AI Transformation
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AI Architecture
Development of scalable AI architectures – from RAG pipelines to agent systems to complete MLOps platforms.
✓ What We Offer
✓ RAG Pipeline Design & Implementation
✓ LLM Integration & Orchestration
✓ AI Agent Development
✓ MLOps Platform Setup
✓ Vector Database Architecture
✓ Prompt Engineering & Optimization
✓ Model Evaluation & Benchmarking
✓ Scalable AI Infrastructure
From Idea to Production-Ready AI
A good AI solution needs more than an API call to ChatGPT. We design and build architectures that scale, are reliable, and deliver real business value.
Our Architecture Patterns
RAG (Retrieval Augmented Generation)
The gold standard for enterprise AI – enriching LLMs with your own knowledge:
- Document Processing Pipelines
- Chunking & Embedding Strategies
- Vector Database Selection & Tuning
- Hybrid Search (Semantic + Keyword)
- Re-Ranking & Filtering
AI Agents
Autonomous systems that independently solve complex tasks:
- Tool Use & Function Calling
- Multi-Step Reasoning
- Memory & Context Management
- Human-in-the-Loop Integration
MLOps
Operating machine learning in production:
- Model Registry & Versioning
- Automated Training Pipelines
- A/B Testing & Experimentation
- Model Monitoring & Drift Detection
- Feature Stores
Technology Stack
| Layer | Enterprise | Open-Source |
|---|---|---|
| LLM | OpenAI GPT-4, Azure OpenAI | Llama, Mistral, Ollama |
| Orchestration | Azure AI, Vertex AI | LangChain, LlamaIndex |
| Vector DB | Azure AI Search, Vertex Vector | Qdrant, Milvus, Chroma |
| Automation | Power Automate, Logic Apps | N8N, Prefect |
| MLOps | Azure ML, Vertex AI | MLflow, Kubeflow |
Our Architecture Process
- Requirements Workshop – Understanding what you want to achieve
- Architecture Design – Technology selection, component design
- Proof of Concept – Quickly validate before we scale
- Production Build – Robust, scalable implementation
- Handover & Enablement – Empowering your team