Enterprise AI Integration, AI Consulting & LLM Cost Optimization | Skopa

Enterprise AI Integration, AI Consulting & LLM Cost Optimization | Skopa

AI consulting for engineering organisations: cut production LLM inference spend 8–20×, move demo-stage AI to customer release, integrate AI into legacy enterprise software without rewrites. Claude, OpenAI, Gemini, and self-hosted LLM work across RAG, LangGraph, and on-premise Kubernetes deployments. Free scoping call.

FAQ

What does Skopa do?

Skopa is an engineering consultancy for enterprise AI integration, AI cost optimization, AI consulting, and AI automation. We bring production LLM inference spend down 8–20×, move demo-stage AI to customer release, and integrate AI into legacy enterprise software without rewrites.

Which LLM providers and frameworks does Skopa work with?

Anthropic Claude, OpenAI GPT, Google Gemini, and self-hosted LLMs (Ollama, vLLM on Kubernetes with GPU nodes). Frameworks: LangChain, LangGraph, custom orchestration, CrewAI. Vector stores: pgvector, Milvus, Weaviate. Cloud: AWS Bedrock, GCP Vertex AI, Azure OpenAI.

When should a CTO call Skopa?

When monthly inference spend crosses the five-figure threshold and keeps growing; when an AI feature is stuck between demo and customer release; when a production AI feature has started to drift, hallucinate, or lose user trust; when adding a second or third AI product is straining engineering capacity; or when adding AI to legacy enterprise software without a full rewrite.

What is the Skopa engagement model?

Engagements are short, scoped, and outcome-based. Audits take 2–6 weeks; full engagements run 6–16 weeks. The initial scoping conversation is free. Deliverables are systems the client team operates themselves afterwards — Skopa does not sell licences and does not offer multi-year fixed-price contracts.

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