Public sector organizations are asked to do work that matters — and do it under pressure. Government agencies serve communities in direct, visible ways, but they’re doing it with tighter budgets, ongoing staffing challenges and an economic climate that rarely gives them breathing room.
To navigate that reality, many agencies are looking at where technology can ease the strain. Natural language agentic tools are one new area gaining traction. They help teams pull usable insights from large volumes of information and streamline routine work, making it easier to improve processes across departments.
Many public sector organizations still struggle with having their data live in disparate, legacy tools that make data collaboration nearly — if not entirely — impossible. Agencies waste precious time manually consolidating data sources, meaning that insights gained are often outdated by the time full consolidation is complete.
This also makes data ownership across organizations unclear, leading to gaps between various departments, including, crucially, operations and finance. This causes significant challenges for organizations when they’re planning future budgets because they often don’t have an updated or accurate view of their current spending. Precious resources, including employee labor spent on data reconciliations and analysis, are therefore inadvertently not most effectively leveraged.
Agencies are using natural language agentic tools to reduce the amount of time staff spend on manual, repetitive work. With Snowflake Intelligence, employees can get answers to complex financial and operational questions without needing to navigate multiple systems or build custom reports. Staff across roles, not just those with technical or analytics backgrounds, can prompt Snowflake Intelligence using plain language and get clear, usable information near instantly.
All insights are pulled from data stored within Snowflake’s platform or data sitting externally and accessible with Iceberg Tables, helping organizations work with governed data and generate reliable insights. Public sector employees can then spend less time on tedious, manual work and more time fulfilling their organization’s mission.
The Virginia State Police (VSP) is committed to serving its community through leadership, collaboration and community engagement. The organization values innovation, trust and competence, and it embraces inclusion and diversity in its workforce. Leaning into its innovation value, VSP is transforming into an intelligence-led organization, using Snowflake to eliminate manual data silos and achieve gains in operational efficiency and cost management.
Before leveraging Snowflake, the organization was dealing with significant data silos. Essential data lived on disconnected spreadsheets or in legacy systems. On top of that, there was no clear ownership or governance of the data in many cases.
As a result, the organization explains that it suffered from a lack of real-time financial visibility. Leadership couldn’t aggregate data quickly enough to identify spending trends, including being able to distinguish between recurring payments and one-time costs. To address these gaps, the team relied on manual record reconciliation of mission-critical records, which required labor-intensive, line-by-line reconciliation.
VSP leaders were finally able to easily query complex financial data with natural language and voice command capabilities, embracing the benefits of Snowflake’s AI-powered interface.
Using semantic modeling, the organization built a semantic layer over expenditure data. This helps VSP accurately categorize and launch predictive analysis of department spending.
To cut down on manual, repetitive work, the organization leveraged Snowflake to apply automated, rule-based reconciliation at scale, dramatically accelerating record resolution. Rather than employees spending time on these monotonous tasks, they can now spend their time more meaningfully supporting and promoting the organization’s mission.
As a result, VSP analysts reported experiencing up to 80x faster data processing across all operational workflows while realizing rapid time-to-insight. “What we’ve demonstrated with Snowflake Cortex is so far beyond what anyone here thought was possible,” says VSP Chief Data Officer Steven MacLauchlan. “In some use cases, we’ve solved in 45 minutes what used to take an army of people weeks to complete.” The team now manages complex financial reporting tasks in days rather than months of manual effort, significantly improving operations.
VSP has additionally embraced high-precision analytics and achieved more than 99% accuracy in predicting recurring costs. This led to the team identifying approximately $3 million in potential vendor negotiation savings. Overall efficiency has also improved dramatically. For example, it previously took six people nearly two weeks to process 4,000 critical records; now, the organization can process 82,000 records in as few as 45 minutes.
When budgets are tight, small inefficiencies add up. Being able to see where funds are underused or misaligned allows public sector agencies to reduce duplication and direct resources where they’re needed most. Snowflake Intelligence gives teams a clearer view of their financial data without requiring complex or time-intensive analysis, making it easier to act on what they find.
By leveraging Snowflake Intelligence to minimize manual work, public sector organizations can move resources to focus on mission-critical work. In the case of the Virginia State Police, community members look to their police force to uphold safety and security standards, so giving employees more time to spend on that work creates value and lasting impact.
Interested in learning more about how you can leverage Snowflake Intelligence to gain data-driven answers to complex questions? Watch the on-demand virtual event Snowflake Connect: AI.
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