The right model for every step of your pipeline
Claude Opus 5.5, GPT-6 Luna and Sol, Gemini, Grok 4.7, Jev. The AI model market shifts every month. We assess your use case, prototype with multiple models and design the multi-model architecture that optimises quality and cost.
From evaluation to deployment
Use-case assessment
We analyse your tasks, volumes, latency requirements, compliance needs and budget. We identify which parts of your pipeline need reasoning (Opus, Sol), which need throughput (Luna, Flash) and which need structured data (Jev).
Multi-model prototyping
We run your actual tasks against 3-4 candidate models. We measure quality, latency and cost per query. No made-up numbers: the data comes from your specific use case.
Routing design
We design the logic that decides which model handles each query. A complexity classifier that routes to the right model can reduce costs by 60-80%.
Compliance and security
We evaluate data residency options (EU, US), no-training policies, SOC2 certifications, and GDPR requirements for each provider.
Implementation
We deploy the multi-model architecture with quality and cost monitoring. Integration with your existing stack via API.
Ongoing review
Models change every month. We review quarterly whether your architecture is still optimal or if newer models improve quality or cost.
The full market, not a single vendor
Free audit of your AI architecture
Tell us about your use case, we evaluate which models fit and propose the optimal multi-model architecture. No strings attached.
Tell us your challenge. We'll propose a solution.
No commitment. Within 24 hours, you'll receive a proposal with scope, timeline and budget. No fine print.