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Seeking: AI and Machine Learning Platform Technologies-image of a finger touching the screen and lines of yellow extening out in different directions

A yet2 client is seeking start-ups and innovative companies developing novel artificial intelligence, machine learning (AI/ML) and advanced computing technologies and platforms to aid in the development, training, and deployment of AI solutions across their organization.

The client is interested in identifying and establishing an ecosystem of AI/ML companies and tools across three core technology categories, and is particularly interested in technologies and systems within these categories designed for high-stakes applications and use cases:

  • DataOps – technologies and platforms for storing, processing, and managing data for AI/ML training and inference.
    • Including, but not limited to: data pipelines, data observability, data processing, data storage, synthetic data generation
  • MLOps – technologies and platforms for handling the end-to-end ML lifecycle from training to deployment to verification and explainability
    • Including, but not limited to: model training, testing, deployment, and monitoring; AI security; AutoML platforms; ML pipelines; Explainable AI; Verification and Validation
  • Computing / ML Infrastructure – computing technologies and platforms for AI/ML training and inference at the edge
    • Including, but not limited to: high-power computing for training and inference, edge computing, low SWaP (Size, Weight, and Power) inference, portable AI computing, Infrastructure as Code (IaC)

Possible Solution Areas

The client is open to solutions from any industry or application; however, they are particularly interested in solutions being developed or currently used in applications in high-stake industries such as financial services, gambling, security, defense, public safety, autonomous vehicles, aerospace, fraud detection, predictive maintenance, and more.

Requirements / Constraints

Solutions of particular interest will have the following characteristics:

  • Be able to scale or currently used for large-scale production applications
  • Deployed on-prem and/or at the edge
  • Kubernetes-based solutions
  • Open-source solutions are of interest but not required
  • Early-stage companies (e.g. pre-revenue or just begun generating revenue) are of particular interest

University research is not of interest

Desired Outcome of the Solution

yet2’s client is open to a range of collaboration opportunities

Related Tech Needs

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Photo Credit: Gerd Altmann from Pixabay

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