PARTNERS

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market and has redefined modern computer graphics, high performance computing and artificial intelligence. The company’s pioneering work in accelerated computing and AI is reshaping trillion-dollar industries, such as transportation, healthcare and manufacturing, and fueling the growth of many others.

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 was founded in 2014 with a simple yet ambitious aim: accelerate the adoption of machine learning to solve some of the world’s most challenging problems. Since then they have attracted over £10m in venture funding, enabling the organisation to build a community of highly-talented ML experts dedicated to solving the challenges faced by every organisation working with machine learning and AI. Their customers and users have collectively deployed more than five million models in thousands of organisations across the world, including AstraZeneca, H&M and Capital One.

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.

LGN provides software to deploy, monitor, and update edge AI models at enterprise scale.  Their Neuroform product is the worlds first closed loop of continuous learning from edge AI deployments, this results in sustainable system performance over time and total model mobility to shift from one environment to another without huge costs or lengthy delays.  If needed, LGN can offers a turn-key solution with their MaaS (Model as a Service) business model, guaranteeing system functionality out of the box.

Iguazio’s machine-learning operations (MLOps) platform enables enterprises to build and deploy automated machine-learning pipelines, drastically shortening the time required to create real business value with artificial intelligence. Using Iguazio, enterprise clients including Fortune 500 companies have accelerated deployment of artificial intelligence to production and enabled the continuous rollout and management of new AI services, at scale and in real time. The Iguazio platform includes a built-in feature store. It can be deployed anywhere (multi-cloud, on-premises, or hybrid) to bring to life ambitious AI-driven strategies. The Iguazio platform is used across verticals to solve the complexities of MLOps and create business impact through a multitude of use cases, such as fraud prediction, real-time recommendation engines, and predictive maintenance. Iguazio partners with dozens of technology companies, including Microsoft, AWS, Google, NetApp, NVIDIA, and MongoDB.

Superb AI is an end-to-end training data platform that automates data preparation at scale and makes building and iterating on datasets quick, systematic, and repeatable. Launched in 2018 by data scientists, academics, and ML engineers, Superb AI is reinventing how teams of all sizes label, manage, curate, and deliver training data. Fueled by decades of experience and academic research in computer vision and deep learning, including 25+ publications, 7,300+ citations, and 100+ patents, Superb AI empowers companies at all stages to build and deploy computer vision applications faster than ever before.

Terminus DB is an open-source document graph database. Build collaborative apps quickly and easily using TerminusDB. Create knowledge from your data by linking JSON documents in a powerful knowledge graph. With workflow & approval pipelines, revision control of data and schema, and advanced diff & patch operations, TerminusDB, and managed cloud version TerminusX, are the backends for the next generation of smart applications.

YData provides a data-centric platform that accelerates the development and increases the RoI of AI solutions by improving the quality of training datasets. Data scientists can now make use of automated data quality profiling and improve datasets leveraging state-of-the-art synthetic data generation.

Modzy enables organizations to deploy, integrate, run, and monitor ML/AI models anywhere — in the cloud, on-premises, or at the edge. With 15x faster model deployment and up to 80% cloud cost savings, teams use Modzy to build AI- powered solutions faster. The Modzy platform speeds up AI solution development times by 20X with powerful APIs, manages the chaos of deploying models to the cloud, on-prem, edge, and disconnected locations, and helps optimize and save infrastructure costs associated with running models in the cloud.

Superwise is a model observability platform built for high-scale production ML. Giving practitioners fully automated, enterprise-grade model monitoring capabilities that take years to develop in-house, wrapped in a self-service platform. Superwise auto-calibrates model metrics, analyzes events, and correlates anomalies for you so you can easily see when models misbehave and accelerate your time to resolution before issues impact business outcomes.

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.

Valohai is the MLOps platform purpose-built for ML Pioneers, giving them everything they've been missing in one platform that just makes sense. Now they run thousands of experiments at the click of a button, easily collaborate across teams and projects – all using the tools they love. Empowering ML Pioneers to build faster and deliver stronger products to the world. Valohai is used by companies such as JFrog, LEGO Group, Boston Scientific, and Konux. Read more about our approach to MLOps.

To deliver the value of ML and data science to your enterprise, the HPE delivers an enterprise-grade ML cloud service that enables developers and data scientists to rapidly build, train, and deploy ML models—from pilot to production, at any scale. HPE includes a number of powerful preconfigured hardware stacks and it’s powered by HPE Ezmeral ML Ops and the popular Determined Training Platform along with a suite of strong open source tooling.  It provides data scientists with self-service access to a sandbox environment for prototyping and testing, to eliminate IT provisioning delays, ensure repeatability, and accelerate time-to-value. And as a fully managed solution, the HPE GreenLake offering frees IT from routine infrastructure management tasks.

Arize AI is a Machine Learning Observability 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.

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.

FeatureBase is a real-time database built on bitmaps. It is designed primarily for speed and horizontal scalability, and is particularly well-suited for workloads that require many real-time updates, inserts, and deletes on massive datasets. FeatureBase ingests data continuously to execute analytical workloads in real-time for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing, transforming, and aggregating billions of rows of data at greater than 100x the price-performance of traditional columnar databases.

Activeloop, the dataset optimization company, seamlessly manages data for deep learning. Activeloop automatically connects unstructured data to machine learning models. Its open-source package Hub (http://github.com/activeloopai/Hub) enables data streaming, scalable machine learning pipelines, and dataset version control for distributed workloads. Activeloop platform, app.activeloop.ai allows companies to easily access, visualize and improve their datasets to build great models. Activeloop’s stack is used by teams at Google, Waymo, and Red Cross. Activeloop is founded by a team from Princeton, Google, Equinix, Tesla and backed by Y Combinator.

Fiddler offers an enterprise Model Performance Management platform for teams to monitor, explain, analyze, and improve their models and build trust into AI. The unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. Unlike observability solutions, Fiddler integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. F500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale and increase revenue by improving predictions for better business outcomes.

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.

BOSCH AIShield is a corporate start-up at Bosch offering one stop solution for AI Security. AIShield secures AI/ML systems against various adversarial threats (model extraction, model evasion, data poisoning & model inference attacks) across industry use cases by providing vulnerability assessment and endpoint protection for AI/ML models, with its API offering and consulting led technology services. AIShield works seamlessly with core MLOps platforms responsible for orchestration & compute and works with other satellite platforms for observability & cybersecurity monitoring. Backed by learnings and implementations within Bosch AIoT ecosystems, AIShield was unveiled in Jan 2022 after being in stealth mode for 2 years while building the solution. Bosch AIShield holds 20+ patents in AI security domain. The team closely works with tech communities, start-ups, enterprises, regulatory bodies, cloud platforms and cybersecurity firms for evangelizing & accelerating AI security adoption.

Pasteur Labs is reshaping the software stack for industrial R&D based on “simulation intelligence” (SI) technologies. Their new class of operating system enables simulation testbeds to achieve 100-1000x the efficiency of today’s systems, producing high-fidelity, real-time “digital twin” environments that can be explored with AI agents and optimization algorithms. As a public-benefit corporation, Pasteur Labs is dedicated to building “Nobel-Turing” technologies for the long-term, responsible advancement of science and society broadly.  The non-profit “sister” org Institute for Simulation Intelligence (ISI) supports PhD students, postdocs, and other researchers in open pursuit of SI endeavors.

TruEra fills a critical gap in your AI stack, analyzing, explaining, and testing model quality throughout the lifecycle. TruEra’s AI Quality solutions analyze, debug, and monitor machine learning models, leading to higher quality and trustworthiness, as well as faster deployment. Backed by years of pioneering research, TruEra works across the model lifecycle and multiple model development platforms, and embeds easily into your existing AI stack.

Modulos offers a low-code Data-Centric AI platform for fast and efficient experimentation to deliver innovative clients’ solutions and stay ahead of the competition. We do not let poor data quality undermine your innovation efforts: we guide you to pinpoint data that need to be curated, as they negatively influence your results. Fostering cooperation between technical and business teams, we create the right environment to thrive and deliver successful use cases faster and at a lower cost. Modulos platform also addresses solutions’ fairness towards your diverse clients’ groups, simplifying efforts to comply with regulations.

Poor quality ML data is the biggest impediment to fast productionization of ML models — yet, managing data across training and production models is ad-hoc, time consuming, highly manual and error-prone today, especially for unstructured data. This leads to reactive training data fixes for production models, biases creeping in and poor model predictions.

Galileo is a first of it’s kind ML Data Management tool to enable quick error (mislabels,  poor predictions, etc) analysis, production<>training drift detection, smart training data sampling from production data and data/model tracking – all in one, collaborative space – ML teams, SMEs, PMs, Labeling teams all use Galileo to enable data transparency and high quality training data that is always representative of the real world.

 We are well funded, built on the founding team’s past work leading product and engineering at Google AI and Uber AI, and are in private beta working with ML teams at F500 and fast moving early stage enterprises that have critical ML models using unstructured data, starting with NLP.

Run:ai helps organizations accelerate their AI transformation by delivering a foundation on which they can build their modular AI infrastructure. Using Run:ai's Atlas Computing Platform companies enable AI practitioners to gain on-demand access to pooled resources for any AI workload, build, train and inference. Built on cloud-native technology it helps IT to simplify the implementation and scaling of AI infrastructure while increasing team productivity and utlization of expensive GPUs. Learn more at www.run.ai.

Track everything you need to make your models reproducible with Weights & Biases— from hyperparameters and code to model weights and dataset versions. Weights & Biases helps your ML team unlock their productivity by optimizing, visualizing, collaborating on, and standardizing their model and data pipelines – regardless of framework, environment, or workflow. Used by ML engineers at OpenAI, Lyft, Pfizer, Qualcomm, NVIDIA, Toyota, GitHub, and MILA, W&B is part of the new standard of best practices for machine learning. W&B is free for personal use and academic projects, and it's easy to get started. Run your first experiment in 30 seconds with this quick hosted notebook: wandb.me/intro

As AI models become broadly deployed in commercial applications, their reliability and biases are becoming a massive business challenge. Imagine “intelligent” surveillance cameras or health care software that treat people differently purely because of race or skin tone. manot AI is a model refinement SaaS platform that recognizes, diagnoses, and mitigates biases when they occur ensuring a real-time feedback loop from the production environment where the model operates.

Feature engineering is a core part of everyday machine learning, but writing, computing, and serving features gets very complex & costly, especially when dealing with real-time features. Fennel is a real-time feature engineering platform that solves all these problems and makes ML more accessible to early data science/ML teams. The platform is fully managed with zero operational overhead, designed ground up to be easy to use, comes packaged with all the engineering best practices, and uses a suite of advanced optimizations to reduce infra costs for the same workload. Fennel is built by an ex-Facebook team and backed by several industry leaders: https://fennel.ai/company.

MakinaRocks provides an MLOps platform that streamlines the entire machine learning workflow and combines it with cutting-edge industrial AI technologies to deliver end-to-end AI solutions for industrial applications. Our AI solutions empower businesses in various industrial sectors to optimize their operations and create business value with AI-driven insights. From predictive maintenance to process optimization, MakinaRocks' industrial AI solutions are tailored to the specific needs of our clients. At MakinaRocks, our mission is to accelerate industries' transition to AI. As a trusted partner of the AI Infrastructure Alliance, we are dedicated to advancing AI adoption across industries and helping businesses in the industrial field unlock the full potential of AI.

Arthur is the AI Performance Company. Our platform monitors, measures, and improves machine learning models to deliver better results. We help data scientists, product owners, and business leaders accelerate model operations and optimize for accuracy, explainability, and fairness. Arthur’s research-led approach to product development drives exclusive capabilities in computer vision, NLP, bias mitigation, and other critical areas. We’re on a mission to make AI better for everyone, and we are deeply passionate about building ML technology to drive responsible business results.

Sematic is the open-source orchestrator loved by ML teams. In order to keep ML models fresh and relevant, they need to be retrained often with new data. Fast retraining loops can only be achieved via fully-automated end-to-end pipelines that sequences all steps necessary to go from raw data to a trained model with evaluation metrics. Building such pipelines on cloud infrastructure is challenging without the right tooling. Sematic was built by a team of ex Cruise engineers exactly for this purpose. Without infrastructure skills, ML engineers can easily develop complex end-to-end pipelines and run them on their local machine and in the cloud and benefit from visualizations and observability. Sematic customers report an 80% reduction in model turnaround time since using Sematic.

At Colorado College our goal is to provide the finest liberal arts education in the country. Drawing upon the adventurous spirit of the Rocky Mountain West, we challenge students, one course at a time, to develop those habits of intellect and imagination that will prepare them for learning and leadership throughout their lives.

deepset is the company behind Haystack open-source LLM framework and deepset Cloud — an LLM platform for enterprise AI teams. Since 2018, deepset has helped AI teams to apply the latest in NLP to real-world applications.