Maxim AI

# Maxim AI Documentation

> Maxim AI is the GenAI evaluation and observability platform that helps teams build reliable AI applications. This documentation covers our platform features, APIs, SDKs, and comprehensive guides for AI development and testing.

Maxim AI provides:
- Observability and monitoring for AI applications
- Agent simulation and evaluation
- Comprehensive SDK support for Python and TypeScript
- Integration with leading Agent Development platforms and frameworks
- Enterprise-grade security

## Documentation

- [Maxim AI - Home](https://getmaxim.ai): Maxim AI is an end-to-end evaluation and observability platform for AI agents.
- [Maxim Bifrost](https://www.getmaxim.ai/bifrost): Bifrost is a high-performance LLM gateway that connects 1000+ models through a single API interface with extremely high throughput and is 40x faster than LiteLLM.
- [Maxim Bifrost - OSS Friends](https://www.getmaxim.ai/bifrost/oss-friends): Amazing open source projects that share our mission of making AI development more accessible and efficient.
- [Platform Overview](https://www.getmaxim.ai/docs/introduction/overview): An introduction to Maxim's platform for AI application development and observability.
- [Maxim Documentation Home](https://www.getmaxim.ai/docs): Overview of Maxim's platform and its features for AI application development.
- [The GenAI evaluation and observability platform](https://www.getmaxim.ai/llms.txt): Overview of Maxim AI's GenAI evaluation and observability platform.
- [CoTools and the Future of LLM Tool Use for Complex Reasoning](https://www.getmaxim.ai/blog/chain-of-tools-llm-framework): Introduction to the Chain-of-Tools framework for enabling LLMs to interact with external tools.
- [Maxim AI February 2025 Update](https://www.getmaxim.ai/blog/maxim-february-2025-update): Overview of new features and updates in Maxim AI for February 2025.
- [Building Robust Evaluation Workflows for AI Agents](https://www.getmaxim.ai/blog/evaluation-workflows-for-ai-agents): Best practices for evaluating AI agents through structured workflows.
- [Experimentation](https://www.getmaxim.ai/products/experimentation): Product page for Maxim AI's experimentation tools for prompts and agents.
- [Evaluating a Healthcare Use Case Using Vertex AI and Maxim AI - Part 1](https://www.getmaxim.ai/blog/evaluating-a-healthcare-use-case-using-vertex-ai-and-maxim-ai-part-1): Introduction to evaluating healthcare AI systems using Vertex AI and Maxim AI.
- [Can Your AI Explain Why It’s Moral?](https://www.getmaxim.ai/blog/can-your-ai-explain-why-its-moral): Examines the ethical reasoning capabilities of AI models using a structured audit framework.
- [Advanced RAG Techniques](https://www.getmaxim.ai/blog/advanced-rag-techniques): Exploration of Astute RAG for handling imperfect retrieval in LLMs.
- [Agent-as-a-Judge: Evaluating Agentic Systems](https://www.getmaxim.ai/blog/agent-evaluation): Explores the Agent-as-a-Judge framework for evaluating agentic systems using AI.
- [Maxim AI June 2025 Updates](https://www.getmaxim.ai/blog/maxim-ai-june-2025-updates): Highlights new features, integrations, and updates in Maxim AI for June 2025.
- [Announcing Maxim AI’s General Availability and Seed Round](https://www.getmaxim.ai/blog/announcing-maxim-ais-general-availability-and-the-3m-funding-round-led-by-elevation-capital): Announcement of Maxim AI's general availability and $3M funding round led by Elevation Capital.
- [Chain-of-Thought Prompting: Enhancing LLM Reasoning](https://www.getmaxim.ai/blog/chain-of-thought-prompting): A blog exploring the Chain-of-Thought prompting technique for LLMs.
- [SuperBPE: Rethinking Tokenization for Language Models](https://www.getmaxim.ai/blog/superbpe-rethinking-tokenization-for-language-models): Exploration of the SuperBPE tokenization strategy for language models.
- [Maxim AI March 2025 Updates](https://www.getmaxim.ai/blog/maxim-ai-march-2025-updates): Highlights of new features, customer stories, and upcoming releases in Maxim AI.
- [Base vs. Aligned: Why Base LLMs Might be Better at Randomness and Creativity](https://www.getmaxim.ai/blog/base-vs-aligned-why-base-llms-might-be-better-at-randomness-and-creativity): Explores the tradeoffs between base and aligned LLMs in tasks requiring unpredictability and creativity.
- [Sure your LLM is smart, but does it really give a damn?](https://www.getmaxim.ai/blog/sure-your-llm-is-smart-but-does-it-really-give-a-damn): Exploration of goal-directedness in large language models and its impact on agentic applications.
- [RAGChecker](https://www.getmaxim.ai/blog/ragchecker-eval-tool): Exploration of the RAGChecker framework for evaluating Retrieval-Augmented Generation systems.
- [Schedule a Demo - Maxim](https://www.getmaxim.ai/demo): Schedule a demo to see Maxim in action and save development time.
- [Agent Simulation & Evaluation](https://www.getmaxim.ai/products/agent-simulation-evaluation): Simulate and evaluate AI agent interactions across scenarios and user personas.
- [Built an Event Discovery AI Agent using No-Code under 15 mins](https://www.getmaxim.ai/blog/built-an-event-discovery-ai-agent-using-no-code-under-15-mins): Blog post on creating an event discovery AI agent using n8n and Maxim.
- [Innovative Training of LLMs in Continuous Latent Spaces](https://www.getmaxim.ai/blog/llms-continuous-latent-spaces): Exploration of Coconut, a novel approach to LLM reasoning in continuous latent spaces.
- [Agent Observability](https://www.getmaxim.ai/products/agent-observability): Monitor and improve AI agent performance with real-time insights and observability tools.
- [Skipping the Thinking: How Simple Prompts Can Outperform Complex Reasoning in AI](https://www.getmaxim.ai/blog/skipping-the-thinking-how-simple-prompts-can-outperform-complex-reasoning-in-ai): Explores the 'NoThinking' strategy for efficient AI reasoning.
- [Maxim AI Pricing Plans](https://www.getmaxim.ai/pricing): Explore Maxim AI's pricing plans for developers, professionals, businesses, and enterprises.
- [Synthetic Data Generation Grounded in Real Data Sources](https://www.getmaxim.ai/blog/synthetic-data-generation): Exploration of the Source2Synth framework for generating high-quality synthetic data.
- [RAGEval: Scenario-specific RAG Evaluation Framework](https://www.getmaxim.ai/blog/rageval-rag-eval): Introduction to RAGEval, a framework for generating domain-specific RAG evaluation datasets.
- [What is RAG? A Comprehensive Guide](https://www.getmaxim.ai/blog/rag-in-ai): An in-depth guide to retrieval-augmented generation (RAG) in AI.
- [Maxim Social Updates](https://www.getmaxim.ai/blog/maxim-social-updates): Highlights Maxim AI's partnerships, launches, and platform listings.
- [APIGen-MT: Structured Multi-Turn Data via Simulation](https://www.getmaxim.ai/blog/apigen-mt-structured-multi-turn-training-data-for-agents): Introduction to APIGen-MT for generating multi-turn training data for AI agents.
- [Platform Overview](https://www.getmaxim.ai/docs/observability/concepts): Overview of Maxim's tools for AI application development and observability.
- [Build an AI Interview Voice Agent with LiveKit & Maxim](https://www.getmaxim.ai/blog/build-an-ai-interview-voice-agent-with-livekit-maxim): A tutorial on building a real-time AI interview voice agent using LiveKit and Maxim.
- [Careers](https://www.getmaxim.ai/careers): Join Maxim AI to shape the future of AI development.
- [Scaling Enterprise Support: Atomicwork's Journey to Seamless AI Quality with Maxim](https://www.getmaxim.ai/blog/scaling-enterprise-support-atomicworks-journey-to-seamless-ai-quality-with-maxim): Case study on how Atomicwork uses Maxim AI to ensure reliable and scalable AI-powered enterprise support.
- [Maxim AI - Product Updates, December 2024](https://www.getmaxim.ai/blog/maxim-ai-december-2024-updates): Overview of new features and updates in Maxim AI for December 2024.
- [About Us](https://www.getmaxim.ai/about-us): Overview of Maxim's mission, team, and vision for AI development.
- [Long-context LLMs vs RAG](https://www.getmaxim.ai/blog/llm-rag-compare): Comparison of long-context LLMs and Retrieval-Augmented Generation (RAG) models.
- [Maxim AI January 2025 Updates](https://www.getmaxim.ai/blog/maxim-ai-january-2025-updates): Overview of new features and updates in Maxim AI for January 2025.
- [Can We Trust What AI Models Say They're Thinking? A Deep Dive into Chain-of-Thought Faithfulness](https://www.getmaxim.ai/blog/can-we-trust-what-ai-models-say-theyre-thinking-a-deep-dive-into-chain-of-thought-faithfulness): Exploration of the faithfulness of AI models' Chain-of-Thought reasoning.
- [🌤️ Building a Gemini-Powered Conversational Weather Agent with Maxim Logging](https://www.getmaxim.ai/blog/building-a-gemini-powered-conversational-weather-agent-with-maxim-logging): A tutorial on building a conversational weather agent using Gemini AI and Maxim logging.
- [Mindtickle’s Robust AI Productionizing Process powered by Maxim](https://www.getmaxim.ai/blog/mindtickle-ai-quality-evaluation-using-maxim): Explores how Mindtickle uses Maxim to enhance AI quality and streamline production processes.
- [Agent Evaluation: Metrics for Evaluating Agentic Workflows](https://www.getmaxim.ai/blog/ai-agent-evaluation-metrics): A blog post discussing metrics for evaluating AI agents in dynamic workflows.
- [Mastering the Art of Prompt Engineering: A Practical Guide for Better AI Outcomes](https://www.getmaxim.ai/blog/mastering-prompt-engineering): A comprehensive guide to crafting effective prompts for AI models.
- [Best Practices for Retrieval-Augmented Generation (RAG)](https://www.getmaxim.ai/blog/rag-best-practices): Comprehensive guide to optimizing RAG systems with advanced techniques.
- [AlphaEvolve: AI for Scientific Discovery](https://www.getmaxim.ai/blog/alphaevolve-ai-for-scientific-discovery): Exploration of AlphaEvolve, an AI system for algorithmic discovery in scientific challenges.
- [The Role of Retrieval in Improving RAG Performance](https://www.getmaxim.ai/blog/rag-retrieval): Exploration of retrieval techniques to enhance Retrieval-Augmented Generation (RAG).
- [✨ Agentic mode, Scheduled runs, New evals, and more](https://www.getmaxim.ai/blog/maxim-ai-may-2025-updates): Highlights of Maxim AI's May 2025 updates, including new features and model support.
- [LLM Hallucination Detection](https://www.getmaxim.ai/blog/llm-hallucination-detection): Exploration of fine-grained hallucination detection techniques for improving LLM accuracy.
- [Tool Chaos No More: Measuring Model-Tool Accuracy](https://www.getmaxim.ai/blog/tool-chaos-no-more-how-were-measuring-model-tool-accuracy-in-the-age-of-mcp): Insights into benchmarking tool call accuracy in AI models using MCP.
- [Custom Evaluators](https://getmaxim.ai/docs/library/how-to/evaluators/create-custom-ai-evaluator): Guide to creating and configuring custom evaluators for AI evaluation needs.
- [Last Week at Maxim: Week 1 of May](https://www.getmaxim.ai/blog/last-week-at-maxim-week-1-of-may): Weekly updates on new features and improvements at Maxim.
- [Improving RAG accuracy with reranking techniques](https://www.getmaxim.ai/blog/reranker-rag): Explores how reranking techniques can enhance Retrieval-Augmented Generation (RAG) accuracy.
- [Tracing Quickstart](https://www.getmaxim.ai/docs/tracing/quickstart): A guide to setting up distributed tracing for GenAI applications.
- [Evaluating Data Contamination in LLMs](https://www.getmaxim.ai/blog/llm-data-quality): Analysis of data contamination in large language models and its impact on benchmarks.
- [Create a Customer Support Email Agent](https://www.getmaxim.ai/docs/offline-evals/guides/create-customer-support-agent): Step-by-step guide to building a customer support email agent using Maxim AI.
- [Evaluating the Quality of Clinical Documentation Using Maxim AI](https://www.getmaxim.ai/blog/create-reliable-clinical-notes-using-maxim): A guide to creating and evaluating reliable clinical notes using Maxim AI's tools.
- [Founders’ Office - Marketing Generalist](https://www.getmaxim.ai/jobs/marketing-generalist): Job opening for a Marketing Generalist role at Maxim, focused on content strategy in the AI development space.
- [Evaluating the Quality of NL-to-SQL Workflows](https://www.getmaxim.ai/blog/evaluating-the-quality-of-nl-to-sql-workflows): Explores methods to improve NL-to-SQL workflows for better query accuracy and user trust.
- [LangChain Integration](https://www.getmaxim.ai/docs/sdk/typescript/integrations/langchain/langchain): Comprehensive guide to integrating Maxim observability with LangChain applications in TypeScript/JavaScript.
- [From Zero to OTel: Architecting a Stateless Tracing SDK for GenAI](https://www.getmaxim.ai/blog/from-zero-to-otel-architecting-a-stateless-tracing-sdk-for-genai-part-1): Explores the architecture of a stateless distributed tracing system compatible with OpenTelemetry for GenAI observability.
- [Building a Math Trivia Game Agent with Mistral AI and Maxim](https://www.getmaxim.ai/blog/building-a-math-trivia-game-agent-with-mistral-ai-and-maxim): A tutorial on creating a Math Trivia Game using Mistral AI and Maxim for observability.
- [Making Language Models Unbiased, One Vector At a Time](https://www.getmaxim.ai/blog/making-language-models-unbiased-one-vector-at-a-time): Explores methods to reduce bias in large language models using interpretability-based techniques.
- [Do Language Models Know That They're Being Evaluated?](https://www.getmaxim.ai/blog/do-language-models-know-that-theyre-being-evaluated): Explores the phenomenon of evaluation awareness in language models and its implications.
- [Maxim Integration for CrewAI](https://www.getmaxim.ai/docs/sdk/python/integrations/crewai/crewai): Comprehensive agent monitoring, evaluation, and observability for CrewAI applications.
- [From Turn 1 to Turn 10: How LLMs Get Lost In Multi-Turn Conversations](https://www.getmaxim.ai/blog/from-turn-1-to-turn-10-how-llms-get-lost-in-multi-turn-conversations): Explores the challenges LLMs face in multi-turn conversations and proposes methods to mitigate performance degradation.
- [Set Up Alerts and Notifications](https://www.getmaxim.ai/docs/online-evals/set-up-alerts-and-notifications): Learn how to configure notification channels and set up alerts for monitoring AI application performance and quality metrics.
- [Evaluating the Quality of Healthcare Assistants using Maxim AI](https://www.getmaxim.ai/blog/evaluating-quality-of-healthcare-assistants-using-maxim): Guide to evaluating AI healthcare assistants for reliability and performance using Maxim.
- [DSPy Framework](https://www.getmaxim.ai/blog/dspy-framework): An overview of DSPy, a declarative framework for optimizing LLM pipelines.
- [OpenAI’s BrowseComp: Redefining How We Benchmark Web-Browsing Agents](https://www.getmaxim.ai/blog/openai-browsecomp-web-browsing-agent-benchmark): An overview of OpenAI's BrowseComp benchmark for evaluating web-browsing agents.
- [Maxim SDK Core Class](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Maxim): Primary entry point for interacting with the Maxim observability platform.
- [SDK HTTP Agent Quickstart](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-http/quickstart): Guide to quickly get started with agent evaluations via HTTP endpoints using Maxim SDK.
- [Frontend Software Engineer](https://www.getmaxim.ai/jobs/frontend-software-engineer): Job opening for a Frontend Software Engineer role at Maxim AI in Bangalore, India.
- [Simulation Runs](https://www.getmaxim.ai/docs/simulations/simulation-runs): Test AI conversational abilities with scenario-based simulations.
- [Using a Jury of LLMs Instead of a Single Judge to Evaluate LLM Generations](https://www.getmaxim.ai/blog/llm-as-a-jury): Explores the use of a panel of smaller LLMs for unbiased and cost-effective evaluation of AI outputs.
- [Understanding Jailbreaking and Prompt-Based Injections](https://www.getmaxim.ai/blog/jailbreaking-prompt-injection): Explores the risks and mechanisms of jailbreaking and prompt injection attacks in large language models.
- [Akshay Deo](https://www.getmaxim.ai/blog/author/akshay): Blog page featuring articles authored by Akshay Deo on Maxim AI updates and insights.
- [Evaluating RAG performance: Metrics and benchmarks](https://www.getmaxim.ai/blog/rag-evaluation-metrics): A detailed blog on evaluating Retrieval-Augmented Generation (RAG) systems using metrics and benchmarks.
- [KNOWHALU: Hallucination detection via multi-form knowledge-based factual checking](https://www.getmaxim.ai/blog/knowhalu-llm-fact-check): Explores KnowHalu, a novel approach to detecting hallucinations in LLM-generated text.
- [Maxim SDK Overview](https://www.getmaxim.ai/docs/sdk/overview): Introduction to Maxim SDK for AI application development.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/page/13): A collection of recent blog posts on AI advancements and Maxim AI updates.
- [Building and Evaluating a Reddit Insights Agent with Gumloop and Maxim AI](https://www.getmaxim.ai/blog/building-and-evaluating-a-reddit-insights-agent-with-gumloop-and-maxim-ai-2): A detailed guide on building and evaluating a Reddit insights agent using Gumloop and Maxim AI.
- [Bifrost](https://www.getmaxim.ai/bifrost): High-performance LLM gateway connecting multiple AI providers through a single API.
- [User Simulation in AI: From Rule-Based Models to LLM-Powered Realism](https://www.getmaxim.ai/blog/user-simulation-in-ai-from-rule-based-models-to-llm-powered-realism): Explores the evolution of user simulation in AI, from rule-based models to LLM-powered realism.