Modular Alternatives

Long-term memory for AI. The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval. Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results. Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely.

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.

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.

The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications.

Build, deploy, and scale end-to-end AI applications in the cloud. Griptape gives developers everything they need to build, deploy, and scale retrieval-driven AI-powered applications, from the development framework to the execution runtime. 🎢 Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. ☁️ Griptape Cloud is a one-stop shop to hosting your AI structures, whether they are built with Griptape, another framework, or call directly to the LLMs themselves. Simply point to your GitHub repository to get started. 🔥 Run your hosted code by hitting a basic API layer from wherever you need, offloading the expensive tasks of AI development to the cloud. 📈 Automatically scale workloads to fit your needs.

Vercel combines the best developer experience with an obsessive focus on end-user performance. Our platform enables frontend teams to do their best work. Developers love Next.js, the open source React framework Vercel built together with Google and Facebook. Next.js powers the biggest websites like Airbnb, Twilio, and Washington Post, for use cases in e-commerce, travel, news, and marketing. Vercel is the best place to deploy any frontend app. Start by deploying with zero configuration to our global edge network. Scale dynamically to millions of pages without breaking a sweat. Reliable live-editing experience for your UI components. Connect your pages to any data source, headless CMS, or API and make it work in everyone’s dev environment. From caching to Serverless Functions, all our cloud primitives work perfectly on localhost.

Access readily available dedicated machines with pre-configured professional AI development tools, from dependable data centers at competitive prices. From HPC resources to an all-in-one AI platform with an integrated ML development toolkit, Apolo covers it all. Apolo can be deployed in a distributed architecture, as a dedicated enterprise cluster, or as a multi-tenant white-label solution to support dedicated instances or self-service cloud. Right out of the box, Apolo spins up a full-fledged AI-centric development environment with all the tools you need at your fingertips. Apolo manages and automates the infrastructure and processes for successful AI development at scale. Apolo's AI-centric services seamlessly stitch your on-prem and cloud resources, deploy pipelines, and integrate your open-source and commercial development tools. Apolo empowers enterprises with the tools and resources necessary to achieve breakthroughs in AI.

It streamlines development and deployment, reduces cloud costs, and frees users from vendor lock-in. Configure the hardware resources, such as GPU, and memory, and specify your preference for using spot instances. dstack automatically provisions cloud resources, fetches your code, and forwards ports for secure access. Access the cloud dev environment conveniently using your local desktop IDE. Configure the hardware resources you need (GPU, memory, etc.) and indicate whether you want to use spot or on-demand instances. dstack will automatically provision cloud resources and forward ports for secure and convenient access. Pre-train and finetune your own state-of-the-art models easily and cost-effectively in any cloud. Have cloud resources automatically provisioned based on your configuration? Access your data and store output artifacts using declarative configuration or the Python SDK.

Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. A range of NVIDIA GPUs to help with cost-effective inference or scale-up or scale-out training. Leverage RAPID and Spark with GPUs to execute deep learning. Run GPU workloads on Google Cloud where you have access to industry-leading storage, networking, and data analytics technologies. Access CPU platforms when you start a VM instance on Compute Engine. Compute Engine offers a range of both Intel and AMD processors for your VMs.

Enterprise-ready AI system that trains locally on your data, deploys on your cloud and scales to millions of users without an engineering team. Build customize and deploy your own chat-based AI. Finance chatbot. xFinance, a 13-billion parameter model fine-tuned on an open-source model using LoRA. Our goal was to show that it is possible to achieve impressive results in financial NLP tasks without breaking the bank. Personal AI assistant, your own AI to chat with your documents. Single or multiple documents, easy or complex questions, and much more. Effortless deep learning platform for enterprises, hardware efficient algorithms to speed up inference at a lower cost. Real-time logging and monitoring of resource utilization and cloud costs of deployed models. xTuring is an open-source AI personalization software. xTuring makes it easy to build and control LLMs by providing a simple interface to personalize LLMs to your own data and application.

Ship AI faster with managed, cloud-hosted AI packages. Full, built-in support for GPT-4. No API tokens are necessary. Build with our low code framework. Integrations with all major models are built-in. Deploy for an instant API. Scale and share without managing infrastructure. Turn prompts, prompt chains, and basic Python into a managed API. Turn a clever prompt into a published API you can share. Add logic and routing smarts with Python. Steamship connects to your favorite models and services so that you don't have to learn a new API for every provider. Steamship persists in model output in a standardized format. Consolidate training, inference, vector search, and endpoint hosting. Import, transcribe, or generate text. Run all the models you want on it. Query across the results with ShipQL. Packages are full-stack, cloud-hosted AI apps. Each instance you create provides an API and private data workspace.

The Granica AI efficiency platform reduces the cost to store and access data while preserving its privacy to unlock it for training. Granica is developer-first, petabyte-scale, and AWS/GCP-native. Granica makes AI pipelines more efficient, privacy-preserving, and more performant. Efficiency is a new layer in the AI stack. Byte-granular data reduction uses novel compression algorithms, cutting costs to store and transfer objects in Amazon S3 and Google Cloud Storage by up to 80% and API costs by up to 90%. Estimate in 30 mins in your cloud environment, on a read-only sample of your S3/GCS data. No need for budget allocation or total cost of ownership analysis. Granica deploys into your environment and VPC, respecting all of your security policies. Granica supports a wide range of data types for AI/ML/analytics, with lossy and fully lossless compression variants. Detect and protect sensitive data even before it is persisted into your cloud object store.

The Intel Distribution of OpenVINO toolkit makes it simple to adopt and maintain your code. Open Model Zoo provides optimized, pretrained models and Model Optimizer API parameters make it easier to convert your model and prepare it for inferencing. The runtime (inference engine) allows you to tune for performance by compiling the optimized network and managing inference operations on specific devices. It also auto-optimizes through device discovery, load balancing, and inferencing parallelism across CPU, GPU, and more. Deploy your same application across combinations of host processors and accelerators (CPUs, GPUs, VPUs) and environments (on-premise, on-device, in the browser, or in the cloud).

Use our platform to build AI products, train, fine tune and deploy models on the cloud without worrying about infrastructure, cost management, scaling, and other technical headaches. Train, fine tune and deploy models with prebuilt, fully customizable, modular components. Focus on the science and not the engineering. A Lightning component organizes code to run on the cloud, manage its own infrastructure, cloud costs, and more. 50+ optimizations to lower cloud costs and deliver AI in weeks not months. Get enterprise-grade control with consumer-level simplicity to optimize performance, reduce cost, and lower risk. Go beyond a demo. Launch the next GPT startup, diffusion startup, or cloud SaaS ML service in days not months.

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU.

Impacting virtually every industry, generative AI unlocks a new frontier of opportunities, for knowledge and creative workers, to solve today’s most important challenges. NVIDIA is powering generative AI through an impressive suite of cloud services, pre-trained foundation models, as well as cutting-edge frameworks, optimized inference engines, and APIs to bring intelligence to your enterprise applications. NVIDIA AI Foundations is a set of cloud services that advance enterprise-level generative AI and enable customization across use cases in areas such as text (NVIDIA NeMo™), visual content (NVIDIA Picasso), and biology (NVIDIA BioNeMo™). Unleash the full potential with NeMo, Picasso, and BioNeMo cloud services, powered by NVIDIA DGX™ Cloud, the AI supercomputer. Marketing copy, storyline creation, and global translation in many languages. For news, email, meeting minutes, and information synthesis.

NVIDIA Base Command™ Platform is a software service for enterprise-class AI training that enables businesses and their data scientists to accelerate AI development. Part of the NVIDIA DGX™ platform, Base Command Platform provides centralized, hybrid control of AI training projects. It works with NVIDIA DGX Cloud and NVIDIA DGX SuperPOD. Base Command Platform, in combination with NVIDIA-accelerated AI infrastructure, provides a cloud-hosted solution for AI development, so users can avoid the overhead and pitfalls of deploying and running a do-it-yourself platform. Base Command Platform efficiently configures and manages AI workloads, delivers integrated dataset management, and executes them on right-sized resources ranging from a single GPU to large-scale, multi-node clusters in the cloud or on-premises. Because NVIDIA’s own engineers and researchers rely on it every day, the platform receives continuous software enhancements.

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.

Train and serve large AI models at scale with a single command. Point to your S3 bucket and go. We handle the rest, orchestration, efficiency, node failures, and infrastructure. Simple and scalable. MosaicML enables you to easily train and deploy large AI models on your data, in your secure environment. Stay on the cutting edge with our latest recipes, techniques, and foundation models. Developed and rigorously tested by our research team. With a few simple steps, deploy inside your private cloud. Your data and models never leave your firewalls. Start in one cloud, and continue on another, without skipping a beat. Own the model that's trained on your own data. Introspect and better explain the model decisions. Filter the content and data based on your business needs. Seamlessly integrate with your existing data pipelines, experiment trackers, and other tools. We are fully interoperable, cloud-agnostic, and enterprise proved.

A fully-managed platform for Ray, from the creators of Ray. The best way to develop, scale, and deploy AI apps on Ray. Accelerate development and deployment for any AI application, at any scale. Everything you love about Ray, minus the DevOps load. Let us run Ray for you, hosted on cloud infrastructure fully managed by us so that you can focus on what you do best, and ship great products. Anyscale automatically scales your infrastructure and clusters up or down to meet the dynamic demands of your workloads. Whether it’s executing a production workflow on a schedule (for eg. retraining and updating a model with fresh data every week) or running a highly scalable and low-latency production service (for eg. serving a machine learning model), Anyscale makes it easy to create, deploy, and monitor machine learning workflows in production. Anyscale will automatically create a cluster, run the job on it, and monitor the job until it succeeds.

Our cloud-based environment that automatically sets up your ComfyUI workflow. Each workflow fully equipped with all the essential custom nodes and models, ensuring a hassle-free beginning. Unlock the full potential of your creative projects with ComfyUI Cloud's high-performance GPUs. Benefit from faster processing speeds at market-leading rates, ensuring both time and cost savings. Launch ComfyUI cloud instantly, no installation required, for a seamless start with a fully prepared environment, ready for immediate use. Access ready-to-use ComfyUI workflows with pre-set models and nodes, avoiding configuration hassles in the cloud. Experience rapid results with our powerful GPUs, boosting productivity and efficiency in creative projects.

Langtail is an end-to-end platform that accelerates the development and deployment of language model (LLM) applications. It enables companies to rapidly experiment, collaborate, and launch production-grade LLM products. Key features include: 1. No-code LLM playground for prompt debugging and ideation 2. Collaborative workspaces for sharing prompts and insights 3. Comprehensive observability suite with logging and analytics 4. Evaluation framework for systematically testing prompt performance 5. Deployment infrastructure for serving prompts via API in multiple environments 6. Upcoming fine-tuning capabilities to improve models with user feedback Langtail empowers both technical and non-technical teams to find high-value LLM use cases, refine prompts for reliable performance, and deploy applications with ease. It's the all-in-one platform to take your LLM projects from prototype to production faster than ever.

Viso Suite is the world’s only end-to-end platform for computer vision. It enables teams to rapidly train, create, deploy and manage computer vision applications – without writing code from scratch. Use Viso Suite to deliver industry-leading computer vision and real-time deep learning systems with low-code and automated software infrastructure. The use of traditional development methods, fragmented software tools, and the lack of experienced engineers are costing organizations lots of time and leading to inefficient, low-performing, and expensive computer vision systems. Build and deploy better computer vision applications faster by abstracting and automating the entire lifecycle with Viso Suite, the all-in-one enterprise vision platform.​ Collect data for computer vision annotation with Viso Suite. Use automated collection capabilities to gather high-quality training data. Control and secure all data collection. Enable continuous data collection to further improve your AI models.

Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices.

Fireworks partners with the world's leading generative AI researchers to serve the best models, at the fastest speeds. Independently benchmarked to have the top speed of all inference providers. Use powerful models curated by Fireworks or our in-house trained multi-modal and function-calling models. Fireworks is the 2nd most used open-source model provider and also generates over 1M images/day. Our OpenAI-compatible API makes it easy to start building with Fireworks. Get dedicated deployments for your models to ensure uptime and speed. Fireworks is proudly compliant with HIPAA and SOC2 and offers secure VPC and VPN connectivity. Meet your needs with data privacy - own your data and your models. Serverless models are hosted by Fireworks, there's no need to configure hardware or deploy models. Fireworks.ai is a lightning-fast inference platform that helps you serve generative AI models.

Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, and HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Deploy all your AI models to automatically compute outputs (inference) in your datastore in a single environment with simple Python commands.

Cloobot X is a Next Gen No-Code platform built for Enterprises having in-house IT teams with the below value proposition: 1. Overcome limitations of existing No-Code Platforms (Scalability, Vendor lock-in, etc) 2. Support problem solvers including consultants, domain experts, product managers, designers and end users at every stage of the Software development lifecycle 3. Cutting down time to delivery by 10x with instant deliverables in the form of Prototypes, MVP, Workflow Apps & Codebase (In a programming language of choice) using just prompts. 4. Enable Enterprises to adapt Gen AI while addressing the concerns around it (Platform can be deployed on-premise, Can run on custom LLMs, code is generated by proprietary algorithm and not by Code-based LLMs)

Make AI a trusted part of your business. Build better, deploy faster, and audit easily with the flexibility of a cloud-native platform and the power to deploy anywhere. Easily import models and search cataloged models from across your organization. Save time by annotating data rapidly with model-in-the-loop hinting. Understand the full provenance of your data, models, workflows, and inferences. Deploy models where you need them, including for edge and IoT use cases. Getting valuable insights from your data is not just for data scientists. With Chariot’s low-code interface, meaningful collaboration can take place across teams. Train models rapidly using your organization's production data. Deploy models with one click and monitor models in production at scale.

Whether prompt engineering, fine-tuning, or training, we are ready to meet your business demands. Easily integrate your new model into your production application using the Together Inference API. With the fastest performance available and elastic scaling, Together AI is built to scale with your needs as you grow. Inspect how models are trained and what data is used to increase accuracy and minimize risks. You own the model you fine-tune, not your cloud provider. Change providers for whatever reason, including price changes. Maintain complete data privacy by storing data locally or in our secure cloud.

Compose, test, optimize, and deploy reliable prompts for the leading language models and AI platforms to supercharge your apps and workflows. PROMPTMETHEUS is an Integrated Development Environment (IDE) for LLM prompts, designed to help you automate workflows and augment products and services with the mighty capabilities of GPT and other cutting-edge AI models. With the advent of the transformer architecture, cutting-edge Language Models have reached parity with human capability in certain narrow cognitive tasks. But, to viably leverage their power, we have to ask the right questions. PROMPTMETHEUS provides a complete prompt engineering toolkit and adds composeability, traceability, and analytics to the prompt design process to assist you in discovering those questions.

Deploy all major ML frameworks such as Pytorch, Onnx, XGBoost etc with 1 line of code. Don't have your own models? Deploy our prebuilt models that have been optimised to run with sub-second latency. Fine-tune smaller models on particular tasks in order to decrease costs and latency while increasing performance. It takes just a few lines of code and don't worry about infrastructure, we got it. Integrate with top ML observability platforms in order to be alerted about feature or prediction drift, compare model versions and resolve issues quickly. Discover the root causes for prediction and feature drift to resolve degraded model performance. Understand which features are contributing most to the performance of your model.

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.

Exspanse streamlines the path from development to business value. Build, train & rapidly deploy powerful machine learning models from a single user interface that can scale with your business. Train, tune, and prototype models from the Exspanse Notebook with the help of high-powered GPUs, CPUs & our AI code assistant. Think beyond training & modeling when you can use the rapid deploy feature to deploy models as an API right from an Exspanse Notebook. Clone and publish unique AI projects to DeepSpace AI marketplace to advance the AI community. Power, efficiency, and collaboration in one comprehensive platform. Unleash your full potential as a solo data scientist while maximizing your impact. Manage and accelerate your AI development process through our integrated platform. Turn your innovative ideas into working models quickly and effectively. Seamlessly transition from building to deploying AI solutions, without the need for extensive DevOps knowledge.

Ever Efficient AI offers a powerful yet accessible AI automation platform helping businesses maximize efficiency - without hiring a full-time AI engineer on the team. Their flexible subscription plans connect you with AI experts who build customized data solutions tailored to your specific workflows and industry. No complex modeling or coding is required on your end. The collaborative process lets those with domain expertise guide tool development. EverEfficientAI's team manages the technical complexity behind the scenes, converting your datasets and processes into optimized AI systems. Bi-weekly agile sprints adapt the tools over time while providing transparency. With a focus on usability and rapid integration, EverEfficientAI makes advanced AI easily actionable by any organization. The future of work is here - are you ready to let your data work smarter for you?

Build, train and deploy your models in the cloud, using the latest IPU AI systems and the frameworks you love, with our cloud partners. Allowing you to save on compute costs and seamlessly scale to massive IPU compute when you need it. Get started with IPUs today with on-demand pricing and free tier offerings with our cloud partners. We believe our Intelligence Processing Unit (IPU) technology will become the worldwide standard for machine intelligence compute. The Graphcore IPU is going to be transformative across all industries and sectors with a real potential for positive societal impact from drug discovery and disaster recovery to decarbonization. The IPU is a completely new processor, specifically designed for AI compute. The IPU’s unique architecture lets AI researchers undertake entirely new types of work, not possible using current technologies, to drive the next advances in machine intelligence.

We're building autonomous systems that write and deploy custom software to perform complex tasks, from just English instruction. Maya translates steps written in English into visual programs that you can edit & extend without writing code. Describe the business logic for your application in English to generate a visual program. Dependencies auto-detected, installed, and deployed in seconds. Use our drag-and-drop editor to extend functionality to 100s of nodes. Build useful tools quickly, to automate all your work. Stitch multiple data sources by just describing how they work together. Pipe data into tables, charts, and graphs generated from natural language descriptions. Build, edit, and deploy dynamic forms to help a human enter & modify data. Copy and paste your natural language program into a note-taking app, or share it with a friend. Write, modify, debug, deploy & use apps programmed in English. Describe the steps you want Maya to generate code for.

Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.

Developer-centric tool to monitor and improve AI features powered by LLMs and other foundation models. Our simple SDK gives you an intuitive and actionable view of how your generative AI applications are performing in production. Integrate LLM management into your existing codebase and developer workflow. Use our fine-grained access controls and audit logs to maintain full control over your data. Derive actionable insights on how to improve LLM user interactions. Not only are these teams best-equipped to integrate these new capabilities into existing software products, but their proclivity to deploy, iterate, and improve will also be ever more pertinent going forward. As software becomes increasingly malleable, we believe engineering teams will be the driving force behind turning that malleability into delightful and hyper-personalized user experiences. Developers will be at the center of the generative AI revolution.

Whether you're building AI chatbots, virtual assistants, or other intelligent applications, set up your workspace effortlessly by integrating GPT-powered language models with your provider keys for unparalleled performance. Accelerate the creation of your diverse AI applications using LLM Spark's GPT-driven templates or craft unique projects from the ground up. Test & compare multiple models simultaneously for optimal performance across multiple scenarios. Save prompt versions and history effortlessly while streamlining development. Invite members to your workspace and collaborate on projects with ease. Semantic search for powerful search capabilities to find documents based on meaning, not just keywords. Deploy trained prompts effortlessly, making AI applications accessible across platforms.

Train and deploy GPT models for any use case with the first no-code AI platform for businesses. Our prompt experts are here to help you. If you're looking to fine-tune open source models with your own data, our cost-effective tools are specifically designed for the same. Securely deploy your own open source model across multiple clouds without the need to rely on third-party vendors for your valuable data. Our team of experts will deliver the perfect app tailored to your specific requirements. Our tool enables you to effortlessly monitor your usage and reduce costs. Partner with us and let our expert team address your pain points effectively. Efficiently classify your customer calls and automate your company’s customer service with ease. Our advanced solution empowers you to streamline customer interactions and enhance service delivery. Build a robust system that detects fraud and anomalies in your data based on previously flagged data points.

Merging the best of a notebook and an IDE into one integrated coding environment, experts can explore their data and write stable code at the same time with fully automated cloud infrastructure. Zerve’s data science development environment gives data science and ML teams a unified space to explore, collaborate, build, and deploy data science & AI projects like never before. Zerve offers true language interoperability, meaning that as well as being able to use Python, R, SQL, or Markdown all in the same canvas, users can connect these code blocks to each other. No more long-running code blocks or containers, with Zerve enjoying unlimited parallelization at any stage of the development journey. Analysis artifacts are automatically serialized, versioned, stored, and preserved for later use, meaning easily changing a step in the data flow without needing to rerun any preceding steps. Fine-grained selection of compute resources and extra memory for complex data transformation.

Klu.ai is a Generative AI platform that simplifies the process of designing, deploying, and optimizing AI applications. Klu integrates with your preferred Large Language Models, incorporating data from varied sources, giving your applications unique context. Klu accelerates building applications using language models like Anthropic Claude, Azure OpenAI, GPT-4, and over 15 other models, allowing rapid prompt/model experimentation, data gathering and user feedback, and model fine-tuning while cost-effectively optimizing performance. Ship prompt generations, chat experiences, workflows, and autonomous workers in minutes. Klu provides SDKs and an API-first approach for all capabilities to enable developer productivity. Klu automatically provides abstractions for common LLM/GenAI use cases, including: LLM connectors, vector storage and retrieval, prompt templates, observability, and evaluation/testing tooling.

Enable observability to detect data and ML issues faster, deliver continuous improvements, and avoid costly incidents. Start with reliable data. Continuously monitor any data-in-motion for data quality issues. Pinpoint data and model drift. Identify training-serving skew and proactively retrain. Detect model accuracy degradation by continuously monitoring key performance metrics. Identify risky behavior in generative AI applications and prevent data leakage. Protect your generative AI applications are safe from malicious actions. Improve AI applications through user feedback, monitoring, and cross-team collaboration. Integrate in minutes with purpose-built agents that analyze raw data without moving or duplicating it, ensuring privacy and security. Onboard the WhyLabs SaaS Platform for any use cases using the proprietary privacy-preserving integration. Security approved for healthcare and banks.

IBM Watson Machine Learning is a full-service IBM Cloud offering that makes it easy for developers and data scientists to work together to integrate predictive capabilities with their applications. The Machine Learning service is a set of REST APIs that you can call from any programming language to develop applications that make smarter decisions, solve tough problems, and improve user outcomes. Take advantage of machine learning models management (continuous learning system) and deployment (online, batch, streaming). Select any of widely supported machine learning frameworks: TensorFlow, Keras, Caffe, PyTorch, Spark MLlib, scikit learn, xgboost and SPSS. Use the command-line interface and Python client to manage your artifacts. Extend your application with artificial intelligence through the Watson Machine Learning REST API.

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Bring LLM-powered features to production with tools for prompt engineering, semantic search, version control, quantitative testing, and performance monitoring. Compatible across all major LLM providers. Quickly develop an MVP by experimenting with different prompts, parameters, and even LLM providers to quickly arrive at the best configuration for your use case. Vellum acts as a low-latency, highly reliable proxy to LLM providers, allowing you to make version-controlled changes to your prompts – no code changes needed. Vellum collects model inputs, outputs, and user feedback. This data is used to build up valuable testing datasets that can be used to validate future changes before they go live. Dynamically include company-specific context in your prompts without managing your own semantic search infra.

CORE is a high-performance computing platform built for a range of applications. CORE offers a simple point-and-click interface that makes it simple to get up and running. Run the most demanding applications. CORE offers limitless computing power on demand. Enjoy the benefits of cloud computing without the high cost. CORE for teams includes powerful tools that let you sort, filter, create, and connect users, machines, and networks. It has never been easier to get a birds-eye view of your infrastructure in a single place with an intuitive and effortless GUI. Our simple yet powerful management console makes it easy to do things like adding a VPN or Active Directory integration. Things that used to take days or even weeks can now be done with just a few clicks and even complex network configurations become easy to manage. Paperspace is used by some of the most advanced organizations in the world.

NeuReality accelerates the possibilities of AI by offering a revolutionary solution that lowers the overall complexity, cost, and power consumption. While other companies also develop Deep Learning Accelerators (DLAs) for deployment, no other company connects the dots with a software platform purpose-built to help manage specific hardware infrastructure. NeuReality is the only company that bridges the gap between the infrastructure where AI inference runs and the MLOps ecosystem. NeuReality has developed a new architecture design to exploit the power of DLAs. This architecture enables inference through hardware with AI-over-fabric, an AI hypervisor, and AI-pipeline offload.

The complete LLM platform with a superior developer experience and robust infrastructure. Build, deploy, and manage hyper-personalized, streamlined, and trusted generative AI apps. Langbase is an open source OpenAI alternative, a new inference engine & AI tool for any LLM. The most "developer-friendly" LLM platform to ship hyper-personalized AI apps in seconds.

Lyzr is an enterprise Generative AI company that offers private and secure AI Agent SDKs and an AI Management System. Lyzr helps enterprises build, launch and manage secure GenAI applications, in their AWS cloud or on-prem infra. No more sharing sensitive data with SaaS platforms or GenAI wrappers. And no more reliability and integration issues of open-source tools. Differentiating from competitors such as Cohere, Langchain, and LlamaIndex, Lyzr.ai follows a use-case-focused approach, building full-service yet highly customizable SDKs, simplifying the addition of LLM capabilities to enterprise applications. AI Agents: Jazon - The AI SDR Skott - The AI digital marketer Kathy - The AI competitor analyst Diane - The AI HR manager Jeff - The AI customer success manager Bryan - The AI inbound sales specialist Rachelz - The AI legal assistant