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AI Model API Integrations

We act as the 'glue' between AI models (OpenAI, Anthropic, Google, open-source) and your systems (CRM, ERP, e-commerce, apps). Reliable, secure middleware with caching and intelligent routing to optimize costs and latency.

Seamless connection between AI models, cloud services, and your existing business systems.

Use cases

  • Unified AI layer for multiple products
  • Provider replacement without app refactoring
  • Shared caching across data science teams
  • Multi-region compliance (EU/US data residency)
  • A/B testing between different models

Measurable benefits

  • API costs under control and monitored per feature
  • Predictable latency with caching
  • Vendor independence (no lock-in)
  • Enterprise-grade security

Technical details

AI Providers

  • OpenAI (GPT-4o, o1, DALL-E, Whisper)
  • Anthropic (Claude 3.5 Sonnet/Opus)
  • Google (Gemini 1.5 Pro/Flash)
  • Open-source (Llama, Mistral, Qwen)

Middleware

  • Custom API gateways (FastAPI, Hono)
  • Per-tenant rate limiting
  • Request/response transformation
  • Multi-region failover

Security

  • OAuth 2.0, OIDC, JWT
  • API key rotation
  • Secrets management (Vault, AWS Secrets)
  • Audit logs and WAF

Cost optimization

  • Semantic caching to avoid duplicate calls
  • Model-based routing (cheap → expensive)
  • Automatic batching
  • Budget alerts per client/feature

How we connect systems that do not talk to each other

  1. Interface analysis — We verify what each system really exposes: documented APIs, webhooks, scheduled exports or only database access.
  2. Data contract — We define entities, unique keys and sync direction: without an authoritative source per field, conflicts become permanent.
  3. Authentication — Dedicated integration credentials with expiry and rotation — never personal accounts.
  4. Idempotency and retries — Every call must be repeatable without duplicating data, because network interruptions are normal.
  5. Rate limits and cost — We respect provider rate limits and size synchronisations on real volumes.
  6. Observability — Call logs, alerts on recurring failures and a minimal dashboard showing which side of the integration stopped.

We deliver the integration map, data contract, credential configuration and operational logs.

Working with us

The team that analyses the process is the team that builds and maintains it: product, engineering, integration with your existing systems, governance of automated decisions and post-release support.

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FAQ

What is semantic caching?

It stores AI responses to semantically similar requests, avoiding duplicate calls. On highly repetitive use cases the impact on cost is significant, and we measure it before and after rollout.

Can I switch providers without rewriting the app?

Yes. The middleware exposes a single API and internally manages routing to the provider. You switch models via configuration.

Do you also support self-hosted models?

Yes: we integrate vLLM, Ollama, and Text Generation Inference for on-premise or private cloud models.