Question: I need a platform that helps my team experiment, measure, and optimize our AI applications, can you suggest one?

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Athina

If you want a platform to experiment, measure and optimize your AI work, Athina is worth a look. It's an end-to-end solution for GenAI teams that supports popular frameworks and offers real-time monitoring, cost tracking and customizable alerts. Among its features are LLM Observability, Experimentation, Analytics and Insights, as well as multiple workspaces and custom models. Athina's tiered pricing is designed for teams of all sizes, so it's a good option for teams trying to accelerate AI development.

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Statsig

Another good option is Statsig, a full-stack feature management and experimentation platform. Statsig helps teams speed up experimentation velocity and ship features with data-driven confidence. Its main products are Experiments for automated analysis, Feature Flags for controlling feature releases, and Analytics for data-driven decisions. It also offers Session Replays for visibility into user behavior and supports multiple pricing tiers, including a free Developer plan.

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HoneyHive

If you're more interested in AI evaluation and testing, HoneyHive is a mission-critical option. It's a single LLMOps environment for collaboration, testing and evaluation of AI applications, with features like automated CI testing, production pipeline monitoring, dataset curation and prompt management. HoneyHive supports 100+ models and has a customizable Enterprise plan, so it's good for teams that need a more comprehensive AI development and deployment tool.

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Humanloop

Last, consider Humanloop, a platform for managing and optimizing LLM applications. It's designed to help you overcome common problems like inefficient workflows and manual evaluation with its collaborative prompt management and evaluation suite. Humanloop supports common LLM providers, offers integration SDKs, and offers a free tier for prototyping and an Enterprise tier for larger-scale use. That makes it a good choice for teams that want to make their AI development more efficient and reliable.

Additional AI Projects

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Freeplay

Streamline large language model product development with a unified platform for experimentation, testing, monitoring, and optimization, accelerating development velocity and improving quality.

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MLflow

Manage the full lifecycle of ML projects, from experimentation to production, with a single environment for tracking, visualizing, and deploying models.

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LastMile AI

Streamline generative AI application development with automated evaluators, debuggers, and expert support, enabling confident productionization and optimal performance.

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Parea

Confidently deploy large language model applications to production with experiment tracking, observability, and human annotation tools.

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Openlayer

Build and deploy high-quality AI models with robust testing, evaluation, and observability tools, ensuring reliable performance and trustworthiness in production.

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Anyscale

Instantly build, run, and scale AI applications with optimal performance and efficiency, leveraging automatic resource allocation and smart instance management.

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Dataloop

Unify data, models, and workflows in one environment, automating pipelines and incorporating human feedback to accelerate AI application development and improve quality.

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Abacus.AI

Build and deploy custom AI agents and systems at scale, leveraging generative AI and novel neural network techniques for automation and prediction.

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Keywords AI

Streamline AI application development with a unified platform offering scalable API endpoints, easy integration, and optimized tools for development and monitoring.

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Klu

Streamline generative AI application development with collaborative prompt engineering, rapid iteration, and built-in analytics for optimized model fine-tuning.

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Clarifai

Rapidly develop, deploy, and operate AI projects at scale with automated workflows, standardized development, and built-in security and access controls.

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Dataiku

Systemize data use for exceptional business results with a range of features supporting Generative AI, data preparation, machine learning, MLOps, collaboration, and governance.

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Predibase

Fine-tune and serve large language models efficiently and cost-effectively, with features like quantization, low-rank adaptation, and memory-efficient distributed training.

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Instill

Automates data, model, and pipeline orchestration for generative AI, freeing teams to focus on AI use cases, with 10x faster app development.

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AirOps

Create sophisticated LLM workflows combining custom data with 40+ AI models, scalable to thousands of jobs, with integrations and human oversight.

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TeamAI

Collaborative AI workspaces unite teams with shared prompts, folders, and chat histories, streamlining workflows and amplifying productivity.

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Airtrain AI

Experiment with 27+ large language models, fine-tune on your data, and compare results without coding, reducing costs by up to 90%.

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PI.EXCHANGE

Build predictive machine learning models without coding, leveraging an end-to-end pipeline for data preparation, model development, and deployment in a collaborative environment.

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Athena

Accelerate analytics workflows with an AI-native platform that learns your workflow, automates tasks, and enables collaborative data analysis with natural language interaction.

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SuperAnnotate

Streamlines dataset creation, curation, and model evaluation, enabling users to build, fine-tune, and deploy high-performing AI models faster and more accurately.