9 Integrations with Lambda
View a list of Lambda integrations and software that integrates with Lambda below. Compare the best Lambda integrations as well as features, ratings, user reviews, and pricing of software that integrates with Lambda. Here are the current Lambda integrations in 2026:
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1
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 -
2
Jupyter Notebook
Project Jupyter
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. -
3
Keras
Keras
Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API. -
4
ZenML
ZenML
Simplify your MLOps pipelines. Manage, deploy, and scale on any infrastructure with ZenML. ZenML is completely free and open-source. See the magic with just two simple commands. Set up ZenML in a matter of minutes, and start with all the tools you already use. ZenML standard interfaces ensure that your tools work together seamlessly. Gradually scale up your MLOps stack by switching out components whenever your training or deployment requirements change. Keep up with the latest changes in the MLOps world and easily integrate any new developments. Define simple and clear ML workflows without wasting time on boilerplate tooling or infrastructure code. Write portable ML code and switch from experimentation to production in seconds. Manage all your favorite MLOps tools in one place with ZenML's plug-and-play integrations. Prevent vendor lock-in by writing extensible, tooling-agnostic, and infrastructure-agnostic code.Starting Price: Free -
5
OpsVerse
OpsVerse
Aiden by OpsVerse is an AI-powered DevOps copilot designed to streamline workflows, automate repetitive tasks, and provide real-time insights into infrastructure and deployments. Powered by agentic AI, Aiden constantly learns from your team’s behavior and adapts to your specific needs, offering tailored responses and actions. It integrates seamlessly into your DevOps environment, proactively detecting and resolving issues, from scaling infrastructure to addressing deployment failures. Aiden ensures privacy-first design and compliance with data security policies, with deployment flexibility to fit your organization’s needs.Starting Price: $79 per month -
6
NVIDIA Brev
NVIDIA
NVIDIA Brev is a cloud-based platform that provides instant access to fully configured GPU environments optimized for AI and machine learning development. Its Launchables feature offers prebuilt, customizable compute setups that let developers start projects quickly without complex setup or configuration. Users can create Launchables by specifying GPU resources, Docker images, and project files, then share them easily with collaborators. The platform also offers prebuilt Launchables featuring the latest AI frameworks, microservices, and NVIDIA Blueprints to jumpstart development. NVIDIA Brev provides a seamless GPU sandbox with support for CUDA, Python, and Jupyter Lab accessible via browser or CLI. This enables developers to fine-tune, train, and deploy AI models with minimal friction and maximum flexibility.Starting Price: $0.04 per hour -
7
Caffe
BAIR
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. -
8
Shadeform
Shadeform
Shadeform is a GPU cloud marketplace that provides a single platform, unified console, and API for finding, comparing, launching, and managing on-demand GPU instances across numerous cloud providers, making it easier to develop, train, and deploy AI models without juggling multiple accounts or provider interfaces. It lets users view live pricing and availability for GPUs across clouds, launch instances in either their own cloud accounts or in Shadeform-managed accounts, and manage a cross-cloud fleet from one place with standardized tooling such as curl, Python, or Terraform. It aggregates GPU capacity and pricing data so teams can optimize compute spend, deploy containerized workloads with consistent interfaces, centralize billing and account management, and avoid vendor-specific complexity by using a unified API that supports multiple providers. Shadeform also offers scheduling and automated provisioning so that users can secure resources when they become available.Starting Price: $0.15 per hour -
9
EquityZen
EquityZen
EquityZen is a financial technology investment platform and private market marketplace that connects shareholders of private companies (often employees or early investors looking to sell their equity) with accredited investors seeking access to pre-IPO investment opportunities. It simplifies secondary market transactions in late-stage private company stock by providing a clear process and structured investment products that help introduce liquidity to traditionally illiquid private markets and enable participation in the growth of leading private firms. Since its 2013 launch, EquityZen’s marketplace has facilitated tens of thousands of private placements across hundreds of companies, bringing together buyers and sellers and offering pooled investment vehicles and direct share acquisitions to accredited investors. Its tools and network aim to unlock equity compensation value for shareholders while giving investors diversified access to private company shares.
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