Artificial Intelligence
Custom AI solutions built for your business
We design and build production-ready AI systems — from customer-facing chatbots and voice assistants to internal automation pipelines and MCP-powered data integrations. Backed by 200+ delivered projects and 19 years of software development experience, we help businesses move from AI curiosity to measurable results.
What We Build with AI
AI Answer Engine Optimization
We optimize your content and knowledge base so AI-powered search engines and chatbots — ChatGPT, Perplexity, Gemini, and others — surface your business as the authoritative answer. Structured data, semantic markup, and conversational content strategies that put your brand at the top of AI-generated responses.
AI Chatbots & Virtual Assistants
Custom chatbots trained on your business data — for customer support, lead generation, onboarding, and internal Q&A. Integrated via web, mobile, or messaging platforms.
MCP Server Development
We build Model Context Protocol servers that connect large language models directly to your databases, APIs, and internal tools — giving AI real-time access to the data it needs to act.
AI in Mobile Applications
Embed AI features directly into your iOS or Android app — smart search, content recommendations, image recognition, voice commands, and on-device inference.
LLM Integration & Fine-tuning
We integrate OpenAI, Anthropic Claude, Google Gemini, and open-source models into your product stack. Custom prompt engineering, RAG pipelines, and model fine-tuning included.
AI Strategy & Consulting
Not sure where to start? We audit your existing processes, identify the highest-ROI AI opportunities, and deliver a prioritized implementation roadmap — no buzzwords, just a plan.
How We Deliver with AI
Discovery & Scoping
We start with your business goals — not the technology. A structured workshop maps your processes, data sources, and success metrics before a single line of code is written.
Prototype & Validate
A working proof-of-concept in 2–4 weeks. You see real outputs on your real data before committing to full development.
Build & Integrate
Production-grade implementation — secure API connections, data pipelines, UI components, and full integration with your existing systems.
Monitor & Improve
AI systems need ongoing tuning. We provide monitoring dashboards, model performance tracking, and continuous improvement cycles post-launch.
Why AI and Why Now
The window for early movers is closing
Businesses that deployed AI-powered customer support, document processing, or predictive analytics in 2023–2024 have already cut operational costs by 20–40% in those workflows. The productivity gap between AI-adopters and laggards is widening every quarter. Waiting for AI to become "more mature" means ceding ground to competitors who are already running leaner, faster, and with better data visibility.
The barrier to entry has never been lower
You no longer need a machine learning team or a data science department to implement AI. Modern APIs from Anthropic, OpenAI, and Google put frontier-model intelligence behind a single HTTP call. MCP protocol lets those models connect to your existing databases and tools without rebuilding your infrastructure. A focused integration project can go from idea to production in under two months.
AI that actually knows your business
Generic AI tools answer generic questions. The difference is context. When an AI assistant is connected to your product catalog, your CRM, your booking system, or your internal knowledge base via an MCP server, it stops being a chatbot and starts being a knowledgeable team member available 24/7. That is the kind of AI we build — specific, grounded, and measurably useful.
AI Technologies
We are model-agnostic and tool-agnostic. We select the right stack based on your requirements, not on partnerships.
Anthropic Claude 3.5 / 4, OpenAI GPT-4o, Google Gemini 1.5 Pro, Mistral, Llama 3
LangChain, LlamaIndex, Vercel AI SDK, Model Context Protocol (MCP)
Pinecone, Weaviate, pgvector (PostgreSQL), Chroma
AWS, Google Cloud, Vercel, Docker, Node.js, Python FastAPI
Industry Experience
Ready to integrate AI into your business?
Tell us about your project — we'll get back to you with a tailored proposal and timeline.
The estimator is built for mobile apps — but it's a live example of how we put AI to work.
Frequently Asked Questions
What is AI and what is an LLM?
AI (Artificial Intelligence) is software that can perform tasks typically requiring human intelligence — understanding language, recognizing images, making decisions. An LLM (Large Language Model) is a specific type of AI trained on vast amounts of text data that can read, write, summarize, and reason in natural language. Models like Anthropic Claude, OpenAI GPT-4o, and Google Gemini are LLMs. In practical terms, LLMs are the engine behind modern chatbots, AI assistants, and text-based automation — and they are what we build with.
What AI services does Codify offer?
We build AI chatbots, MCP servers, automation pipelines, AI-powered mobile apps, and provide LLM integration and AI strategy consulting. We work with OpenAI, Anthropic Claude, Google Gemini, and open-source models.
How much does AI integration cost?
It depends on the scope. A focused chatbot integration typically starts from €5,999. Complex automation systems or custom MCP server development are scoped individually. Use our AI estimator to get a project-specific breakdown.
Can you add AI to our existing app or website?
Yes. We specialize in integrating AI capabilities into existing products — adding a chatbot widget, embedding recommendations, or connecting a backend pipeline — without rebuilding from scratch.
What is an MCP server and do I need one?
MCP (Model Context Protocol) is an open standard that lets AI models securely access your live data — databases, APIs, documents — in real time. If you want an AI assistant that actually knows your business data rather than giving generic answers, you likely need an MCP server.
How long does it take to build an AI solution?
A prototype is typically ready in 2–4 weeks. A production-ready solution usually takes 6–12 weeks depending on complexity. We always start with a working proof-of-concept on your data before full development.
Can you add AI features to an existing iOS app?
Yes. We integrate AI capabilities directly into Swift/SwiftUI iOS apps — on-device inference with Core ML, cloud LLM calls via Anthropic or OpenAI APIs, smart search, voice commands, and personalized recommendations. We can extend your existing codebase without rewriting the app.
How do you integrate AI into Android applications?
We embed AI into Android apps using Kotlin — connecting to cloud LLMs for conversational features, using Google ML Kit for on-device vision and NLP tasks, and building background pipelines for smart notifications and content classification. Integration works with both new builds and existing apps.
What AI features can be added to a web application?
Web apps can benefit from AI-powered chatbots, semantic search, automated content generation, document analysis, and personalized dashboards. We build these using RAG pipelines, LLM APIs, and streaming UI components — all deployable on your existing infrastructure without a full rebuild.