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Drishti Shah

LLM routing techniques for high-volume applications

High-volume AI systems can’t rely on a single model or provider. This guide breaks down the most effective LLM routing techniques and explains how they improve latency, reliability, and cost at scale.

Tracking LLM token usage across providers, teams and workloads

Learn how organizations track, attribute, and control LLM token usage across teams, workloads, and providers and why visibility is key to governance and efficiency.

LLM access control in multi-provider environments

Learn how LLM access control works across multi-provider AI setups, including roles, permissions, budgets, rate limits, and guardrails for safe, predictable usage.

Agent observability: measuring tools, plans, and outcomes

Agent observability:what to measure, how to trace reasoning and tool calls, and how Portkey helps teams debug and optimize multi-step AI agents in production.

Buyer’s guide to LLM observability tools 2026

A complete guide to evaluating LLM observability tools for 2026; from critical metrics and integration depth to governance, cost, and the build-vs-buy decision for modern AI teams.

AI cost observability: A practical guide to understanding and managing LLM spend

A clear, actionable guide to AI cost observability—what it is, where costs leak, the metrics that matter, and how teams can manage LLM spend with visibility, governance, and FinOps discipline.

AI tool sprawl: causes, risks, and how teams can regain control

AI tool sprawl creates fragmented access, inconsistent governance, and rising operational overhead. This guide explains why it happens, the risks it introduces, and practical steps teams can take to bring structure back to their AI stack.

Gemini 3.0 vs GPT-5.1: a clear comparison for builders

A concise comparison of Gemini 3.0 and GPT-5.1 across reasoning, coding, multimodal tasks, agent performance, speed, and cost. Learn which model performs better overall and how teams can run both through a single production-ready gateway.

From standard to ecosystem: the new MCP updates, Nov 2025

Releasing November 25, the latest MCP update introduces async operations, stateless architecture, and registry GA, advancing MCP from a standard to an interoperable ecosystem for production AI systems.

Claude Skills: definition, use cases, and limitations

A detailed look at Claude Skills — what they are, how they work, and why they matter. Learn how Anthropic’s new Skills framework could make LLM workflows more structured, consistent, and efficient for real-world use.