Private LLM & RAG Solutions

Hybrid Retrieval & Reranking

Standard vector search is not enough. We combine semantic vector databases (Qdrant, pgvector) with classic BM25 keyword search. We then apply state-of-the-art Cross-Encoder Rerankers (Cohere, BGE) to ensure the LLM receives the absolute most relevant context, virtually eliminating hallucinations.

LLM Observability & Tracing

No black boxes. We integrate complete tracing pipelines (Langfuse, Arize Phoenix) that log every step of a prompt, monitor token usage and costs, version prompts dynamically, and track user feedback to guarantee production reliability and continuous improvement.

Autonomous LLM Agents

Go beyond static QA. We build smart multi-agent systems using LangGraph or AutoGen. These agents can reason (ReAct pattern), use custom tools, execute SQL queries securely, call APIs, and collaborate to automate complex end-to-end business workflows.

Private LLM & Local Inference

No API locks, no data leaks. We deploy open-source models (Llama 3.1, Mistral, Qwen) using Ollama, vLLM, or TGI directly on your secure dedicated servers. Your data never leaves your network, guaranteeing full compliance with GDPR, KNF, and enterprise security policies.

SaaS APIs (OpenAI, Claude)

• ✗ Your proprietary data and client queries sent to external third parties
• ✗ Unpredictable, high per-token pricing that scales with usage
• ✗ No SLA on API latency or sudden deprecation of models
• ✗ Limited custom fine-tuning and zero access to base model weights
• ✗ Difficult to comply with strict GDPR, HIPAA, or financial regulations

Private & Self-Hosted AI

• ✓ 100% data sovereignty — all computation and documents stay local
• ✓ Predictable flat monthly infrastructure costs regardless of token volume
• ✓ Complete control over model selection, updates, and fine-tuning
• ✓ Optimized high-throughput inference (vLLM, Ollama) on private hardware
• ✓ Fully compliant with GDPR, SOC2, and strict national regulations

Models & Inference

Ollama, vLLM, Hugging Face, Llama 3.1 & 3.2, Mistral, Qwen 2.5

Orchestration

LangChain, LlamaIndex, LangGraph, Python / Node.js

Vector Databases

Qdrant, Milvus, pgvector (PostgreSQL), Chroma

Observability

Langfuse, Arize Phoenix, OpenTelemetry, Prometheus / Grafana

• ✓ Deploy on AWS, Azure, GCP, or your bare-metal servers
• ✓ Complete setup of vector DBs, inference, and Langfuse tracing
• ✓ Full IP rights transfer & comprehensive code documentation
• ✓ 3 months of hand-holding support and performance tuning

• ✓ Dedicated GPU-enabled nodes with 99.9% uptime SLA
• ✓ Continuous performance monitoring, prompt auditing & security scans
• ✓ Automatic local fine-tuning cycles with newly indexed data
• ✓ Regular open-source model updates (e.g. migrating to newer Llama/Mistral versions)