---
title: "Integrating AI Platforms: Claude, OpenAI, Gemini and Open…"
description: "Production-grade integration of Claude, OpenAI, Gemini, cloud platforms and open models: formats, tools, cost, reliability, security"
url: https://optimizeall.com/learn/ai-platform-apis-integration
updated: 2026-10-05
---

AI · Advanced · 520 minutes · free · updated Sep 2026

# Integrating AI Platforms: Claude, OpenAI, Gemini and Open Models via API

Production-grade integration of Claude, OpenAI, Gemini, cloud platforms and open models: formats, tools, cost, reliability, security

- **Lessons:** 19 in 7 modules
- **Video lectures:** 19 lectures, 171 minutes
- **Updated:** Sep 2026

## Tools you'll use

- Claude API
- OpenAI API
- Gemini API
- Anthropic Python SDK
- OpenAI Python SDK
- Google Gen AI SDK
- Amazon Bedrock
- Microsoft Foundry
- Gemini Enterprise Agent Platform
- vLLM
- Ollama
- FastAPI
- TypeScript
- Pydantic
- Docker

[Start the course](https://optimizeall.com/learn/ai-platform-apis-integration/provider-landscape-and-choosing)

## About this course

Most AI products now depend on more than one model provider, and the hard part is integration, not the prompt. This advanced, hands-on course teaches you to integrate Anthropic Claude, OpenAI and Google Gemini through their official SDKs, plus cloud platforms (Amazon Bedrock, Microsoft Foundry, Gemini Enterprise Agent Platform) and open-weight models via hosted APIs. You will compare message formats side by side, stream responses safely, implement tool calling and structured outputs across providers, send images, PDFs and audio, and build semantic search with embeddings. You will cut cost with batch APIs and prompt caching, handle rate limits and failures with backoff and circuit breakers, track spend per feature and tenant, and design a multi-provider abstraction with fallbacks and model routing. You will finish with security, privacy and a production checklist, then build, test and deploy a provider-agnostic content-generation microservice with a TypeScript client.

## What you will learn

- Choose providers and models with your own evals and cost per completed task
- Call Claude, OpenAI and Gemini correctly, including streaming, tools and structured outputs
- Process images, PDFs and audio and build embeddings-based semantic search
- Reduce cost and latency with batch APIs, prompt caching, routing and budgets
- Handle rate limits and failures with typed errors, backoff, circuit breakers and fallbacks
- Integrate via Bedrock, Microsoft Foundry, Gemini Enterprise Agent Platform and open-weight hosts
- Ship a secure, privacy-aware, observable multi-provider AI microservice

## Before you start

- [Advanced Prompt Engineering](https://optimizeall.com/learn/advanced-prompt-engineering)
- [Latest AI Techniques: RAG, Tool Use, Agents & MCP](https://optimizeall.com/learn/latest-ai-techniques-rag-agents-mcp)

## Course content

### Platform foundations

The provider landscape and how to choose models with your own evals, plus authentication, key management and secrets done safely.

- [The AI platform landscape: providers, APIs and how to choose](https://optimizeall.com/learn/ai-platform-apis-integration/provider-landscape-and-choosing): 14 min
- [API keys, authentication and secrets management](https://optimizeall.com/learn/ai-platform-apis-integration/api-keys-auth-and-secrets): 13 min

### Core API calls across providers

Messages and conversation state, streaming, tool calling and structured outputs with Claude, OpenAI and Gemini side by side.

- [Messages, roles and conversation state across Claude, OpenAI and Gemini](https://optimizeall.com/learn/ai-platform-apis-integration/messages-and-conversation-formats): 16 min
- [Streaming responses to users and between services](https://optimizeall.com/learn/ai-platform-apis-integration/streaming-responses): 15 min
- [Tool calling across Claude, OpenAI and Gemini](https://optimizeall.com/learn/ai-platform-apis-integration/tool-calling-across-providers): 17 min
- [Structured outputs: reliable JSON from every provider](https://optimizeall.com/learn/ai-platform-apis-integration/structured-outputs-json-schema): 15 min

### Multimodal inputs and embeddings

Images, PDFs and audio across providers, and embeddings APIs for semantic search in production.

- [Multimodal inputs: images, PDFs and audio](https://optimizeall.com/learn/ai-platform-apis-integration/vision-documents-and-audio): 16 min
- [Embeddings APIs and semantic search in production](https://optimizeall.com/learn/ai-platform-apis-integration/embeddings-and-semantic-search): 15 min

### Cost, scale and reliability

Batch APIs, prompt caching, rate limits and retries, and cost tracking with budgets and unit economics.

- [Batch APIs: bulk processing at a discount](https://optimizeall.com/learn/ai-platform-apis-integration/batch-apis-for-bulk-work): 14 min
- [Prompt caching across providers](https://optimizeall.com/learn/ai-platform-apis-integration/prompt-caching-across-providers): 14 min
- [Rate limits, errors, retries and backoff](https://optimizeall.com/learn/ai-platform-apis-integration/rate-limits-retries-and-backoff): 15 min
- [Cost tracking, attribution and budgets](https://optimizeall.com/learn/ai-platform-apis-integration/cost-tracking-and-budgets): 14 min

### Multi-provider architecture

A thin abstraction layer with fallbacks, and model routing strategies measured against simple baselines.

- [Multi-provider abstraction and fallbacks](https://optimizeall.com/learn/ai-platform-apis-integration/provider-abstraction-and-fallbacks): 17 min
- [Model routing: the right model for each request](https://optimizeall.com/learn/ai-platform-apis-integration/model-routing-strategies): 14 min

### Cloud platforms and open-weight models

Amazon Bedrock, Microsoft Foundry and Gemini Enterprise Agent Platform, plus open-weight models via hosted APIs and self-hosting.

- [Cloud AI platforms: Amazon Bedrock, Microsoft Foundry and Gemini Enterprise Agent Platform](https://optimizeall.com/learn/ai-platform-apis-integration/cloud-ai-platforms): 16 min
- [Open-weight models via hosted APIs and self-hosting](https://optimizeall.com/learn/ai-platform-apis-integration/open-weight-models-via-apis): 15 min

### Production readiness and capstone

Security, privacy and the production checklist, then a provider-agnostic content-generation microservice built, tested and deployed.

- [Security, data privacy and the production checklist](https://optimizeall.com/learn/ai-platform-apis-integration/security-privacy-production-checklist): 16 min
- [Capstone part 1: build a provider-agnostic content-generation microservice](https://optimizeall.com/learn/ai-platform-apis-integration/capstone-build-content-microservice): 26 min
- [Capstone part 2: test, evaluate, deploy and ship a TypeScript client](https://optimizeall.com/learn/ai-platform-apis-integration/capstone-test-deploy-typescript-client): 22 min

## Certificate: Certified AI Platform Integration Engineer

The holder can integrate Claude, OpenAI, Gemini, cloud AI platforms and open-weight models in production: correct message formats, streaming, tool calling, structured outputs, multimodal inputs and embeddings; cost control with batch, caching, routing and budgets; resilient error handling and fallbacks; and secure, privacy-aware deployment of a multi-provider AI microservice.

- **Final assessment:** 30 questions, 45 minutes
- **Passing score:** 80%