Solution
Build the data foundation for analytics and AI
Teams need governed pipelines, warehouses, and access patterns that scale.
XELARVIS designs lakes, lakehouses, warehouses, pipelines, and governance so analytics and AI programs run on reliable, scalable data foundations.
Practice areas
This solution combines the following XELARVIS service capabilities—each links to how we staff, engineer, and govern delivery.
A consistent path from business problem to production outcomes.
01
Understand the business problem, data, systems and desired outcome.
02
Define the solution architecture, operating model and success criteria.
03
Develop the required AI, analytics, data or technology components.
04
Connect the solution with existing systems, workflows and data.
05
Evaluate performance, security, quality, governance and usability.
06
Move the solution into its target production environment.
07
Monitor performance and continuously improve the solution.
Design target architectures for analytics and AI workloads.
Implement reliable batch and real-time data movement with governance.
Improve availability, quality, and pipeline reliability.
Support analytics and AI with platforms built for growth.
How we evaluate progress—without inventing vanity metrics.
Technology stack
Curated for this outcome theme—not inherited from the full service catalog.
Core language for AI, analytics, and automation.
Relational data modeling and analytics queries.
Large-scale data processing.
Real-time data streaming.
Lakehouse analytics and ML.
Cloud data warehouse platform.
Secure, scalable cloud foundations.
Enterprise cloud and AI services.
Cloud infrastructure and data services.
Containerized application delivery.
Orchestration at enterprise scale.
Data platform and engineering leaders building foundations for analytics and AI.
Related
Next step
Tell us what you are trying to solve. We can help identify the right capabilities, solution approach, technology foundation, and delivery path.
