A secure, accountable layer that turns siloed data into decisions that deliver lasting impact
Nearly 85% of AI initiatives fail due to poor data quality, availability or governance. This problem is all-consuming, as data scientists often spend up to 80% of their time collecting, cleaning and preparing data, leaving little time for business or model building.
This secure, accountable layer of the AI tech stack consolidates fragmented data, automatically validates its quality, and provides end-to-end data lineage. By combining data engineering and data science for enrichment, it speeds time to value and deepens the insights generated by AI Co-Pilots. In short: it enables the intelligence that accelerates high-impact decisions and improves organizational outcomes.
Every company or organization must address data first. Building a solid data layer is the single most critical investment for any successful AI initiative. Our unified data foundation provides the bedrock to ensure AI models are smart, secure and scalable – and can transform data into decisions that deliver lasting impact.
Consolidate data in one place, with automated quality scoring for trusted data to use for AI-enabled decision making.
Robust audit trails and transparent data lineage ensure proper data management and governance, key components in a successful AI transformation.
This single-pane view enables users to view and act on data, run basic situational analyses and visualize base data to achieve high-quality results.
Deliver value faster by automatically adding years of SME domain knowledge to the dataset.
Stop wasting time and money on sub-par AI projects. Our focused implementation and unified data foundation ensure companies derive value and impact from their AI deployments.
Eliminate the need to question data integrity by using automated data quality scoring and end-to-end data lineage. Finally, leaders can trust underlying insights and focus energy on strategic decision-making.
Quickly consolidate messy, siloed data sources into a trusted, accountable data layer that understands industry and operational demands. By pairing data engineering with data science, companies can gain value from data in weeks, not years.