Communication automation
in messengers

Build AI bots from rules and scenarios. Use AI for complex questions and knowledge-base answers

0

Conversations automated

0 second

Customer response speed

0 %

Of requests Lia closes without an agent

x0,0

Reduction in support payroll

Lia vs. other solutions

Human

  • Adapts on the fly — but holds a limited number of parallel conversations
  • Understands everything — depends on knowledge and mood
  • Most expensive resource; scaling means hiring

Lia

  • Handles most requests instantly, 24/7
  • Reads the customer accurately, solves typical and complex cases via AI and your knowledge base
  • Cuts payroll 2.5×, scales to any volume

Scripted bot

  • Answers only rigid, pre-defined questions
  • Misses nuance, useless off-script
  • Cheap for trivial tasks, rigid to change

Platform
components

With an intuitive builder and powerful AI, you'll steer every conversation and resolve customer questions with precision

Conversation-flow builder

Compose support flows in a drag-and-drop builder. Add NLU and LLM, configure routing, run JS code.

Drag-and-drop scenario builder: intent triggers, text snippets, actions, reactions

Typical requests — in one second

NLU recognizes customer intents and entities — answers typical requests in a second, without expensive LLMs. Models hold 500 RPS and don't need retraining.

List of intents with training phrases and variation counts

Emotion, context, and intent — precisely

LLM handles the second line: complex questions, off-script wording, edge cases — answers come out sharper.

LLM block configuration: model, prompt, temperature, timeout

Transparent conversation tracing

Tracing follows the full path of a message through the system. You see which scenario blocks fired and why.

Conversation tracing: chat, scenario, entities, facts, request logs

Answers from your knowledge base

RAG answers complex questions against your documents. Entities and parameters are extracted from the conversation on the fly.

Deploy an AI teammate

Want to automate communication to the maximum?

AI consultant

Consults customers on products and services 24/7. Reads the request, picks the solution, walks people through the funnel.

AI sales rep

Works inbound leads: qualifies, runs presentations, helps close deals.

AI receptionist

Books appointments, confirms reservations, sends reminders — takes load off your staff.

76% more effective than a human

Our AI teammates outperform traditional staff on key metrics — delivering unprecedented efficiency and growth for your business

01 — 05

Payroll cut 2.5×

An AI teammate costs less than a human — payroll drops measurably.

02 — 05

Data access and seamless integration

Plugs into your CRM and knowledge bases — fresh info, action without delay.

03 — 05

24/7 — no breaks, no churn

Works round the clock: no breaks, fatigue, burnout, or turnover.

04 — 05

Context, emotion, and the catalog

Knows the product, reads context and slang, finds catalog items fast — answers stay on point.

05 — 05

Thousands of dialogues in parallel

Handles hundreds of thousands of concurrent requests — no lead slips.

Estimate the savings from automation

from ₽3.5 per dialogue

Expected annual savings

What industry are you in?

Pick a department

How it works

01

Implementation and launch

We automate your processes transparently, stage by stage. From planning through configuration — progress stays under your control. The result fits your specific business needs.

Stage goal

Automation level no lower than 50%

02

Growth and optimization

Service-hour packages are a tool for project growth. The Lia team adapts scenarios to new tasks and lifts answer accuracy.

Stage goal

Maximum automation share and decision precision

03

Reliability and SLA

We own system stability. The SLA fixes 99% uptime.

Terms

Flexible support tiers for your scale

Platform capabilities

01 — 11

Admin console

One workspace to manage the platform and monitor processes.

02 — 11

Conversation routing

Routes the incoming request to the right line or support team.

03 — 11

Tags

Classify conversations and messages for analysis and sorting in external systems.

04 — 11

Event analytics

Every message, intent, and entity from customer conversations lands in ClickHouse — build reports in any BI, find scenario bottlenecks, decide on data.

05 — 11

Conversation tracing

Shows the customer journey and bot decisions across scenarios and conversation history.

06 — 11

Alert scenarios

Trigger scenarios on critical events or external-system failures.

07 — 11

NPS surveys

Collect customer scores during or after the conversation.

08 — 11

NLU + RAG + LLM

Reads the request, finds the info, generates a precise answer.

09 — 11

Reporting and analytics

Automation and support-quality metrics on one panel.

10 — 11

Scalability

The platform handles any request volume and grows with the business.

11 — 11

Reliability and uptime

99% uptime per SLA — customer support 24/7.

Start in your usual channel

Run Lia where your customers and agents already communicate. We handle seamless integration with leading communication platforms

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

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

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

Daria Churakova

Deputy Head of Support

"

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

Ruslan Mamrukov

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

Vlad Pak

Head of User Support

80

Of requests automated

%
10

Saved per request

RUB
80

Saved per request

%
80

Of requests automated

%
63

Of requests automated

%
x2.5

Saved per request

47

Faster issue resolution

%
x5

Faster issue resolution

59

Of requests closed by the bot

%
x3

Saved per request

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.

Questions left?

Book a free demo and see how Lia helps solve your business challenges.