Build the data foundation for practical AI. iShift's Data Strategy & AI practice brings a data-focused approach to our application modernization and AI work. We help organizations define a practical path from fragmented data to trusted analytics and AI-enabled workflows. We are expanding this practice through our Databricks and Snowflake partnerships, engineer training, and focused solution development.
Discuss Your Data PrioritiesIdentify priority use cases, assess data quality and access, and define a phased roadmap. Align data investments with mission needs, governance requirements, and measurable goals.
Plan data integration and platform architecture for analytics and AI. Our growing Databricks and Snowflake capabilities focus on organizing, connecting, and governing enterprise data.
Explore how trusted data can support document intelligence, analytics, and AI-assisted decisions. Connect insights to applications and workflows, with access controls and human review built into the design.
These examples illustrate where we can start a discovery conversation. The right approach depends on your data, security requirements, and operational priorities.
Bring together data from separate systems to improve visibility into program performance and operational trends.
Explore search and summarization over approved content, with source references and controlled access.
Explore patterns and exceptions in audit, regulatory, or financial data to support human review and prioritization.
Start with a discovery conversation to clarify your data priorities and constraints. Define a focused assessment or proof of concept with agreed success measures. Use the findings to determine the next step, including architecture, governance, and a phased implementation plan.
We are expanding our Data Strategy & AI practice through partnerships with Databricks and Snowflake, two leading modern data platforms. These relationships support our focus on organizing, connecting, and governing enterprise data to power analytics and AI-enabled workflows.
For technology partners and delivery teams: we welcome conversations about focused data and AI opportunities, joint solution exploration, and connecting modern data platforms to enterprise applications and workflows.
