AI Gateway

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

Introduction Bifrost by Maxim AI is an open-source, high-performance LLM gateway built in Go that helps AI engineers build production-ready AI applications. This technical guide walks you through Bifrost's architecture, features, and practical implementation patterns to help you leverage its full capabilities. What is Bifrost? Bifrost is an

TL;DR Running large language models in production can quickly become expensive and slow without proper optimization. Organizations often face monthly bills exceeding $250,000 and response times that frustrate users. This guide explores proven strategies to reduce LLM costs by 30-50% and latency by up to 10x through intelligent