Automate communication with your customers

With AI tools that understand customers and help your team do more

Conversations automated

0 second

Average response time

0 %

Of requests Lia closes without an agent

x0,0

Reduction in support payroll

When
we need to cut payroll

−80% of requests without an agent

Read case

01 — 05

When you need to cut support payroll

Lia closes up to 80% of requests without an agent. Support payroll drops by up to 2M ₽ a year — quality holds.

02 — 05

When customers won't wait

Lia answers in under a second, 24/7, no queue. CSAT and NPS climb, churn drops — customers get an answer, not a place in the queue.

03 — 05

When growth outpaces hiring

The platform holds 10,000 requests per minute. Seasonal peaks and step changes pass without rushed hires or temp onboarding.

04 — 05

When agents burn out on routine

Routine moves to the AI; agents take the complex cases. Burnout and churn fall, engagement climbs — strong specialists stay on the team.

05 — 05

When growth points hide inside requests

Sentiment analysis and tagging on 100% of conversations. Real customer pain, reactions to features, and growth points are visible — support runs as a product-insight engine.

Read case

Lia works in every vertical

Talk to customers in any vertical. Lia ships ready patterns for your industry — pick the closest case and adapt it to your processes.

Trusted by market leaders

In our first month with the Lia team we hit 51.2% coverage. A year later it grew to 78.61%, with intent-recognition error below 5%.

Katerina Kozina

Head of Quality Control

We set up smart routing by topic and country. We answer instantly — even questions like why we cook without gloves and don't include napkins :)

Aleksandr Shalamov

Support Chat Lead

Lia is a full-fledged member of the Localrent support team. Customers notice it, and the team feels meaningful relief on FAQs. Lia keeps us in touch with customers through the night so our specialists can recover.

Daria Churakova

Deputy Head of Support

Burnout from chat volume is down, and the team is more engaged in actually solving cases.

Ruslan Mamrukov

Head of User Support

Lia helps us stay close to our customers and always reach them in time. Response speed is critical in kick-sharing, and Lia clearly makes us faster.

Vlad Pak

Head of User Support

Of requests automated

Saved per request

RUB

Saved per request

Of requests automated

x2.5

Saved per request

Faster issue resolution

Of requests closed by the bot

Saved per request

How an AI teammate goes live

01 — 05

Create an AI agent from a template

Lia ships ready-built templates for every business area

02 — 05

Connect your data sources

Files in PDF, Word, HTML, JSON — or APIs from your CRM and knowledge bases.

03 — 05

Configure automation

Adjust the agent's logic to your scenarios — no code, in a visual builder

04 — 05

Connect channels

Chats, email, messengers, telephony — requests arrive where customers are

05 — 05

Ship and measure

Pull pilot metrics and refine scenarios before scale-up

Pull metrics and refine scenarios

How does integration work?

There are two integration points. First — the system you use to talk to customers (CRM or chat platform). Second — your internal services: CRM, admin panels, knowledge base.

Depending on your stack, Lia either connects directly to your CRM via API or plugs into your chat platform (e.g. Webim), which already receives messages from Telegram and WhatsApp. Nothing changes for the customer — they keep messaging in their usual channel.

Chat-platform integration is fully on us — no engineering effort required from your team.

Can Lia send outbound messages?

Yes — when paired with a webhook trigger. For example: by timer or on an event from your CRM.

What's the neural network built on?

The core is built on BERT (originally from Google), but that's only one piece — multiple tools work together at Lia's core. Python ties them together, letting us compose many blocks into a single system.

Where exactly are neural networks used?

Neural networks sit at the intelligence core of the Lia platform and process customer text in several places:

Request clustering: groups large volumes of similar requests by topic, helping you analyze them and surface the dominant queries.

Request classification (with LLMs): identifies the topic, intent, or category of every incoming request — for instant, correct routing.

Knowledge-base answer generation (LLM-powered): understands the customer question, finds the most relevant knowledge-base entry, and produces a precise, natural answer.

Which languages does Lia support?

We focus first on Russian. We can also enable: English, Portuguese, Spanish, Chinese, Dutch, French, German, Italian, Japanese, Turkish.

How does Lia handle typos?

Lia recognizes text well even when the request contains errors. We deliberately avoid spell-correction so we don't introduce extra changes into the user's message. Instead, Lia reads the semantic vector of the whole sentence — including typos. In practice this gives the best result.

Worth noting: when we cluster the corpus, frequent typos cluster too — which lets us identify meaning even more accurately despite imperfect spelling.

What's the maximum load?

Lia already handles tens of thousands of messages per minute, and the architecture scales to multiples of that — distributing load across nodes.

Automate communication with your customers