
What combining gives you
| Separate bots | One AI for calls and chats | |
|---|---|---|
| Knowledge base | Two copies, updated separately | One; a rule is updated once |
| Console | Two systems, two logins | Calls and chats in neighboring sections |
| Customer history | Split across channels | Calls and messages side by side |
| Analytics | Combined by hand | One view of all contacts |
| Handoff to a person | Different logic in each bot | One set of rules |
Start with calls: speech analytics already transcribes recordings, scores them against your checklist and shows the result in the console. Chats and the bot plug into the same console, and you can test them with demo access.
One knowledge base
You upload documents once — policies, terms, answers to frequent questions. The voice bot answers from them on calls, and in chats the AI drafts a reply with a link to the source. If there is no supporting document, the draft is flagged as unsupported, so the agent can see the answer needs checking.
One console
The Chats section sits next to Calls. Managers do not switch between systems, and agents work in one window with three panes: the conversation list, the conversation and the customer card with history. The Calls section with the log and analytics already works for speech analytics customers.
One customer history
Customers are matched by phone number. The call page shows chats with that contact, and the chat shows data from the customer card. Conversation outcomes go to the CRM — for calls this works today as part of speech analytics.
One set of handoff rules
Trigger words, working hours and escalation rules are set once and mean the same thing to the whole team. An agent who handles calls today and chats tomorrow works with the same logic in the same interface.
How AI and people share the work
Combining does not mean the AI answers everywhere on its own. The roles differ by channel:
- On calls, the voice bot handles routine conversations, answers from the knowledge base and hands complex cases to an agent according to your rules.
- In chats, the bot replies to the first message according to rules set by an administrator: working hours and words that send the conversation straight to a person. After that, the AI suggests a draft reply to the agent, and the agent sends it.
This split keeps written answers accurate: a person checks the text the customer keeps.
Status in Leksta
| Area | Status |
|---|---|
| Call speech analytics (your PBX or SIP trunk) | Available |
| AI chats: website widget, Telegram, Viber, Max | Soon, demo access by request |
| AI chats: Instagram, WhatsApp, Messenger | Soon, connected after Meta reviews our app |
| Voice bot | Soon, demo access by request |
The AI identifies itself
A principle for every channel: on calls and in chats, customers know they are talking to an AI. The voice bot says so at the start of the conversation. We think this is right: it keeps trust and avoids the awkward moment when a customer figures it out on their own.
What managers see
- Today: a call log with AI scores against your checklist — more in quality control for 100% of calls — and Telegram alerts about problem calls.
- With AI chats: chat analytics, such as time to first reply, reply rate and escalations to people.
An example: one customer, two channels
A guest at a country resort writes in Telegram in the evening asking about early check-in. The bot replies to the first message according to the rules: thanks the guest and asks for the dates. In the morning the administrator opens Chats, sees a draft reply the AI prepared from the check-in policy, checks it and sends it. Later that day the same guest calls to ask about parking, and the voice bot answers from the same knowledge base. When the guest asks to speak to a person, the administrator sees both the call transcript and yesterday's chat. Nobody asks the guest to repeat anything.
With two separate systems the same story would look different: the chat in one window, the call in another, the check-in policy in two versions.
Where to start today
- Connect speech analytics. It works on the recordings from your PBX and immediately shows what customers ask about. More on the speech analytics page.
- Build one knowledge base. Take the answers your phone and chat agents already use and merge them into shared documents: chats and the voice bot work from this base right away.
- Agree on handoff rules. The same trigger words and working hours for every channel.
- Get demo access. Want to test AI chats and the voice bot for your business? Get demo access.
When one module is enough
If you have one channel — say, only inbound calls to reception — start with one module. Combining pays off when customers write and call at the same time and you already see answers drifting apart.
Terms from this post are in the glossary.
FAQ
Why combine a voice bot and a chatbot?
So customers get the same answers in every channel and agents see the whole history. One knowledge base is updated once and works in voice and chats.
How do I connect a chatbot and a voice bot to one knowledge base?
Upload your company documents once — policies, terms, answers to frequent questions. The Leksta bot and chatbot answer from this base, and speech analytics already shows what customers ask about. Get demo access and test it on your scenarios.
Which messengers can I connect to AI chats?
The website widget, Telegram, Viber and Max. Instagram, WhatsApp and Messenger connect after Meta reviews our app.
Does the AI reply to customers in chats on its own?
The bot replies to the first message according to administrator rules. After that, the AI suggests a draft and a person sends it.
Does the agent see the customer's calls from the chat?
Yes: customers are matched by phone number, and the card shows calls and chats with that contact.
Do I need to train the bot separately for each channel?
No. There is one knowledge base: a document uploaded once is used on calls and in chats.