Altara secures $7M to bridge the data gap that’s slowing down physical sciences
Altara’s AI aims to diagnose failures and help speed up R&D by unifying data siloed across spreadsheets and legacy systems.
mint AI·
Technology leaders report that attempts to scale AI is not meeting expectations. Key barriers include governance, legacy systems, talent, and cultural anxiety. Companies must prioritise reinvention and execution over mere adoption to thrive in the evolving tech landscape.
Read full articleAltara’s AI aims to diagnose failures and help speed up R&D by unifying data siloed across spreadsheets and legacy systems.
Enterprises are experimenting with AI agents internally first, using smaller testing teams and strict governance before deploying customer-facing applications.
When it comes to AI adoption, some institutions lead with executive strategy, others with faculty experimentation, but all are working through governance, curriculum updates and faculty training.
Washington CIO Bill Kehoe details the way artificial intelligence can unlock many facets of modernization, enabling faster decommissioning of legacy systems and expedited business process re-engineering.
Aubrey Vaughan, vice president of government strategy at Celonis, explains why DoD can’t just lather AI over top of legacy systems to improve financial audits.
Google is recasting its data and analytics portfolio as the Agentic Data Cloud, an architecture it says is aimed at moving enterprise AI from pilot to production by turning fragmented data into a unified semantic layer that agents can reason over and act on more reliably at scale. The new architecture builds on Google’s existing data platform strategy, bringing together services such as BigQuery, Dataplex, and Vertex AI, and elevating their capabilities in metadata, governance, and cross-cloud interoperability into what the company describes as a shared intelligence layer. That intelligence layer strategy is underpinned by the new Knowledge Catalog, an evolution of Dataplex Universal Catalog, that the company said uses new capabilities to extend its metadata foundation into a semantic layer mapping business meaning and relationships across data sources. These capabilities include native support for third-party catalogs, applications such as Salesforce, Palantir, Workday, SAP, and Servi
Every marketing and AI leader is being asked to do the same thing right now: scale AI across teams, accelerate adoption, and show measurable results.
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