Superpipe Alternatives

Build, test, and deploy Large Language Model pipelines on your own infrastructure, optimizing results with multistep pipelines, dataset management, and experimentation tracking.
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Flowise

If you're looking for another Superpipe alternative, Flowise is worth a look. It's an open-source, low-code tool that lets developers create their own Large Language Model (LLM) orchestration flows and AI agents. With its graphical interface, more than 100 integrations and ability to self-host on major cloud providers, Flowise is designed to make it easy to create and integrate sophisticated LLM apps, whether you're generating product catalogs or running in air-gapped environments.

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Langfuse

Another good alternative is Langfuse, an open-source foundation for debugging, analyzing and iterating on LLM apps. Langfuse has features like tracing, prompt management and detailed analytics, and supports integrations with major LLM providers. It's also got security certifications like SOC 2 Type II and ISO 27001, and offers tiered pricing including a free hobby tier and a pro version for unlimited data usage.

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Lamini

If you're looking for something more geared for the enterprise, check out Lamini. It's geared for software teams that want to build, manage and deploy LLMs on their own data. Lamini has features like memory tuning, deployment on different environments and high-throughput inference, and can be installed on-premise or in the cloud. It also can scale to thousands of LLMs and offers free and enterprise tiers.

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Humanloop

Last, Humanloop is a platform for managing and optimizing LLM development. It's designed to address issues like suboptimal workflows and manual evaluation with its collaborative prompt management system and evaluation and monitoring suite. Humanloop integrates with popular LLM providers and offers Python and TypeScript SDKs, so it's good for product teams, developers and anyone building AI features.

More Alternatives to Superpipe

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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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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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LLMStack

Build sophisticated AI applications by chaining multiple large language models, importing diverse data types, and leveraging no-code development.

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Velvet

Record, query, and train large language model requests with fine-grained data access, enabling efficient analysis, testing, and iteration of AI features.

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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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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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AnythingLLM

Unlock flexible AI-driven document processing and analysis with customizable LLM integration, ensuring 100% data privacy and control.

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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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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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GradientJ

Automates complex back office tasks, such as medical billing and data onboarding, by training computers to process and integrate unstructured data from various sources.

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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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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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LlamaIndex

Connects custom data sources to large language models, enabling easy integration into production-ready applications with support for 160+ data sources.

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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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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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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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LM Studio

Run any Hugging Face-compatible model with a simple, powerful interface, leveraging your GPU for better performance, and discover new models offline.

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LangChain

Create and deploy context-aware, reasoning applications using company data and APIs, with tools for building, monitoring, and deploying LLM-based applications.

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HoneyHive

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

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SciPhi

Streamline Retrieval-Augmented Generation system development with flexible infrastructure management, scalable compute resources, and cutting-edge techniques for AI innovation.