Evaluation

Beyond the SDK: Why AI Teams Love HTTP Endpoint-Based Evals

Beyond the SDK: Why AI Teams Love HTTP Endpoint-Based Evals

Since the beginning, HTTP Endpoint-Based Offline Evals have been a core feature of the Maxim platform and a favorite among our users. While our SDKs allow engineers to integrate evaluations directly into their codebase, a purely code-based approach introduces friction, often limiting who can run them and how they are

Building a Customer Support AI Agent with AWS Bedrock and Testing It at Scale

Building a Customer Support AI Agent with AWS Bedrock and Testing It at Scale

Introduction Customer support is one of the most impactful use cases for AI agents. A well-designed support agent can handle thousands of inquiries simultaneously, provide instant responses, and maintain context across complex conversations. But how do you ensure your agent actually works before unleashing it on real customers? In this

What are Offline Evaluations and How to Set Them Up for Your AI System Using Maxim AI

What are Offline Evaluations and How to Set Them Up for Your AI System Using Maxim AI

Introduction Before deploying your AI system to production, you need confidence that it performs well across various scenarios, maintains quality standards, and produces consistent results. This is where offline evaluations become essential. Offline evaluations use curated datasets, scenario simulations, and evaluators to benchmark prompts, workflows, and agents before deployment. They

What are Online Evaluations and How to Set Them Up for Your AI System Using Maxim AI

What are Online Evaluations and How to Set Them Up for Your AI System Using Maxim AI

Introduction Building an LLM-powered application is one thing; ensuring it performs optimally in production is another challenge entirely. In this blog we will go deeper into Online Evaluations & setting them up for production usecases. Let's start by understanding the difference between Online & Offline Evals. Online vs.

When AI Snitches: Auditing Agents That Spill Your Model’s (Alignment) Tea

When AI Snitches: Auditing Agents That Spill Your Model’s (Alignment) Tea

Sure, your model aced every benchmark, but can you trust it when the stakes are real? Every frontier lab runs alignment post-training before shipping their chat models to the world. The problem? Actually auditing whether this alignment worked can be an absolute nightmare. You're basically trying to find

Building and Evaluating a Reddit Insights Agent with Gumloop and Maxim AI

Building and Evaluating a Reddit Insights Agent with Gumloop and Maxim AI

Reddit is one of the internet’s most valuable data sources, and also one of the most chaotic. Somewhere between the hot takes on r/technology and the unsolicited growth advice on r/marketing, there are real signals hiding in plain sight: what people are building, breaking, hyping up, or

Evaluating a Healthcare use case using Vertex AI and Maxim AI - Part 1

Evaluating a Healthcare use case using Vertex AI and Maxim AI - Part 1

Introduction Building AI agents has become more accessible than ever, empowering developers to create sophisticated, autonomous systems. But moving from a working prototype to a production-ready agentic application brings a new set of challenges, from ensuring reliability and safety, to evaluating performance at scale. Agentic systems, by nature, are complex.