Manot Alternatives

Automates 80% of the feedback loop, aggregating end-user feedback to identify and resolve model accuracy issues, improving product reliability and team productivity.
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Humanloop

If you're looking for a Manot alternative, Humanloop is a good choice. This service is geared for managing and optimizing Large Language Model (LLM) development, and it's designed to address some of the pain points that can come with LLMs, like suboptimal workflows and manual evaluation. It includes a collaborative prompt management interface, an evaluation and monitoring interface, and customization and optimization tools. Humanloop integrates with major LLM suppliers and offers a variety of SDKs for integration, so it's good for product teams, developers and anyone else building AI features.

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Freeplay

Another option is Freeplay, a lifecycle management tool for LLM product development. It automates the development process with tools like prompt management, automated batch testing, AI auto-evaluations and human labeling. Freeplay offers a unified interface for teams with lightweight SDKs for Python, Node and Java, and multiple deployment options. It's geared for enterprise teams that want to move beyond manual processes and speed up development.

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Klu

If you're focused on building, deploying and optimizing generative AI applications, Klu is another option. Klu supports multiple LLMs and offers features like fast iteration, built-in analytics and custom model support. It offers tools for collaboration on prompts, automated prompt engineering and performance monitoring, which can help AI engineers and teams iterate faster based on model, prompt and user feedback.

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Parea

Another option is Parea, which offers a wide range of tools for AI teams to ship LLM applications with confidence. Parea includes experiment tracking, observability, human annotation tools and a prompt playground for testing multiple prompts on large datasets. The service integrates with popular LLM providers and frameworks and offers several pricing tiers, including a free builder plan and an enterprise plan for larger teams.

More Alternatives to Manot

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Deepchecks

Automates LLM app evaluation, identifying issues like hallucinations and bias, and provides in-depth monitoring and debugging to ensure high-quality applications.

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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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Langfuse

Debug, analyze, and experiment with large language models through tracing, prompt management, evaluation, analytics, and a playground for testing and optimization.

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Chai AI

Crowdsourced conversational AI development platform connecting creators and users, fostering engaging conversations through user feedback and model training.

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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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Langtail

Streamline AI app development with a suite of tools for debugging, testing, and deploying LLM prompts, ensuring faster iteration and more predictable outcomes.

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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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Promptfoo

Assess large language model output quality with customizable metrics, multiple provider support, and a command-line interface for easy integration and improvement.

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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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Prem

Accelerate personalized Large Language Model deployment with a developer-friendly environment, fine-tuning, and on-premise control, ensuring data sovereignty and customization.

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Baseplate

Links and manages data for Large Language Model tasks, enabling efficient embedding, storage, and versioning for high-performance AI app development.

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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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MonsterGPT

Fine-tune and deploy large language models with a chat interface, simplifying the process and reducing technical setup requirements for developers.

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LLM Explorer

Discover and compare 35,809 open-source language models by filtering parameters, benchmark scores, and memory usage, and explore categorized lists and model details.

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Metatext

Build and manage custom NLP models fine-tuned for your specific use case, automating workflows through text classification, tagging, and generation.

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Vellum

Manage the full lifecycle of LLM-powered apps, from selecting prompts and models to deploying and iterating on them in production, with a suite of integrated tools.

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LangWatch

Ensures quality and safety of generative AI solutions with strong guardrails, monitoring, and optimization to prevent risks and hallucinations.

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Meta Llama

Accessible and responsible AI development with open-source language models for various tasks, including programming, translation, and dialogue generation.

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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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HoneyHive

Collaborative LLMOps environment for testing, evaluating, and deploying GenAI applications, with features for observability, dataset management, and prompt optimization.