We can’t do it alone. It takes great partners to build the highways of tomorrow.
Determined AI lets data science teams train models faster using state-of-the-art distributed training. It also lets those teams find better models with advanced hyperparameter tuning.
It makes scaling training across GPUs with smart on-prem & cloud scheduling easy and it lets teams track and reproduce their work with built-in experiment tracking.
Pachyderm delivers a robust data versioning and data lineage platform for AI/ML that acts like Git for data. It’s advanced pipelining system uses Kubernetes and Docker to quickly scale data transformation, training and model development across a distributed data science team. It’s customers include some of the world’s most advanced companies including cutting edge automakers, banks, healthcare, biotech and defense agencies.
Seldon accelerates the adoption of machine learning technologies to solve the world most challenging problems with a diverse and growing set of applications. Seldon Deploy simplifies the process of testing, monitoring and deploying models in live environments through intuitive dashboards and greater collaboration between data scientists and DevOps teams. Alibi helps explain the predictions of back box machine learning models and gauge the confidence of their predictions.
For machine learning leaders that need to put ML models into production faster, more securely, and cost-effectively within their existing operational processes, Algorithmia is machine learning operations (MLOps) software that manages all stages of the ML lifecycle. Unlike inefficient, expensive, and insecure do-it-yourself MLOps management solutions that lock users into specific technology stacks, Algorithmia automates ML deployment, optimizes collaboration between operations and development, leverages existing SDLC and CI/CD processes, and provides advanced security and governance. Over 110,000 engineers and data scientists have used Algorithmia’s platform to date, including the United Nations, government intelligence agencies, and Fortune 500 companies. For more information, visit www.algorithmia.com.
Maiot‘s mission is to enable production-ready ML code. They developed and maintain ZenML, an extensible, open-source MLOps framework to create reproducible pipelines. It exposes a simple interface for data scientists to write production-ready code, while also providing a configurable integration for data engineers.
Allegro AI makes ML researchers and engineers more effective by giving them tools to manage their experiments, data, pipelines and model deployment. The company’s open source ClearML MLOps platform automates and simplifies developing, managing and deploying machine learning solutions by giving data scientists simple plug & play tools for experiment management, workload orchestration, data operations (feature stores & data pipelines) and deployment solutions that integrate into any tool chain. Allegro AI is trusted by brands such as: NVIDIA, NetApp, Samsung, Hyundai, Bosch, Microsoft, Intel, IBM and Philips.
Superb AI is a training data platform built by a team of researchers and engineers. With over 3 decades of experience in AI R&D along with over 100 patents and over 7,000 research citations, the team at Superb AI is aiming to deliver the most advanced and comprehensive training data platform for all teams at the forefront of artificial intelligence.
Terminus DB brings a distributed, revision control database to data science teams across the world. The TerminusDB is an open-source full-featured in-memory graph database management system that stores data like git. It allows for the whole suite of revision control features: branch, merge, squash, rollback, blame, and time-travel, linked through TerminusHub, which allows teams to manage access to databases and to collaboratively work on shared resources.
Neu.ro Inc. is a technology company using state-of-the-art Machine Learning (ML) and Deep Learning (DL) to solve real-world problems for business and science. The core product of the company is the Neu.ro – MLOps Platform-as-a-Service for full-cycle ML/DL application development and deployment on public, hybrid, and on-premise clouds. Named a Gartner Cool Vendor in AI Core Technologies in 2019, Neu.ro has executed successful engagements with leading enterprises in North America, EMEA, CIS, China, and Japan.
YData is a data-centric platform that democratizes the access to valuable data and allows Data Scientists to build and deploy better AI solutions with high-quality and synthetic data.
Founded in October 2018, Fiddler’s mission is to enable businesses of all sizes to build, deploy, and maintain trustworthy AI solutions. Fiddler’s next-generation Explainable Monitoring solution enables data science and technical teams to monitor, explain, and analyze their AI solutions, providing transparent and reliable experiences to business stakeholders and customers. Fiddler works with pioneering Fortune 500 companies as well as emerging tech companies. For more information please visit www.fiddler.ai or follow us on Twitter @fiddlerlabs.
Tecton provides an enterprise feature store that makes it easy to build, deploy, and share features for machine learning. Tecton transforms raw data into feature values, stores the values, and serves them for model training and online predictions. It allows data scientists to build and deploy features within hours instead of months. Tecton was founded by the creators of Uber Michelangelo.
Superwise.ai enables data science and operational teams to monitor and assure the health of their AI-based systems. Its AI Assurance platform monitors AI models in real-time, detecting and driving action when there’s any deviation from these models’ healthy and expected behavior, thus eliminating the risks derived by the black-box nature of these implementations. Such risks include: bad decisions, unwanted bias, and compliance issues. The company serves global players in the area of eCommerce, online marketing, and financial services. Among the use cases already implemented by its customers: Customer Lifetime Value (CLV) predictions, fraud detection, lead scoring, credit risk, and more.
Valohai is an end-to-end MLOps platform for machine learning and deep learning. The platform provides everything you need to take your machine learning projects from POC to production. Build machine learning pipelines that automate everything from data extraction to model deployment. Best of all, everything on the platform is automatically versioned and shareable. The Valohai MLOps platform is used by companies such as Twitter, JFrog, LEGO Group, PARC, and Konux. Read more about our approach to MLOps.
WhyLabs is the AI Observability company behind whylogs – the standard for data logging. The platform provides model monitoring to surface and resolve data quality issues, data bias and concept drift. With out-of-the-box anomaly detection and purpose-built visualizations, WhyLabs prevents costly model failures and eliminates the need for manual troubleshooting. It works on any data, structured or unstructured, at any scale, on any platform. The company was created at a fundamental AI research institute – the Allen Institute for Artificial Intelligence by Amazon Machine Learning alums.
cnvrg.io is an AI OS, transforming the way enterprises manage, scale and accelerate AI and data science development from research to production. The code-first platform is built by data scientists, for data scientists and offers unrivaled flexibility to run on-premise or cloud. From advanced MLOps to continual learning, cnvrg.io brings top of the line technology to data science teams so they can spend less time on DevOps and focus on the real magic – algorithms. Since using cnvrg.io, teams across industries have gotten more models to production resulting in increased business value.
Arize AI is a Machine Learning Observabililty platform that helps ML practitioners successfully take models from research to production, with ease. Arize’s automated model monitoring and analytics platform help ML teams quickly detect issues the moment they emerge, troubleshoot why they happened, and improve overall model performance. By connecting offline training and validation datasets to online production data in a central inference store, ML teams are able to streamline model validation, drift detection, data quality checks, and model performance management.
Spell offers a leading MLops platform designed for modern ML engineering teams to discover deeper insights, deploy models faster, and deliver cost-savings for the business. With advanced tools for model training, deployment, and monitoring, Spell eliminates the common barriers in both skills and resources that hold teams back from scaling up their machine learning initiatives. Spell is trusted by over 10,000 users across leading brands, big and small including Square, Conde Nast, Alphasense, healx, and Stanford.
OctoML applies cutting edge AI to make it easier and faster to put machine learning models into production on any hardware. From the team that built the Apache TVM deep learning compiler stack, used in production by top ML and hardware vendors, OctoML is automating the deployment of machine learning models. With decades of combined experience in computer systems design and machine learning, we believe automated systems are the right approach to reign in the complexity and enable us all to move forward more easily. Our team is composed of passionate ML PhDs, pioneers and professors with experience at Microsoft, Facebook, Amazon, Apple, Qualcomm, Intel and more.
ModelOp, the pioneer of ModelOps software, enables large enterprises to address the critical governance and scale challenges necessary to fully unlock the transformational value of enterprise AI and Machine Learning investments. Core to any AI orchestration platform, G2000 companies use ModelOp Center to govern, monitor and orchestrate models across the enterprise and deliver reliable, compliant and scalable AI initiatives.
Auger.AI offers products focused on machine learning accuracy. The primary product is our accuracy monitoring product MLRAM, which focuses on detecting and correct model drift. MLRAM works with any cloud-based machine learning platform. We also offer the first commercial Bayesian optimization-based automated machine learning, which seeks to deliver higher accuracy than AutoML solution have traditionally delivered. Finally, we are the primary authors of the open source automated machine learning pipeline API, A2ML.
AI Labs is based in the UK and has a unique blend of high value design and manufacturing industry domain knowledge and expertise in cutting edge AI technology. Our aim is to make complex AI technology simple to use and thereby accelerate AI adoption and digital transformation journeys of our customers. This principle is encapsulated in our suite of commercial products viz. AI Boost®, AI Sight®, AI Power® and AI Distill. Our products and services are suited to end users with a wide range of skill domains, irrespective of the size of the organisation, and assist their AI journey in a responsible, transparent and ethical manner.
Snitch AI provides automated scientific validation for machine learning models in a few clicks, without the need to become an expert. We assist data science team to assess the quality of their models that are developing. Our platform gives you the details needed to properly understand this assessment and how to remedy the situation. Our goal is to empower Data Science team to deliver robust, performant and trustworthy AI. With Snitch AI, you will be able to confidently deploy your machine learning models into production and ensure the best possible business outcomes from using them.
Sama provides accurate data for ambitious AI. The company’s high-quality training data platform is trusted by the world’s most ambitious organizations to develop accurate machine learning models. Trusted by leading technology companies such as Walmart, Google and Nvidia, Sama specializes in image, video and sensor data annotation and validation for machine learning algorithms in industries including transportation, retail and e-commerce, consumer and media, medtech, manufacturing and robotics, and agriculture. For more information, visit www.sama.com.
InfuseAI builds PrimeHub, an open-source pluggable MLOps platform. PrimeHub equips enterprises with consistent yet flexible tools to develop, train, and deploy ML models at scale. By improving the iterative process of data science, data teams can collaborate and innovate better. InfuseAI is trusted by research institutes and clients in industries including FSI, manufacturing, and healthcare.
Molecula allows businesses to operationalize AI projects through a novel data format and purpose-built feature storage system. Molecula’s technology automates the extraction of features from raw data at the source, enabling unified, instant access to massive quantities of big data in a highly-performant format. From feature extraction to model training to production, the Molecula feature store provides continuously updated feature access, reuse, and sharing without the need to pre-process data.
Toloka is a crowdsourcing platform. Designed by engineers for engineers, Toloka lets you integrate an on-demand workforce directly into your processes. Our cloud-based crowdsourcing platform is a fast and efficient way to collect and label large data sources for machine learning and other business purposes. With Toloka, you can control the accuracy of data labeling to develop high performing ML models. Toloka helps to improve models of any kind, including those in audio & natural language processing, computer vision, chat bots and voice assistants, search and information retrieval, as well as offering solutions for business challenges and projects on any scale. Requesters, including IT companies, retailers, independent crowdsourcing experts and others, bring their tasks to the Toloka platform. Performers complete their tasks for a fee. The result is a full-fledged crowdsourcing process where a large number of people complete simple tasks in order to solve a large complex task together.
Neptune is a metadata store for MLOps, built for research and production teams that run a lot of experiments. It gives you a central place to log, store, display, organize, compare, and query all metadata generated during the machine learning lifecycle. Individuals and organizations use Neptune for experiment tracking and model registry to have control over their experimentation and model development.
Gretel.ai automates privacy engineering, enabling companies to reduce the time to access sensitive data by up to 10x and backed by mathematical privacy guarantees. With Gretel, developers can get started in minutes with open source reference examples and simple APIs for generating unlimited amounts of synthetic data, labeling personally identifiable information, or anonymizing and removing biases from data. Gretel is designed for integration into modern pipelines and scales automatically– so labeling and transformations are fast, even with high throughput data streams. Gretel services are controlled by a simple web-based interface and can be fully managed in the cloud or deployed on-premises. To get started with Gretel, visit: https://gretel.ai or jump right in with one of our blueprint examples linked above.
MindsDB helps anyone use the power of machine learning to ask predictive questions of their data and receive accurate answers from it. MindsDB was founded in 2017 by Adam Carrigan (COO) and Jorge Torres (CEO), backed with over $5.2M in seed funding from the University of California, Berkeley SkyDeck fund, OpenOcean, and the co-founders of MySQL and MariaDB. MindsDB is also a graduate of Y Combinators’ recent Winter 2020 batch and was recently listed as one of America’s most promising AI companies by Forbes Magazine. To see how MindsDB can help you visit www.mindsdb.com.
TruEra provides the first AI Quality Management System to help enterprises Develop, Adopt and Monitor ML models. Powered by unique AI Explainability technology based on six years of research at Carnegie Mellon University, TruEra’s platform eliminates the black box surrounding ML technologies. This lays the foundation for deep model quality analytics resulting in improved quality, trust, regulatory acceptance and model performance.
Bodywork develop open-source tools for ML engineers. We focus on bridging the gap between research-led solutions and fully-operational ML systems, helping to create a path to production that is fast, reliable and repeatable. At our centre we have bodywork-core, which deploys jobs, services and pipelines (to Kubernetes), without requiring engineers to get involved in containerisation, orchestration and infrastructure. We are an open platform and value the ability to integrate with your existing codebase and technology choices.
LatticeFlow is a spin-off from ETH Zurich building a product to help organizations deliver trustworthy AI models. AI teams from large enterprises and emerging tech companies use LatticeFlow to discover the blind spots of their AI models, improve the quality of the datasets they are trained on, and ultimately deliver models that can be deployed in production with confidence. To learn more information about LatticeFlows, visit https://latticeflow.ai and follow the company on Twitter @latticeflowai.
Acceldata delivers a comprehensive data observability platform that synthesizes signals across data, processing, and pipelines to transform how organizations build, operate, and optimize enterprise data systems. Unlike APM applications, Acceldata monitors and manages complex, inter-connected enterprise data systems that are composed of many technologies, many sources, and operating environments such as on-prem, hybrid, or cloud. We deliver the deepest data observability, spanning metrics, logs, and data quality to improve reliability, accelerate scale, and lower costs for real-time AI and analytics workloads. Customers use Acceldata to predict, identify, and resolve problems before SLAs are breached, and see rapid and significant improvements in their data team productivity and data system performance. Acceldata accelerates data success.
Deepchecks is a minimally intrusive MLOps solution for Continuous Validation of Machine Learning systems, meant to enable you to trust your models through the continuous changes in your data lifecycle. This includes the must-have features for any ML Monitoring system: performance monitoring, algorithmic bias detection, various configurable alerts, etc. But also some unique features that are especially helpful for complex ML pipelines: Monitoring various phases of the pipeline, detecting hidden data integrity issues, detecting low confidence segments, detecting inconsistencies that are hidden within unstructured text, etc. Deepchecks can fit into existing pipelines within all of the major cloud platforms, as well as some on-prem/hybrid architectures. Check out our intro video and our sandbox – and feel free to reach out.
TeachableHub is a fully-managed platform that brings teams together to instantly deploy, seamlessly serve at scale, and easily manage Machine Learning models as serverless APIs from a centralized hub. Our best-of-breed solution helps ML and DS teams of all sizes adopt standardized MLOps practices out of the box and get models from PoC to production in minutes.
Pandio is the leader in AI orchestration. Pandio’s AI-driven architecture automatically orchestrates data, models and ML tools to solve the complexity of connecting systems and scaling AI. Pandio customers get AI to market an order of magnitude faster with AI orchestration built for performance at scale. Orchestrate AI with Pandio.com.
Comet provides a self-hosted and cloud-based MLOps solution that enables data scientists and teams to track, compare, explain and optimize experiments and models. Backed by thousands of users and multiple Fortune 100 companies, Comet provides insights and data to build better, more accurate AI models while improving productivity, collaboration and visibility across teams. Get started for free at www.comet.ml.
At ixpantia our passionate and experienced data scientists and business consultants work with organizations around the world to empower them to innovate with a data-driven approach. From our headquarters in Latin America we support our customers and help their teams develop data products and deploy them to production.
DataArt is a global software engineering firm that takes a uniquely human approach to solving problems. With over 20 years of experience, teams of highly-trained engineers around the world, and deep industry sector knowledge, we deliver high-value, high-quality solutions that our clients depend on, and lifetime partnerships they believe in.
At INNOQ, we give technology a purpose. We future-proof your ideas. Honest consulting, innovative thinking, and a passion for software development means: We deliver successful software solutions, infrastructure, and business models.
SFL Scientific is a US-based data science consulting and professional services firm. SFL is composed of experienced Ph.D.-level data scientists and engineers who specialize in developing bespoke production-grade machine learning and artificial intelligence solutions. All of the solutions we create are customized to address specific client needs. We work with commercial organizations and federal agencies of all sizes to understand their underlying business processes and deliver customized solutions to help drive operational excellence.
Trigr Innovation is an independent consultancy providing fractional product and strategy leadership for emerging B2B firms building AI and data products. As AI becomes ever more prevalent in technology solutions, product management professionals will need to adapt their discovery, innovation, design and execution frameworks to accommodate AI’s unique infrastructure and process requirements. Trigr’s product leadership, data and AI expertise can help you maximize outcomes for your customers and your company.
Canonical publishes Ubuntu – the most used OS in ML development and production – and packages open source MLOps solutions for the enterprise, with security, support and consulting services. Canonical partners with industry leaders (Microsoft, Google, Amazon, Nvidia, Dell, Lenovo, Intel and more) to ensure the best end-to-end experience from workstations to multi-clouds, self-driving cars, autonomous robots and smart devices.
Build Kubernetes Clusters Anywhere – Fast & Easy. Platform9 Managed Kubernetes (PMK) is a SaaS managed offering, providing the simplest tool to manage all your complex Kubernetes needs, anywhere – on-premises, in public clouds or at the edge.
GPUs and other emerging accelerators are increasingly critical to ML/AI operational infrastructure. But physical limitations make GPUs very inflexible compared to other elements of modern computing, keeping utilization as low as 10%. Juice Labs‘ drop-in-anywhere software pools and shares GPUs remotely to keep utilization near 100%, helping any organization get smart about their GPU usage – and drive more business value for less.
Data Science Salon unites the brightest leaders in the media, advertising, and entertainment across the nation in data science fields. We gather face-to-face and virtually to educate each other, illuminate best practices, and innovate new solutions. Data Science Salon | Media, Advertising & Entertainment is the only industry conference that brings together specialists in the media and entertainment data science field to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere. Get the most current state of current industry trends and innovations in media, advertising, entertainment through DSS podcasts, exclusive content, Webinars and live Trainings. DSS also has an extensive on-demand video library of presentations from the top industry experts.
Kardio Labs LLC is a medical imaging startup company founded by the team of medical professionals, technologists and business professionals with rich and diverse experience in their respective fields. We are passionate to solve the problems in the cardiology field by using state of the art technology and create products for radiologist and cardiologist so they can become more efficient. We are developing Artificial intelligence-based solutions for automated reporting of CT Coronary Angiogram for patients suffering from Coronary artery diseases.
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