I integrate AI into your existing applications and workflows -- smart search, content generation, document processing, recommendations, and conversational AI. No rebuilds required.
Every business knows it should be using AI. But most companies struggle with the same question: where do we even start? The answer is not replacing everything with AI -- it is adding intelligence to the systems you already use.
AI integration means connecting models like GPT-4 or Claude to your existing application, CRM, helpdesk, or internal tools. Instead of switching to an entirely new platform, you enhance what you already have. Your support system starts suggesting answers. Your search becomes semantic. Your documents get processed automatically. Your product recommendations become personalized.
I am Kirill Strelnikov, a freelance Python/Django developer and AI engineer based in Barcelona. I have integrated AI into e-commerce platforms, SaaS products, customer support systems, and internal business tools. My approach is practical: I start with the use case that delivers the highest ROI, build a clean integration, and expand from there. All solutions are GDPR-compliant with EU hosting options.
AI integration goes far beyond chatbots. Here are the three main categories of AI features I add to existing business applications.
Conversational AI chatbots, personalized product recommendations, AI-powered search, content generation, dynamic FAQ systems, and smart onboarding flows that adapt to user behavior in real time.
Document processing and data extraction, automated report generation, internal knowledge base search with RAG, email classification and routing, meeting summarization, and code review assistance.
Lead scoring and qualification, invoice processing, email triage and auto-response, content moderation, data enrichment, anomaly detection, and intelligent workflow triggers based on natural language.
For dedicated chatbot projects, see my AI chatbot development service. For autonomous AI systems that plan and execute multi-step tasks, see AI agent development.
I select the right model and architecture for each use case. There is no one-size-fits-all in AI -- the best solution depends on your data, budget, latency requirements, and privacy constraints.
Model selection: I evaluate models based on quality, latency, cost, and privacy. For most business applications, GPT-4o or Claude deliver the best balance. For high-volume, cost-sensitive use cases, I optimize with smaller models or caching strategies that reduce API costs by 60-80%.
RAG (Retrieval-Augmented Generation): For AI that needs to know your specific data -- product catalogs, documentation, policies -- I build RAG systems using vector databases (pgvector, Pinecone, Chroma) that ground AI responses in your actual content.
Prompt engineering: I design and optimize prompts for accuracy, consistency, and safety. This includes system instructions, few-shot examples, output formatting, and guard rails that prevent hallucination and off-topic responses.
AI integration requires a careful, iterative approach. I follow a structured process that minimizes risk and delivers measurable results at each step.
I analyze your current systems, data, and workflows to identify the highest-ROI AI integration opportunities. We discuss your goals, constraints, and budget. This phase takes 2-3 days and ends with a clear recommendation and fixed-price estimate. Take the AI readiness assessment to see where you stand.
I select the right AI model, design the integration architecture, and define the API contracts between your existing system and the AI layer. For RAG systems, I plan the data indexing pipeline. You approve the architecture before development begins.
I build the AI integration as a modular service that connects to your application via API. You see working demos every week and can test with real data. Prompt engineering is iterative -- I refine based on real-world outputs.
Comprehensive testing with your production data. I evaluate accuracy, latency, edge cases, and cost. Prompt optimization reduces API spend while maintaining quality. Load testing ensures the integration handles peak traffic.
Production deployment with monitoring for quality, latency, and cost. I set up alerting for accuracy degradation and provide documentation for your team. Ongoing support packages available for continuous improvement.
Here are real projects that demonstrate how I integrate AI into production business systems.
Integrated OpenAI into a Django e-commerce platform to power personalized product recommendations based on catalog data and conversation history. The AI generates product descriptions automatically, handles intelligent session management, and replaced first-line customer support. Response time dropped from hours to seconds.
Built a Telegram bot that integrates multiple AI models (text, image, video generation) in a single conversational interface. The system routes requests to the optimal model, manages usage credits, and handles concurrent users through Celery task queues. Reached 500 paying users within three months of launch.
AI integration delivers the highest value for businesses that already have a working product or system and want to make it smarter. Here are the ideal use cases:
If your business has data and repetitive processes that could benefit from intelligence, AI integration is worth exploring. Book a free AI readiness assessment to discuss your specific case.
Transparent pricing based on integration complexity. All prices include development, prompt engineering, deployment, documentation, and post-launch support. Final cost confirmed after the discovery phase.
Need a custom scope? Get in touch and I will provide a tailored proposal within 24 hours.
Kirill Strelnikov is a freelance Python and Django developer based in Barcelona, Spain. He specializes in AI integration, building production-grade systems with OpenAI, Claude, LangChain, and RAG architectures. He has delivered over 15 commercial projects for clients across Europe, including AI-powered e-commerce platforms, multi-model AI systems, and intelligent automation tools.
His core tech stack includes Python, Django, PostgreSQL, Redis, Celery, Docker, OpenAI API, and LangChain. He works exclusively with fixed-price contracts. Communication in English, Spanish, and Russian.
Learn more on the about page or explore the full portfolio.
Tell Kirill about your business and the problem you want AI to solve. He will propose an integration plan, estimate the timeline, and give you a fixed price -- all within 24 hours. Free AI readiness assessment, no commitment.
Book a free AI consultation