AI platforms

Without an effective AI platform approach, model development can be hampered by complex, unrepeatable, and fragile workflows, making it difficult for organizations to generate and maximize business value from AI.

Our approach to AI platforms empowers data scientists and machine learning engineers to create replicable AI solutions quickly and collaboratively and improve the reliability, safety, and trustworthiness of your models. We help you reduce friction for your teams and minimize development time and costs — all while maintaining strong governance to ensure secure, ethical, and compliant AI development.

Get in touch

AI platforms

Get in touch

Developer working in his desk surrounded by colourful dot graphic/texture

Imagine creating a scalable AI platform that helps solve a problem 85% of your customers are grappling with daily.

The AI decarbonization system we built for Terrascope outperforms standard approaches with fewer computing resources, less data and delivers emission calculations in days and weeks, rather than months.

It’s what we do.

Learn more

Get to production 5x faster

Streamline development by giving data scientists access to data, computing resources, and foundation models for building AI solutions at scale.

Promote AI infrastructure reuse and composability

Empower data scientists and developers to easily create and customize AI workflows using a drag-and-drop interface. Boost efficiency by streamlining ML integration and fostering collaboration across projects.

Minimize AI compliance risk

Automate auditability and traceability to ensure AI development is transparent and accountable as you grow your capabilities.

Our services

We help you evolve AI development in four phases:

Discovery

Understand your current cloud ecosystem, identify potential use cases and measures of success, and develop an AI platform roadmap and action plan.

Start

Build an initial platform for model training and development, connect it to relevant data sources, and deliver an MVP for an AI or generative AI use case.

Scale

Expand your AI platform capabilities by adding API-driven components such as foundation models and scaling to support multiple use cases.

Sustain

Get ongoing support to maintain your AI platform, add new capabilities, and evaluate new cloud offerings as your needs evolve.