AI Integration Services: Add Intelligence to Your Business

I integrate AI into your existing applications and workflows -- smart search, content generation, document processing, recommendations, and conversational AI. No rebuilds required.

01 / OVERVIEW

Why Your Business Needs AI Integration

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.

02 / WHAT I BUILD

AI Integrations I Deliver

AI integration goes far beyond chatbots. Here are the three main categories of AI features I add to existing business applications.

AI for Customer-Facing Apps

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.

AI for Internal Operations

Document processing and data extraction, automated report generation, internal knowledge base search with RAG, email classification and routing, meeting summarization, and code review assistance.

AI for Automation

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.

03 / TECHNOLOGY

AI Models and Tools I Work With

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.

OpenAI API GPT-4 / GPT-4o Claude API LangChain LlamaIndex Python Django FastAPI PostgreSQL pgvector Redis Celery Docker Pinecone Chroma REST API Webhook

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.

04 / PROCESS

How I Integrate AI Into Your Systems

AI integration requires a careful, iterative approach. I follow a structured process that minimizes risk and delivers measurable results at each step.

AI Readiness Assessment

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.

Model & Architecture Selection

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.

Integration Development

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.

Testing & Prompt Optimization

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.

Deployment & Monitoring

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.

05 / CASE STUDIES

AI Integration Projects I Have Delivered

Here are real projects that demonstrate how I integrate AI into production business systems.

AI Chatbot for an Online Clothing Store

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.

Django OpenAI API REST API PostgreSQL RAG

Telegram AI Aggregator with Multi-Model Integration

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.

Python OpenAI Multi-Model Celery Redis

06 / WHO THIS IS FOR

Who This Service Is For

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:

SaaS companies that want to add AI features (smart search, content generation, recommendations) to their existing product without hiring an AI team
E-commerce businesses that need personalized product recommendations, AI-powered search, or automated product descriptions at scale
Service businesses that want to automate document processing, email triage, or report generation using AI
Startups building AI-first products that need an experienced engineer to architect and implement the AI layer from day one
Companies with large knowledge bases that want employees or customers to find answers instantly using RAG-powered semantic search

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.

07 / PRICING

AI Integration Pricing

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.

Single AI Feature

€2,000 / from

One AI integration point

Single AI feature (search, generation, etc.)
API integration with your application
Prompt engineering and optimization
Basic monitoring setup
2-3 weeks delivery
30 days post-launch support

AI Platform Integration

€5,000 / from

Multiple AI features with RAG

Multiple AI integration points
RAG with vector database
Advanced prompt engineering
Cost optimization strategy
Monitoring and alerting
4-6 weeks delivery
30 days post-launch support

Enterprise AI System

€10,000 / from

Custom AI pipeline

Multi-model architecture
Custom AI pipeline and orchestration
Advanced RAG with hybrid search
Fine-tuning and evaluation
Production monitoring dashboard
8-12 weeks delivery
60 days post-launch support

Need a custom scope? Get in touch and I will provide a tailored proposal within 24 hours.

Frequently Asked Questions

Which AI models do you work with?

I work with all major AI models: OpenAI (GPT-4, GPT-4o), Anthropic (Claude), and open-source models like Llama and Mistral. The choice depends on your use case, budget, and data privacy requirements. For most business applications, I recommend starting with OpenAI or Claude and optimizing from there. I also implement model routing so you can use the right model for each task.

Can you integrate AI into my existing application?

Yes. I specialize in adding AI capabilities to existing systems without requiring a full rebuild. Whether you need smart search, content generation, document processing, or conversational AI, I build it as a modular service that connects to your current application via a clean REST API. Your existing codebase stays intact.

How do you handle data privacy and GDPR?

All solutions are GDPR-compliant. I use EU-hosted infrastructure, implement data anonymization where needed, and ensure your data stays under your control. For highly sensitive use cases, I can deploy open-source models on your own servers so no data goes to third-party APIs. I also implement data retention policies and audit logging.

What is the difference between AI integration and building a chatbot?

AI integration is broader than chatbot development. A chatbot is one specific application of AI. AI integration also includes document processing, smart search, content generation, data analysis, recommendation engines, and workflow automation. If you specifically need a chatbot, see my AI chatbot development service.

How much does AI integration cost?

A single AI feature integration starts from EUR 2,000. Multi-feature platform integrations with RAG and prompt engineering cost from EUR 5,000. Enterprise AI systems with custom pipelines start from EUR 10,000. I provide a fixed-price estimate after a free discovery call, so you know the exact cost before development begins.

08 / YOUR DEVELOPER

About Kirill Strelnikov

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.

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