AI Gateway

TL;DR: LLM provider failures are not edge cases. They are a regular part of running AI in production. Retries, fallbacks, and circuit breakers each solve different failure modes, and combining them intelligently using an AI gateway like Bifrost is the most reliable path to consistent uptime for AI-powered

TL;DR: LLM costs are ballooning as AI usage scales. AI gateways are the fastest way to cut spend, without changing your application logic. This article breaks down the top 5 gateways in 2026, Bifrost, Cloudflare, Vercel, LiteLLM, and Kong AI, so you can pick the right one for your

Enterprise AI adoption is accelerating at an unprecedented rate. According to Gartner, global spending on AI is projected to reach $2.52 trillion in 2026, a 44% increase year-over-year. At the same time, Stanford's 2025 AI Index documented 233 AI-related security incidents in 2024 alone,

Portkey works well for teams in early production stages. Its breadth of model support, config-based routing, and managed observability lower the barrier to multi-provider AI integration. But as organizations scale, several architectural and commercial constraints become blockers. Log-Based Pricing Creates Cost Unpredictability Portkey's pricing model

Comparing the top 5 AI gateways for optimizing LLM cost in 2026: Bifrost, Cloudflare, LiteLLM, Vercel, and Kong. Production LLM applications running across multiple providers routinely generate five-figure monthly invoices, with redundant prompts, untracked team usage, missing fallback logic, and unbounded agent loops driving most of the waste. Worldwide

Fintech companies are deploying LLM-powered applications across fraud detection, credit decisioning, customer support automation, and regulatory compliance workflows. As these systems move from prototype to production, the infrastructure connecting applications to LLM providers becomes a critical scaling bottleneck. Provider outages, unpredictable API costs, fragmented authentication schemes, and compliance requirements