Multi-Brand Portfolio Operator Enables AI-Powered Data Access with Snowflake Agents
50-70% reduction in ad-hoc data requests to analytics teams
3-5x faster time to insights compared to traditional dashboards
30-40% increase in business user self-service analytics adoption
Engagement snapshot
The challenge
The client manages large volumes of structured and unstructured data within Snowflake. However, accessing insights required SQL expertise or support from data teams, creating delays and limiting how effectively business users could use data.
Teams across sales, finance, and operations relied heavily on analysts for even basic queries, leading to bottlenecks, slower decision-making, and underutilization of available data.
What Everest delivered
Everest Technologies developed AI-powered Snowflake Agents to enable natural language interaction with enterprise data, allowing users to access insights instantly without needing SQL knowledge.
Solution components
- AI-powered natural language interface
- Enabled users to ask business questions in plain English
- Delivered accurate, context-aware insights directly from Snowflake
- Snowflake-native AI integration
- Built using Snowflake Cortex for intelligence and scalability
- Leveraged Cortex Analyst for structured data queries
- Leveraged Cortex Search for unstructured data exploration
- Semantic data understanding
- Created semantic layers to interpret business metrics, KPIs, and relationships
- Ensured responses aligned with business context and terminology
- Secure, governed access
- Implemented role-based access controls
- Ensured users only accessed authorized data
- Customizable AI agents
- Designed agents tailored to different business functions and use cases
Approach
Everest followed a structured approach to enable intuitive and secure data access:
- Connected enterprise data sources within Snowflake
- Built semantic understanding of business data using Cortex Analyst
- Enabled AI-driven query processing through natural language inputs
- Delivered instant, accurate insights through AI-powered responses
- Ensured governance and security through role-based access controls
Quantified impact
Impact & outcomes
- 50-70% reduction in ad-hoc data requests to analytics teams
- 3-5x faster time to insights compared to traditional dashboards
- 30-40% increase in business user self-service analytics adoption
- Up to 60% reduction in manual SQL and report creation efforts
- Enabled near real-time insights instead of hours or days of reporting latency
Business impact
- Faster, more informed decision-making across teams
- Reduced dependency on data teams for day-to-day insights
- Improved data accessibility across business functions
- Increased utilization of enterprise data assets
- Shift from reporting-driven workflows to decision-driven execution
Tools & platforms
- Snowflake
- Snowflake Cortex (Analyst & Search)
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