AI Chatbot Development for Business

Your customers don't wait. They don't repeat themselves. And they won't navigate a phone tree at 11 PM. We build AI chatbots that typically handle 60–80% of conversations without human escalation — accurately, instantly, 24/7.


AI chatbot development uses hybrid architecture: deterministic rules handle compliance-critical paths while the LLM layer manages natural conversation and complex queries.


We combine two AI approaches in one system. Deterministic rules handle the scenarios where accuracy is non-negotiable — pricing, compliance, personal data. The LLM layer handles everything else: understanding intent, maintaining conversation context, and responding naturally across languages. Your customer gets a precise answer and a natural conversation in the same chat.

The system connects to your CRM, knowledge base, and internal databases through APIs. Responses are grounded in your actual data through retrieval-augmented generation — reducing hallucination and keeping answers relevant to your business.

What Your AI Chatbot Delivers

Hybrid Architecture

We build chatbots that combine rule-based precision with LLM flexibility — so critical answers are always accurate and free conversation stays natural.

System Integration

We connect your chatbot to CRM, ERP, helpdesk, and databases via API. Salesforce and other — if it has an API, we integrate.

Multi-Language Support

One chatbot, multiple languages. We've deployed YandexGPT for Russian and GPT-4o for English in a single system.

Your Code, Your Data

No vendor lock-in. You own the code, the data, and the infrastructure. We build on open standards — switch providers anytime.

Our AI Chatbot Development Process

1
Discovery
— 1 week

We analyze your support data, map conversation patterns, and define what the bot handles vs what stays with humans. We deliver a clear architecture recommendation.

2
MVP Development
— 4–8 weeks

Working chatbot with core conversation flows, system integrations, and quality guardrails. You test with real users before we go further.

3
Iteration & Launch
— 2–4 weeks

We refine conversation logic based on real user feedback, expand conversation coverage, and improve response accuracy. The bot goes live when it's ready.

4
Ongoing Support

Conversation monitoring, model updates, and scenario expansion as your use cases grow. 20–30% of build cost annually.

Proven in Production

Royal Finance: Hybrid AI chatbot handling 30+ loan products across 2 languages. Deterministic rules for compliance-critical product matching, LLM for natural conversation. Built with Django + YandexGPT/GPT-4o.

Read the full case study →

Frequently Asked Questions

Do I need a custom chatbot, or will a SaaS platform work?

Depends on your volume, complexity, and integration needs. If you have fewer than 500 conversations per month and standard questions, a platform is probably fine. Beyond that — especially if you need CRM integration, multi-language support, or compliance-safe routing — custom development often pays for itself within a year. We wrote a detailed build vs buy comparison to help you decide.

What do you need from us to start?

Access to your support data (ticket logs, chat transcripts), product documentation, and a point of contact who knows your customer questions. We handle the rest — architecture, development, testing, deployment.

How quickly can you deliver an MVP?

4–8 weeks for a working chatbot with core scenarios and integrations. Simple FAQ bots can be faster. Enterprise multi-channel solutions take 10–16 weeks.

What determines the cost?

Three factors: conversation complexity (simple FAQ vs multi-step workflows), number of system integrations, and language requirements. Projects range from $3,000 for a simple FAQ bot to $20,000+ for enterprise-grade solutions. Every project starts with a free consultation and a fixed estimate.

Have you done this for businesses like mine?

We've built chatbots for financial services (Royal Finance — 30+ loan products), and our architecture handles any industry where accurate, context-aware conversation matters. The hybrid approach — combining rules and LLM — works especially well in regulated industries and complex product catalogs.

How do you prevent the bot from giving wrong answers?

Three layers: system prompts that define the bot's boundaries, RAG (retrieval-augmented generation) that grounds responses in your actual data, and deterministic routing for questions where LLM generation isn't acceptable. Your business data stays on your infrastructure by default. When cloud models like GPT-4o are used, we route through enterprise APIs with data processing agreements — your data is never used for model training.

Pricing

Tier Investment Timeline
FAQ bot with standard integrations $3,000–$8,000 4–6 weeks
Hybrid bot with CRM integration $8,000–$20,000 6–10 weeks
Enterprise multi-channel solution $20,000+ 10–16 weeks

Annual maintenance: 20–30% of build cost. Includes monitoring, model updates, and conversation flow expansion.

Every AI chatbot development project starts with a free consultation and a fixed estimate — no commitment.

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