AI Compute Orchestration

Orchestrating internal AI platforms so teams can standardize pipelines, manage model lifecycles, and deploy AI services into production.

Business impact

• Platform provisioning work hours — Vodafone reports 60,000 hours eliminated.
• Code releases across core repositories — Lockheed Martin reports more than 2,500 code releases across three core repositories.

Data requirements

• Engineering code and repositories (tabular) — Lockheed Martin’s repository activity is tied to code release workflows.
• Training and operational AI data (text) — The platforms support AI engineering and production deployment, including assistant and training workloads.
• Model and deployment artifacts (text) — The systems manage lifecycle and release steps for AI solutions.

AI methods and techniques

• Standardized pipelines — Vodafone describes these as the way its AI Booster platform structures AI development and deployment work.
• Automated deployment — The platform automates deployment steps for AI solutions and services.
• Model lifecycle management — Lockheed Martin uses its AI Factory to manage internal AI engineering and lifecycle work.
• Retrieval-augmented generation — Deutsche Telekom’s sales and service assistant platform includes RAG as part of the implementation.

Industries

Real-world evidence

5 documented case studies on record.

Companies using this: Deutsche Telekom, Lockheed Martin, P&G, Tesla, Vodafone.