Data, Analytics & AI

One-size-fits-all data systems hinder sharing and transparency. We pair modern data platforms like Snowflake with domain-driven, people-oriented solutions that start small and scale outward.

• Rapidly assess the architecture of your existing data systems.
• Design a future state architecture aligned to how information flows in your organization.
• Create a strategic roadmap to a data architecture that fits and grows with your business.

We provide short and predictable roadmap for learning how your company can leverage AI and machine learning to drive efficiency and create insights.

• Ensure youʼre hitting the right target with expert problem framing, processes, and controls.
• Gain a clear understanding of unintuitive pitfalls like overfitting, bias, and misalignment.
• Empower leaders to be cautiously competitive in a rapidly changing landscape.

Turn your data catalog into a hub of shared meaning that empowers analysts to streamline identify source data more quickly, streamline integrations, and create more accurate reports.

• Use LLMs to look across your entire metadata ecosystem.
• Detect and group together names and definitions that have similar meaning.
• Consolidate disparate representations into a high-quality, enterprise-wide glossary.

Choose and implement the right analytics software to get the most value from data.

• Understand existing culture, processes, and technologies for best fit with available options.
• Guide organization through installation, configuration, and change management.
• Educate stakeholders on data analytics best practices.

Empower your team with an AI-ready data catalog that people love to use.

• We provide expert guidance from design and configuration through launch and adoption.
• Get maximum ROI through widespread adoption and high-engagement.
• Accelerate knowledge graph formation with AI-powered data harmonization.

Build scalable solutions for improved data accuracy, transparency, and interoperability.

• Use human-centered automation to improve data quality at the point of collection.
• Ensure the business value of data by treating it as a product.
• Establish and grow scalable data management practices.

Develop comprehensive data product-oriented strategies that build stakeholder support and accelerate time to value.

• Work with stakeholders to define goals, document current state, and explore whatʼs possible.
• Develop strategies that ensure demonstrable business value through quick wins.
• Use processes and automations to ensure compliance with industry standards.

Uncover hidden trends, patterns, and relationships and drive better decisions.

• Create understandable and compelling dashboards, reports, and visualizations.
• Migrate legacy reporting to modern platforms like Power BI and Tableau.
• Tune up analytics workflows for better performance and accuracy.