LLM Gateway

TL;DR AI gateways solve the complexity of managing multiple LLM providers by providing unified interfaces, intelligent routing, and production-grade reliability. This guide compares five leading solutions: Bifrost, Cloudflare AI Gateway, Vercel AI Gateway, Kong AI Gateway, and LiteLLM. Each addresses multi-provider access while offering distinct capabilities for cost optimization,

TL;DR: Building production LLM applications requires robust failure handling strategies. Retries automatically recover from transient errors like rate limits and network timeouts. Fallbacks seamlessly switch between providers when the primary option fails. Circuit breakers prevent cascading failures by temporarily blocking requests to unresponsive services. Together, these patterns form the

Table of Contents * TL;DR * Quick Comparison Table * Overview > What is an LLM Orchestration Platform * Detailed Feature Matrix * Platform Profiles * Platforms > Bifrost by Maxim AI * Platforms > LangChain * Platforms > LlamaIndex * Platforms > Haystack * Platforms > Semantic Kernel * Selection Guide > How to Choose * Use Case Matcher * Conclusion

As enterprises move from AI experimentation to production deployment in 2026, the infrastructure layer managing LLM access has become mission-critical. With 40% of enterprise applications now integrated with task-specific AI agents, organizations can no longer afford makeshift solutions for managing multi-provider AI infrastructure. The shift from prototyping to production has

Table of Contents 1. TL;DR 2. The Enterprise Claude Code Challenge 3. How Bifrost Enables Enterprise-Scale Deployments 4. Key Scaling Capabilities * Capabilities > Multi-Team Access Control * Capabilities > Cost Optimization Through Model Routing * Capabilities > Production-Grade Reliability * Capabilities > Unified Observability 5. Implementation Architecture 6. Best Practices for Production

Introduction Tool calling transforms static AI models into dynamic, action-capable agents. Instead of just generating text, AI models can interact with external systems - search the web, query databases, read files, and execute business logic. In this comprehensive guide, you'll learn how to build a production-ready Research Assistant