Alternatives to Kitten Stack
Compare Kitten Stack alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Kitten Stack in 2026. Compare features, ratings, user reviews, pricing, and more from Kitten Stack competitors and alternatives in order to make an informed decision for your business.
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1
Vertex AI
Google
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex. -
2
LM-Kit.NET
LM-Kit
LM-Kit.NET is a cutting-edge, high-level inference SDK designed specifically to bring the advanced capabilities of Large Language Models (LLM) into the C# ecosystem. Tailored for developers working within .NET, LM-Kit.NET provides a comprehensive suite of powerful Generative AI tools, making it easier than ever to integrate AI-driven functionality into your applications. The SDK is versatile, offering specialized AI features that cater to a variety of industries. These include text completion, Natural Language Processing (NLP), content retrieval, text summarization, text enhancement, language translation, and much more. Whether you are looking to enhance user interaction, automate content creation, or build intelligent data retrieval systems, LM-Kit.NET offers the flexibility and performance needed to accelerate your project. -
3
RunPod
RunPod
RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure. -
4
BentoML
BentoML
Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.Starting Price: Free -
5
Amazon SageMaker
Amazon
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers. -
6
Mistral AI
Mistral AI
Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.Starting Price: Free -
7
Vercel
Vercel
Vercel is an AI-powered cloud platform that helps developers build, deploy, and scale high-performance web experiences with speed and security. It provides a unified set of tools, templates, and infrastructure designed to streamline development workflows from idea to global deployment. With support for modern frameworks like Next.js, Svelte, Vite, and Nuxt, teams can ship fast, responsive applications without managing complex backend operations. Vercel’s AI Cloud includes an AI Gateway, SDKs, workflow automation tools, and fluid compute, enabling developers to integrate large language models and advanced AI features effortlessly. The platform emphasizes instant global distribution, enabling deployments to become available worldwide immediately after a git push. Backed by strong security and performance optimizations, Vercel helps companies deliver personalized, reliable digital experiences at massive scale. -
8
TensorFlow
TensorFlow
An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.Starting Price: Free -
9
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
10
Vertesia
Vertesia
Vertesia is a unified, low-code generative AI platform that enables enterprise teams to rapidly build, deploy, and operate GenAI applications and agents at scale. Designed for both business professionals and IT specialists, Vertesia offers a frictionless development experience, allowing users to go from prototype to production without extensive timelines or heavy infrastructure. It supports multiple generative AI models from leading inference providers, providing flexibility and preventing vendor lock-in. Vertesia's agentic retrieval-augmented generation (RAG) pipeline enhances generative AI accuracy and performance by automating and accelerating content preparation, including intelligent document processing and semantic chunking. With enterprise-grade security, SOC2 compliance, and support for leading cloud infrastructures like AWS, GCP, and Azure, Vertesia ensures secure and scalable deployments. -
11
Breeder Cloud Pro
BreederCloud Pro
Easily view upcoming heats, upcoming litters and manage scheduled appointments for your puppies or kittens. Receive text or email reminders when it's time for your puppies or kittens next appointments & create waiting lists for interested clients. Enjoy quick access to manage your dogs or cats medical records and more from your desktop & mobile device. Store medical records, reports, photos and more for every dog, cat, litter and contact with no storage limits. Manage your litters the easy way & create medical reports or manage owners for your puppies or kittens. Enter your kennel expenses & puppy or kitten sales with month-to-month growth charts and profits at a glance. Search our existing & continually growing database to find your dogs or cats pedigree for up to 5 generations. Create your own website & photo galleries to promote your kennel.Starting Price: $4.99 per month -
12
Amazon Bedrock
Amazon
Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices. -
13
Wyvern Protocol
Wyvern Protocol
Trade any kind of digital asset — from rare virtual kittens to ENS names, land rights, or even smart contracts themselves. Wyvern Protocol powers the peer-to-peer exchange of digital assets. Trade any kind of non-fungible asset — from rare virtual kittens to ENS names, land rights, or even smart contracts. Wyvern can be deployed on any EVM-based blockchain, allowing developers to power their asset exchange. The Wyvern Protocol codebase is open source, permissively licensed, and third-party audited. Pick whichever method of sale you prefer: fixed price, Dutch auction, or something more exotic. Interface with the Exchange through a website, a mobile application, or a custom script. Trade any kind of non-fungible asset — from rare virtual kittens to ENS names, land rights, or even smart contracts. Trade ERC20 tokens, ERC721 NFTs, or custom assets in any combination. -
14
Orq.ai
Orq.ai
Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security. -
15
FPT AI Factory
FPT Cloud
FPT AI Factory is a comprehensive, enterprise-grade AI development platform built on NVIDIA H100 and H200 superchips, offering a full-stack solution that spans the entire AI lifecycle, FPT AI Infrastructure delivers high-performance, scalable GPU resources for rapid model training; FPT AI Studio provides data hubs, AI notebooks, model pre‑training, fine‑tuning pipelines, and model hub for streamlined experimentation and development; FPT AI Inference offers production-ready model serving and “Model-as‑a‑Service” for real‑world applications with low latency and high throughput; and FPT AI Agents, a GenAI agent builder, enables the creation of adaptive, multilingual, multitasking conversational agents. Integrated with ready-to-deploy generative AI solutions and enterprise tools, FPT AI Factory empowers businesses to innovate quickly, deploy reliably, and scale AI workloads from proof-of-concept to operational systems.Starting Price: $2.31 per hour -
16
Mongoose
Mongoose
Let's face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That's why we wrote Mongoose. Now say we like fuzzy kittens and want to record every kitten we ever meet in MongoDB. The first thing we need to do is include mongoose in our project and open a connection to the test database on our locally running instance of MongoDB. We have a pending connection to the test database running on localhost. We now need to get notified if we connect successfully or if a connection error occurs. Mongoose documents represent a one-to-one mapping to documents as stored in MongoDB. Each document is an instance of its Model. Subdocuments are documents embedded in other documents. In Mongoose, this means you can nest schemas in other schemas. Mongoose has two distinct notions of subdocuments: arrays of subdocuments and single nested subdocuments. -
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Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. Built on Amazon DataZone, it integrates various AWS analytics and AI/ML services, such as Amazon EMR, AWS Glue, and Amazon Bedrock, into a single platform. Users can discover, access, and process data from various sources like Amazon S3 and Redshift, and develop generative AI applications. With tools for model development, governance, MLOps, and AI customization, SageMaker Unified Studio provides an efficient, secure, and collaborative environment for data teams.
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18
Dify
Dify
Dify is an open-source platform designed to streamline the development and operation of generative AI applications. It offers a comprehensive suite of tools, including an intuitive orchestration studio for visual workflow design, a Prompt IDE for prompt testing and refinement, and enterprise-level LLMOps capabilities for monitoring and optimizing large language models. Dify supports integration with various LLMs, such as OpenAI's GPT series and open-source models like Llama, providing flexibility for developers to select models that best fit their needs. Additionally, its Backend-as-a-Service (BaaS) features enable seamless incorporation of AI functionalities into existing enterprise systems, facilitating the creation of AI-powered chatbots, document summarization tools, and virtual assistants. -
19
RAGFlow
RAGFlow
RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine that enhances information retrieval by combining Large Language Models (LLMs) with deep document understanding. It offers a streamlined RAG workflow suitable for businesses of any scale, providing truthful question-answering capabilities backed by well-founded citations from various complex formatted data. Key features include template-based chunking, compatibility with heterogeneous data sources, and automated RAG orchestration.Starting Price: Free -
20
IBM watsonx.ai
IBM
Now available—a next generation enterprise studio for AI builders to train, validate, tune and deploy AI models IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI (gen AI) capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers: End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides. Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice. -
21
Supavec
Supavec
Supavec is an open source Retrieval-Augmented Generation (RAG) platform designed to help developers build powerful AI applications that integrate seamlessly with any data source, regardless of scale. As an alternative to Carbon.ai, Supavec offers full control over your AI infrastructure, allowing you to choose between a cloud version or self-hosting on your own systems. Built with technologies like Supabase, Next.js, and TypeScript, Supavec ensures scalability, enabling the handling of millions of documents with support for concurrent processing and horizontal scaling. The platform emphasizes enterprise-grade privacy by utilizing Supabase Row Level Security (RLS), ensuring that your data remains private and secure with granular access control. Developers benefit from a simple API, comprehensive documentation, and easy integration, facilitating quick setup and deployment of AI applications.Starting Price: Free -
22
Microsoft Foundry
Microsoft
Microsoft Foundry is an end-to-end platform for building, optimizing, and governing AI apps and agents at scale. It gives developers access to more than 11,000 models — from foundational to multimodal — all available through one unified interface. With a simple, interoperable API and SDK, teams can build faster, ship confidently, and reduce integration complexity. Foundry connects seamlessly with your business systems, enabling AI solutions that understand your data and operate securely across your organization. Built-in governance, monitoring, and fleetwide controls ensure responsible AI deployment from day one. Microsoft Foundry helps companies turn AI into real business impact with speed, security, and precision. -
23
Intel Open Edge Platform
Intel
The Intel Open Edge Platform simplifies the development, deployment, and scaling of AI and edge computing solutions on standard hardware with cloud-like efficiency. It provides a curated set of components and workflows that accelerate AI model creation, optimization, and application development. From vision models to generative AI and large language models (LLM), the platform offers tools to streamline model training and inference. By integrating Intel’s OpenVINO toolkit, it ensures enhanced performance on Intel CPUs, GPUs, and VPUs, allowing organizations to bring AI applications to the edge with ease. -
24
Ragie
Ragie
Ragie streamlines data ingestion, chunking, and multimodal indexing of structured and unstructured data. Connect directly to your own data sources, ensuring your data pipeline is always up-to-date. Built-in advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search help you deliver state-of-the-art generative AI. Connect directly to popular data sources like Google Drive, Notion, Confluence, and more. Automatic syncing keeps your data up-to-date, ensuring your application delivers accurate and reliable information. With Ragie connectors, getting your data into your AI application has never been simpler. With just a few clicks, you can access your data where it already lives. Automatic syncing keeps your data up-to-date ensuring your application delivers accurate and reliable information. The first step in a RAG pipeline is to ingest the relevant data. Use Ragie’s simple APIs to upload files directly.Starting Price: $500 per month -
25
Hugging Face
Hugging Face
Hugging Face is a leading platform for AI and machine learning, offering a vast hub for models, datasets, and tools for natural language processing (NLP) and beyond. The platform supports a wide range of applications, from text, image, and audio to 3D data analysis. Hugging Face fosters collaboration among researchers, developers, and companies by providing open-source tools like Transformers, Diffusers, and Tokenizers. It enables users to build, share, and access pre-trained models, accelerating AI development for a variety of industries.Starting Price: $9 per month -
26
Predibase
Predibase
Declarative machine learning systems provide the best of flexibility and simplicity to enable the fastest-way to operationalize state-of-the-art models. Users focus on specifying the “what”, and the system figures out the “how”. Start with smart defaults, but iterate on parameters as much as you’d like down to the level of code. Our team pioneered declarative machine learning systems in industry, with Ludwig at Uber and Overton at Apple. Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage. Train state-of-the-art deep learning models without the pain of managing infrastructure. Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion. With a declarative approach, finally train and deploy models as quickly as you want. -
27
FastGPT
FastGPT
FastGPT is a free, open source AI knowledge base platform that offers out-of-the-box data processing, model invocation, retrieval-augmented generation retrieval, and visual AI workflows, enabling users to easily build complex large language model applications. It allows the creation of domain-specific AI assistants by training models with imported documents or Q&A pairs, supporting various formats such as Word, PDF, Excel, Markdown, and web links. The platform automates data preprocessing tasks, including text preprocessing, vectorization, and QA segmentation, enhancing efficiency. FastGPT supports AI workflow orchestration through a visual drag-and-drop interface, facilitating the design of complex workflows that integrate tasks like database queries and inventory checks. It also offers seamless API integration with existing GPT applications and platforms like Discord, Slack, and Telegram using OpenAI-aligned APIs.Starting Price: $0.37 per month -
28
Mixedbread
Mixedbread
Mixedbread is a fully-managed AI search engine that allows users to build production-ready AI search and Retrieval-Augmented Generation (RAG) applications. It offers a complete AI search stack, including vector stores, embedding and reranking models, and document parsing. Users can transform raw data into intelligent search experiences that power AI agents, chatbots, and knowledge systems without the complexity. It integrates with tools like Google Drive, SharePoint, Notion, and Slack. Its vector stores enable users to build production search engines in minutes, supporting over 100 languages. Mixedbread's embedding and reranking models have achieved over 50 million downloads and outperform OpenAI in semantic search and RAG tasks while remaining open-source and cost-effective. The document parser extracts text, tables, and layouts from PDFs, images, and complex documents, providing clean, AI-ready content without manual preprocessing. -
29
Deeploy
Deeploy
Deeploy helps you to stay in control of your ML models. Easily deploy your models on our responsible AI platform, without compromising on transparency, control, and compliance. Nowadays, transparency, explainability, and security of AI models is more important than ever. Having a safe and secure environment to deploy your models enables you to continuously monitor your model performance with confidence and responsibility. Over the years, we experienced the importance of human involvement with machine learning. Only when machine learning systems are explainable and accountable, experts and consumers can provide feedback to these systems, overrule decisions when necessary and grow their trust. That’s why we created Deeploy. -
30
Arcee AI
Arcee AI
Optimizing continual pre-training for model enrichment with proprietary data. Ensuring that domain-specific models offer a smooth experience. Creating a production-friendly RAG pipeline that offers ongoing support. With Arcee's SLM Adaptation system, you do not have to worry about fine-tuning, infrastructure set-up, and all the other complexities involved in stitching together solutions using a plethora of not-built-for-purpose tools. Thanks to the domain adaptability of our product, you can efficiently train and deploy your own SLMs across a plethora of use cases, whether it is for internal tooling, or for your customers. By training and deploying your SLMs with Arcee’s end-to-end VPC service, you can rest assured that what is yours, stays yours. -
31
AnyAPI
AnyAPI.ai
AnyAPI is a unified API platform that provides instant access to the world’s leading AI models through a single integration. It allows developers to connect to models from OpenAI, Anthropic, Google, xAI, Mistral, and more using one consistent request format. With minimal setup, teams can power applications with advanced AI in minutes. AnyAPI supports multiple programming languages and works seamlessly with existing tech stacks. Built for performance, the platform delivers low latency, high uptime, and enterprise-grade reliability. Developers can experiment with models using an AI playground before deploying to production. AnyAPI simplifies AI integration so teams can focus on building, not infrastructure.Starting Price: $39/month -
32
Entry Point AI
Entry Point AI
Entry Point AI is the modern AI optimization platform for proprietary and open source language models. Manage prompts, fine-tunes, and evals all in one place. When you reach the limits of prompt engineering, it’s time to fine-tune a model, and we make it easy. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to leverage the full potential of AI models. Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself. For simpler tasks, you can train a lighter model to perform at or above the level of a higher-quality model, greatly reducing latency and cost. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to get the formatting right. Cover edge cases and steer model behavior by adding examples to your dataset.Starting Price: $49 per month -
33
Graphlit
Graphlit
Whether you're building an AI copilot, or chatbot, or enhancing your existing application with LLMs, Graphlit makes it simple. Built on a serverless, cloud-native platform, Graphlit automates complex data workflows, including data ingestion, knowledge extraction, LLM conversations, semantic search, alerting, and webhook integrations. Using Graphlit's workflow-as-code approach, you can programmatically define each step in the content workflow. From data ingestion through metadata indexing and data preparation; from data sanitization through entity extraction and data enrichment. And finally through integration with your applications with event-based webhooks and API integrations.Starting Price: $49 per month -
34
LlamaCloud
LlamaIndex
LlamaCloud, developed by LlamaIndex, is a fully managed service for parsing, ingesting, and retrieving data, enabling companies to create and deploy AI-driven knowledge applications. It provides a flexible and scalable pipeline for handling data in Retrieval-Augmented Generation (RAG) scenarios. LlamaCloud simplifies data preparation for LLM applications, allowing developers to focus on building business logic instead of managing data. -
35
LMCache
LMCache
LMCache is an open source Knowledge Delivery Network (KDN) designed as a caching layer for large language model serving that accelerates inference by reusing KV (key-value) caches across repeated or overlapping computations. It enables fast prompt caching, allowing LLMs to “prefill” recurring text only once and then reuse those stored KV caches, even in non-prefix positions, across multiple serving instances. This approach reduces time to first token, saves GPU cycles, and increases throughput in scenarios such as multi-round question answering or retrieval augmented generation. LMCache supports KV cache offloading (moving cache from GPU to CPU or disk), cache sharing across instances, and disaggregated prefill, which separates the prefill and decoding phases for resource efficiency. It is compatible with inference engines like vLLM and TGI and supports compressed storage, blending techniques to merge caches, and multiple backend storage options.Starting Price: Free -
36
Azure Machine Learning
Microsoft
Accelerate the end-to-end machine learning lifecycle with Azure Machine Learning Studio. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R. -
37
Fetch Hive
Fetch Hive
Fetch Hive is a versatile Generative AI Collaboration Platform packed with features and values that enhance user experience and productivity: Custom RAG Chat Agents: Users can create chat agents with retrieval-augmented generation, which improves response quality and relevance. Centralized Data Storage: It provides a system for easily accessing and managing all necessary data for AI model training and deployment. Real-Time Data Integration: By incorporating real-time data from Google Search, Fetch Hive enhances workflows with up-to-date information, boosting decision-making and productivity. Generative AI Prompt Management: The platform helps in building and managing AI prompts, enabling users to refine and achieve desired outputs efficiently. Fetch Hive is a comprehensive solution for those looking to develop and manage generative AI projects effectively, optimizing interactions with advanced features and streamlined workflows.Starting Price: $49/month -
38
Alibaba Cloud Model Studio
Alibaba
Model Studio is Alibaba Cloud’s one-stop generative AI platform that lets developers build intelligent, business-aware applications using industry-leading foundation models like Qwen-Max, Qwen-Plus, Qwen-Turbo, the Qwen-2/3 series, visual-language models (Qwen-VL/Omni), and the video-focused Wan series. Users can access these powerful GenAI models through familiar OpenAI-compatible APIs or purpose-built SDKs, no infrastructure setup required. It supports a full development workflow, experiment with models in the playground, perform real-time and batch inferences, fine-tune with tools like SFT or LoRA, then evaluate, compress, accelerate deployment, and monitor performance, all within an isolated Virtual Private Cloud (VPC) for enterprise-grade security. Customization is simplified via one-click Retrieval-Augmented Generation (RAG), enabling integration of business data into model outputs. Visual, template-driven interfaces facilitate prompt engineering and application design. -
39
Scale GenAI Platform
Scale AI
Build, test, and optimize Generative AI applications that unlock the value of your data. Optimize LLM performance for your domain-specific use cases with our advanced retrieval augmented generation (RAG) pipelines, state-of-the-art test and evaluation platform, and our industry-leading ML expertise. We help deliver value from AI investments faster with better data by providing an end-to-end solution to manage the entire ML lifecycle. Combining cutting edge technology with operational excellence, we help teams develop the highest-quality datasets because better data leads to better AI. -
40
Baseten
Baseten
Baseten is a high-performance platform designed for mission-critical AI inference workloads. It supports serving open-source, custom, and fine-tuned AI models on infrastructure built specifically for production scale. Users can deploy models on Baseten’s cloud, their own cloud, or in a hybrid setup, ensuring flexibility and scalability. The platform offers inference-optimized infrastructure that enables fast training and seamless developer workflows. Baseten also provides specialized performance optimizations tailored for generative AI applications such as image generation, transcription, text-to-speech, and large language models. With 99.99% uptime, low latency, and support from forward deployed engineers, Baseten aims to help teams bring AI products to market quickly and reliably.Starting Price: Free -
41
Klee
Klee
Local and secure AI on your desktop, ensuring comprehensive insights with complete data security and privacy. Experience unparalleled efficiency, privacy, and intelligence with our cutting-edge macOS-native app and advanced AI features. RAG can utilize data from a local knowledge base to supplement the large language model (LLM). This means you can keep sensitive data on-premises while leveraging it to enhance the model‘s response capabilities. To implement RAG locally, you first need to segment documents into smaller chunks and then encode these chunks into vectors, storing them in a vector database. These vectorized data will be used for subsequent retrieval processes. When a user query is received, the system retrieves the most relevant chunks from the local knowledge base and inputs these chunks along with the original query into the LLM to generate the final response. We promise lifetime free access for individual users. -
42
TopK
TopK
TopK is a serverless, cloud-native, document database built for powering search applications. It features native support for both vector search (vectors are simply another data type) and keyword search (BM25-style) in a single, unified system. With its powerful query expression language, TopK enables you to build reliable search applications (semantic search, RAG, multi-modal, you name it) without juggling multiple databases or services. Our unified retrieval engine will evolve to support document transformation (automatically generate embeddings), query understanding (parse metadata filters from user query), and adaptive ranking (provide more relevant results by sending “relevance feedback” back to TopK) under one unified roof. -
43
Crewship
Crewship
Crewship is the developer-first platform for deploying AI agent workflows. Deploy your CrewAI, LangGraph, and LangGraph.js agents with a single command and watch them execute in real-time. Key features include one-command deployment, real-time execution streaming, artifact management, auto-scaling, version control, and encrypted secrets management. Crewship handles infrastructure so developers can focus on building great AI agents. Multi-framework support with AutoGen, Pydantic AI, smolagents, OpenAI Agents, Mastra, and Agno coming soon.Starting Price: Free -
44
Byne
Byne
Retrieval-augmented generation, agents, and more start building in the cloud and deploying on your server. We charge a flat fee per request. There are two types of requests: document indexation and generation. Document indexation is the addition of a document to your knowledge base. Document indexation, which is the addition of a document to your knowledge base and generation, which creates LLM writing based on your knowledge base RAG. Build a RAG workflow by deploying off-the-shelf components and prototype a system that works for your case. We support many auxiliary features, including reverse tracing of output to documents, and ingestion for many file formats. Enable the LLM to use tools by leveraging Agents. An Agent-powered system can decide which data it needs and search for it. Our implementation of agents provides a simple hosting for execution layers and pre-build agents for many use cases.Starting Price: 2¢ per generation request -
45
SciPhi
SciPhi
Intuitively build your RAG system with fewer abstractions compared to solutions like LangChain. Choose from a wide range of hosted and remote providers for vector databases, datasets, Large Language Models (LLMs), application integrations, and more. Use SciPhi to version control your system with Git and deploy from anywhere. The platform provided by SciPhi is used internally to manage and deploy a semantic search engine with over 1 billion embedded passages. The team at SciPhi will assist in embedding and indexing your initial dataset in a vector database. The vector database is then integrated into your SciPhi workspace, along with your selected LLM provider.Starting Price: $249 per month -
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The Oracle AI Data Platform unifies the complete data-to-insight lifecycle with embedded artificial intelligence, machine learning, and generative capabilities across data stores, analytics, applications, and infrastructure. It supports everything from data ingestion and governance through to feature engineering, model training, and operationalization, enabling organizations to build trusted AI-driven systems at scale. With its integrated architecture, the platform offers native support for vector search, retrieval-augmented generation, and large language models, while enabling secure, auditable access to business data and analytics across enterprise roles. The platform’s analytics layer lets users explore, visualize, and interpret data with AI-powered assistance, where self-service dashboards, natural-language queries, and generative summaries accelerate decision making.
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47
Dynamiq
Dynamiq
Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle. Key features: 🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale 🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes 🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs 📈 Observability: Log all interactions, use large-scale LLM quality evaluations 🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention 📻 Fine-tuning: Fine-tune proprietary LLM models to make them your ownStarting Price: $125/month -
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Backboard
Backboard
Backboard is an AI infrastructure platform that provides a unified API layer giving applications persistent, stateful memory and seamless orchestration across thousands of large language models, built-in retrieval-augmented generation, and long-term context storage so intelligent systems can remember, reason, and act consistently over extended interactions rather than behave like one-off demos. It captures context, interactions, and long-term knowledge, storing and retrieving the right information at the right time while supporting stateful thread management with automatic model switching, hybrid retrieval, and flexible stack configuration so developers can build reliable AI systems without stitching together fragile workarounds. Backboard’s memory system consistently ranks high on industry benchmarks for accuracy, and its API lets teams combine memory, routing, retrieval, and tool orchestration into one stack that reduces architectural complexity.Starting Price: $9 per month -
49
OPAQUE
OPAQUE Systems
OPAQUE Systems offers a leading confidential AI platform that enables organizations to securely run AI, machine learning, and analytics workflows on sensitive data without compromising privacy or compliance. Their technology allows enterprises to unleash AI innovation risk-free by leveraging confidential computing and cryptographic verification, ensuring data sovereignty and regulatory adherence. OPAQUE integrates seamlessly into existing AI stacks via APIs, notebooks, and no-code solutions, eliminating the need for costly infrastructure changes. The platform provides verifiable audit trails and attestation for complete transparency and governance. Customers like Ant Financial have benefited by using previously inaccessible data to improve credit risk models. With OPAQUE, companies accelerate AI adoption while maintaining uncompromising security and control. -
50
TensorBlock
TensorBlock
TensorBlock is an open source AI infrastructure platform designed to democratize access to large language models through two complementary components. It has a self-hosted, privacy-first API gateway that unifies connections to any LLM provider under a single, OpenAI-compatible endpoint, with encrypted key management, dynamic model routing, usage analytics, and cost-optimized orchestration. TensorBlock Studio delivers a lightweight, developer-friendly multi-LLM interaction workspace featuring a plugin-based UI, extensible prompt workflows, real-time conversation history, and integrated natural-language APIs for seamless prompt engineering and model comparison. Built on a modular, scalable architecture and guided by principles of openness, composability, and fairness, TensorBlock enables organizations to experiment, deploy, and manage AI agents with full control and minimal infrastructure overhead.Starting Price: Free
