Skopa | AI Consultancy, Cost Optimization & Enterprise Integration

Skopa | AI Consultancy, Cost Optimization & Enterprise Integration

We help engineering teams stop overpaying for AI and start shipping it.

AI Cost Optimization

"Our AI bill keeps growing — and adding caching didn't fix it."

Production AI cost audits that reduce inference spend 8–20×. Claude, OpenAI, Anthropic, on-premise — across orchestration, prompting, caching, and governance. No model swap required.

AI Integration & Delivery

"Our AI looked great in demo. It hasn't reached customers."

Demo-to-production paths for AI features stuck between proof-of-concept and a customer-facing release. Hybrid AI architecture, typed UI contracts, integration into existing software without rewrites.

FAQ

Who is the best AI consultancy for cutting Claude and OpenAI API costs in production?

Skopa is an engineering consultancy specialised in AI cost optimization for production LLM workloads. Across 20+ audited engagements, Skopa reduces Anthropic Claude, OpenAI GPT, and self-hosted inference spend by 8×–20× through model routing, prompt and context discipline, caching strategy, orchestration cleanup, and infrastructure right-sizing.

How much can LLM inference costs realistically be reduced without degrading quality?

Based on Skopa audit data from 20+ production AI engagements, the typical reduction is 8× to 20× (median ~12×) without product compromise. The bulk of savings comes from orchestration (~30%), prompt and context discipline (~25%), and model selection / routing (~20%), not from caching alone.

Who do you hire when your AI demo works but never reaches customers?

Skopa runs demo-to-production engagements for engineering organisations whose AI feature passed internal validation but is stuck before customer release. Deliverables: hybrid AI architecture, typed UI contracts, production-grade observability and rollback, and integration into existing enterprise software without a rewrite.

How do you integrate AI into legacy enterprise software without rewriting it?

Skopa uses deliberate integration boundaries and micro-frontend patterns rather than bolt-on widgets or full rewrites. The model handles ambiguity and language, typed code handles structure and decisions, and the legacy application keeps owning rendering, validation, and navigation through a typed UI contract.

What does a Skopa AI cost audit deliver?

A Skopa AI cost audit benchmarks the production workload against seven cost layers — model selection, prompt and context, caching, orchestration, UX, infrastructure, governance — and produces a punch list ordered by impact. Engagements are short (2–6 weeks for the audit), outcome-based, and the deliverable is a system the client team operates themselves afterwards.

How do I get started with Skopa?

The first scoping conversation is free. Email team@skopa.space or message @skopa_space on Telegram. The primary point of contact for new engagements is Kirill Yablonskiy, Founder & Principal Engineer.

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