Maxim Updates

🎙️ Feature spotlight 🧩 Fully flexible data curation flows While curating and refining test datasets from logs and test runs, you can now reference and modify any data point from a trace or test run entry; without being limited to predefined fields like input or output. Use Maxim’s DSL in the

🎙️ Feature spotlight 🔢 Synthetic Data Generation You can now generate synthetic datasets in Maxim to simplify and accelerate the testing and simulation of your Prompts and Agents. Use this to create inputs, expected outputs, simulation scenarios, personas, or any other variable needed to evaluate single and multi-turn workflows across Prompts, HTTP

🎙️ Feature spotlight 🧾 Audit logs (Maxim Enterprise) We’ve added Audit logs to the Maxim platform, giving you complete visibility and control over all the activity across your organization. You can now view a detailed trail of every action executed on the platform, including logins, runs, configuration updates, and resource changes,

🎙️ Feature spotlight 🤖 Voice simulation and evals are live on Maxim! Teams can now simulate multi-turn conversations with their voice agents and monitor performance across hundreds of scenarios and user personas – at a fraction of the time and effort required for manual testing. You can simply bring your voice agents onto

🎙️ Feature spotlight 🤖 AI-powered simulations in Prompt Playground We’ve extended simulation capabilities in the Prompt Playground, allowing you to simulate multi-turn interactions/user follow-ups and evaluate your prompts' performance across real-world scenarios and custom user personas. Key highlights: * Seamlessly connect MCP tools or attach context sources to simulate tool-calling

Feature spotlight ⚡️ Introducing Bifrost: The fastest LLM gateway We're excited to announce the public release of Bifrost, the fastest, most scalable LLM gateway out there. We've engineered Bifrost specifically for high-throughput, production-grade AI systems and optimized performance at every level. Here's how Bifrost improves

Last week at Maxim, we rolled out several powerful upgrades to give teams more control, clarity, and customization across the platform. Here's what’s new: Custom Dashboards Just Got an Upgrade Dashboards are now more flexible and insightful: * Custom metric cards – Build exactly what you need to monitor

Feature spotlight 🤖 Agentic mode in the Prompt Playground Prototype complete agent behavior, including automatic tool calling, directly within the playground. Here’s what you can do: * Test multi-step flows: Experiment with and evaluate complex agentic interactions where the model automatically calls tools and executes steps until a final response is

When you’re building with LLMs, day-to-day tasks like writing, brainstorming, and quick automation feel almost effortless. But as soon as you try to construct a robust, production-grade pipeline, the real challenges emerge. One of the first hurdles is interface fragmentation: every provider exposes a different API, with its own

Last week was packed with exciting updates at Maxim! Here's a quick rundown of what we shipped: ✨ New Features & Enhancements Markdown Support for Evaluator Instructions: Human evaluators can now use Markdown for clearer, formatted instructions. Revamped cURL Importer: HTTP agents now support POST calls, making API integrations

Feature spotlight 🔌 MCP Clients on Maxim Maxim now supports the Model Context Protocol (MCP), enabling your agents to interact with external tools, access real-time data, and perform actions. Here's what you can do with MCP clients: * Connect to popular MCP providers like Composio and Gumloop, or use your

Feature spotlight 🔗 Prompt chains: Now more powerful Maxim’s revamped Prompt Chains lets you prototype every step of your complex agentic workflow with greater clarity and control—right from our more intuitive UI. Key highlights: * 🔀 Create parallel chains to execute concurrent or conditional tasks. * 🔁 Flexibly transfer data between ports—choose

Feature spotlight 🚀 Agent simulation Teams today spend countless hours manually going back and forth with their agents to assess quality and identify failure modes. And it’s not a one-time thing— unintended regressions happen all the time, whether due to model updates or optimizations based on user feedback. Introducing Maxim’