I build custom AI chatbots that handle customer support, drive sales, and automate internal workflows. Built with OpenAI, LangChain, and Django -- designed to solve real business problems.
Most businesses lose customers not because of a bad product, but because of slow response times and lack of personalization. An AI chatbot changes that fundamentally. It responds instantly, works around the clock, and learns from every conversation to deliver better results over time.
I am Kirill Strelnikov, a freelance Python/Django developer and AI engineer based in Barcelona. Over the past several years I have built AI-powered chatbots for e-commerce stores, SaaS platforms, and service businesses across Europe. My approach is straightforward: understand the business problem first, then choose the right technology to solve it.
Unlike generic chatbot builders that give you a drag-and-drop interface with limited capabilities, I build custom solutions from the ground up. Every chatbot I deliver is tailored to your specific business logic, integrated with your existing systems, and designed to scale as your needs grow. Whether you need a support bot that deflects tickets, a sales assistant that recommends products, or an internal tool that helps your team work faster -- I handle the entire process from architecture to deployment.
The result is not a toy demo. It is a production-ready system backed by a proper backend, a real database, and clean API architecture that your team can maintain and extend. I work with businesses worldwide, and communication happens via Telegram, WhatsApp, or email -- whatever works best for you.
Every business has different needs. Here are the three main categories of chatbots I develop, each solving a distinct set of problems.
Automated first-line support that handles FAQ, order tracking, returns, and common inquiries. Reduces ticket volume by 50-70% and responds in seconds instead of hours. Seamless handoff to human agents for complex cases. Integrates with your help desk, CRM, and knowledge base.
AI-powered shopping assistants that understand customer preferences, recommend products from your catalog, and guide users toward purchase. Uses conversation history and product data to deliver personalized suggestions. Proven to increase conversion rates and average order value.
Tools for your team: document search, report generation, data extraction, onboarding assistants, and workflow automation. Telegram bots for internal communication and task management. Built to save hours of manual work every week.
Each bot type can be deployed as a web widget, a Telegram bot, a WhatsApp integration, or a standalone API that connects to any frontend. I also build multi-channel solutions that work across several platforms simultaneously.
I use a proven stack that balances cutting-edge AI capabilities with production-grade reliability. Every component is chosen for a specific reason -- no unnecessary complexity, no vendor lock-in.
AI layer: OpenAI API (GPT-4, GPT-4o) serves as the core language model. LangChain handles conversation chains, memory management, retrieval-augmented generation (RAG), and tool-calling agents. For specialized use cases I implement custom prompt engineering, function calling, and fine-tuned system instructions.
Backend: Python and Django provide a robust, scalable foundation. Django REST Framework exposes clean APIs for the chatbot interface. PostgreSQL stores conversation history, user profiles, and product catalogs. Redis handles caching and session management for fast response times.
Infrastructure: Celery manages background tasks like async AI processing and webhook handling. Docker ensures consistent deployments. Nginx serves as a reverse proxy. The entire stack runs on Linux VPS with CI/CD pipelines for smooth updates.
This is the same stack I use for all my development projects. It is battle-tested across 15+ commercial applications and scales from small bots to enterprise-grade systems.
Every project follows a structured process that minimizes risk and delivers results on schedule. Here is what to expect when we work together.
We start with a free consultation where I learn about your business, your customers, and the specific problem the chatbot needs to solve. I ask detailed questions about your existing systems, data sources, and integration requirements. This phase typically takes 2-3 days and ends with a clear project scope, timeline, and fixed-price estimate.
I design the system architecture: data models, API contracts, conversation flows, and the AI prompt strategy. For chatbots using RAG (retrieval-augmented generation), I set up the knowledge base indexing. You review and approve the architecture before development begins.
I build in short sprints with regular demos. You see working software every week, test the chatbot with real conversations, and provide feedback that shapes the next iteration. This approach eliminates surprises and keeps the project aligned with your expectations.
Comprehensive testing with real-world conversation scenarios. I optimize prompt quality, response accuracy, latency, and edge case handling. Load testing ensures the bot handles peak traffic without degradation.
Server deployment, monitoring setup, and go-live. I provide documentation and training for your team. After launch, I offer ongoing support packages for prompt tuning, feature additions, and performance optimization based on real usage data.
Here are two real projects that demonstrate how I approach AI chatbot development. Both went from idea to production and delivered measurable business results.
An e-commerce store was losing customers due to slow response times and lack of personalization. I built a Django system with an OpenAI-powered chatbot that provides personalized product recommendations based on the catalog and conversation history. The bot generates automatic product descriptions, handles intelligent session management, and replaced first-line customer support entirely. It became the primary sales tool -- no human manager required for initial customer interaction. Response time dropped from hours to seconds, and online conversion increased measurably.
Users were juggling dozens of AI services for text, image, and video generation. I created a Telegram bot that unifies multiple AI models in a single conversational interface. The system includes a credit-based billing model, an admin panel for managing models and users, and a scalable architecture built with Celery task queues and Redis. The project reached monetization within the first month of launch and grew to 500 paying users within three months.
These projects share a common pattern: a well-defined business problem, a focused AI solution, and a production-grade backend that runs reliably in the real world. You can explore more of my work on the main portfolio page or read technical breakdowns on my blog.
AI chatbot development is not for everyone. Here are the types of businesses and situations where a custom chatbot delivers the highest ROI:
If your business handles repetitive inquiries, needs faster response times, or wants to offer personalized experiences at scale, a custom AI chatbot is worth exploring. Book a free consultation to discuss your specific case.
Transparent pricing based on project complexity. All prices include development, deployment, documentation, and 30 days of post-launch support. No hidden fees. Final cost is confirmed after the discovery phase.
Need something between tiers or a completely custom scope? Get in touch and I will put together a tailored proposal within 24 hours.
Tell me about your business challenge. I will propose a solution, estimate the timeline, and give you a fixed price -- all within 24 hours. Free initial consultation, no commitment.
Get in touch