AI & ML Solutions
We build AI systems that work in production — not just demos. From RAG-powered chatbots and LLM evaluation pipelines to computer vision and predictive analytics, we integrate artificial intelligence into your existing data infrastructure. Our approach is práctical: we start with your business problem, select the right model and architecture, and deliver measurable results. No hype, no vaporware — just AI that ships.
What We Deliver
- RAG (Retrieval-Augmented Generation) chatbots with hybrid search and knowledge bases
- LLM integration and evaluation pipelines (Claude, GPT-4, Llama, Groq)
- Vector search and embedding systems using Cloudflare Workers AI, OpenAI, or BGE
- Computer vision pipelines for image classification, OCR, and document processing
- AI-assisted development tooling and code generation workflows
- Model deployment, monitoring, and cost optimization
Technologies We Use
Python
Core language for ML pipelines, data processing, and API development
Claude / Anthropic
Advanced LLM for complex reasoning, code generation, and multi-turn conversations
Groq
Ultra-fast inference engine for Llama models — real-time AI responses
Cloudflare Workers AI
Edge AI inference and embeddings — low latency, zero cold starts
Why dataqbs for AI & ML
We are not just AI researchers — we are data engineers who build AI systems on top of real data platforms. This means your AI solution is grounded in clean data pipelines, proper data modeling, and production infrastructure from day one. We have built RAG chatbots serving real users, LLM evaluation systems for production apps, and computer vision pipelines processing thousands of images daily.
- Production RAG chatbots with hybrid search (cosine + BM25) serving real users
- LLM evaluation and prompt engineering for Llama, Claude, and GPT models
- AI built on proper data engineering foundations — not hacky Jupyter notebooks
- Cost-optimized deployments using edge AI, caching, and smart model selection