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Accelerate Decisions and Innovation with GenAI

Harness GenAI

Decisions integrates GenAI across its platform to reduce barriers and democratize data access. From building applications and workflows to analyzing complex data, Decisions helps businesses come to market faster with differentiated solutions that drive market share and revenue.

Natural Language Queries

Empower business users to get the data they need—fast—without relying on IT or waiting weeks for reports. With GenAI, Decisions transforms plain English into complex SQL queries in seconds. Now, your IT team can focus on building new features instead of serving as a reporting help desk.

Revenue Query Example

Natural Language Query: “Show me the total revenue from North America for Q1 2024.”

Generated SQL Query:

SQL

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SELECT SUM(revenue)

FROM sales_data

WHERE region = 'North America' AND quarter = 'Q1 2024';

Return Rate Query Example

Natural Language Query: “Which products had the highest return rate in June 2024?”

Generated SQL Query:

SQL

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SELECT product_name, return_rate

FROM product_returns

WHERE return_month = 'June 2024'

ORDER BY return_rate DESC;

Low-Code Development

Decisions empowers users to build and deploy applications quickly, without extensive coding. This democratizes application development, making it accessible to a broader range of users within the organization.

Rapid Application Development

The low-code capabilities of Decisions enable businesses to prototype, test, and deploy applications rapidly. A sales team can quickly build a custom KPI management tool to goals, actions, and progress—all within a few days rather than the weeks or months required by traditional development methods.

Rapid Application Development

Seamless Integration with Existing Systems

Applications developed on the Decisions platform integrate seamlessly with existing enterprise systems and data sources, including ERPs, CRMs, and financial databases. With built-in APIs, robust data transformation capabilities, and a scalable cloud-native architecture, Decisions simplifies integration while unifying your entire technology ecosystem.

Seamless Integration with Existing Systems

Scalable and Secure

Decisions leverages leading technologies—DuckDB for high-performance OLAP queries, Kubernetes for container orchestration, Redis for fast in-memory data storage, and AWS for scalable infrastructure—to support secure, large-scale data processing and reliable application deployment. Built-in security controls, automated updates, and robust DevOps support empower your teams to innovate faster and bring solutions to market with confidence.

Scalable and Secure

Accelerate Decision Making

Decisions leverages GenAI to empower users to make faster, better decisions in real-time.

Any Data Anywhere

Are you trying to analyze images, videos, spreadsheets, and documents to make the best decision? Decisions leverages GenAI to process both structured and unstructured data from any source. It identifies patterns, trends, and anomalies across your enterprise datasets—regardless of format or location—so you can make decisions with complete context and precision.

Any Data Anywhere

What If Simulations

Quickly build and test “what-if” scenarios to forecast outcomes, quantify trade-offs, and model the impact of strategic changes. Empower decision-makers to assess performance risk, explore various goal-achievement paths, and identify low-effort adjustments that can significantly improve financial or operational results—all within a controlled, simulated environment.

What If Simulations

Automated Workflow

Configure and deploy fully customized, automated workflows to reduce operational bottlenecks and minimize administrative overhead. Decisions enables teams to quickly implement business logic, handle workflow exceptions, and respond dynamically to evolving requirements—enhancing efficiency, reducing downtime, and enabling tailored process control across the enterprise.

Automated Workflow

Advanced Data Operations with DuckDB

The Decisions platform, built on DuckDB, allows advanced data operations such as grouping sets, pivoting, and unpivoting. These features enable scalable, distributed, complex analyses on large datasets.

Grouping Sets for Rollup

Users easily create reports that include total rollups alongside detailed breakdowns. For example, to analyze sales by vendor and product category with a totals row, the SQL might look like this:

Generated SQL Query:

SQL

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SELECT vendor, product_category, SUM(sales) AS total_sales

FROM sales_data

GROUP BY GROUPING SETS ((vendor, product_category), (vendor), ())

ORDER BY vendor, product_category;

This query provides a summary of total sales by vendor and product category, with rollups to show overall totals.

Pivoting Timeframes

To pivot order dates into months (YYYYMM) using DuckDB’s PIVOT

SQL

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SELECT * FROM sales_data

PIVOT (

SUM(sales)

FOR DATE_FORMAT(order_date, '%Y%m') IN ('202401', '202402')

)

ORDER BY vendor, product_category;

This query pivots the sales data by month, providing a month-by-month breakdown.

Unpivoting Metrics

To unpivot a series of metric columns such as Annual Sales and Profit Margin into a new column called Metrics:

SQL

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SELECT vendor, product_category, metric, value

FROM sales_data

UNPIVOT (

value FOR metric IN (annual_sales, profit_margin)

);

This query consolidates the annual_sales and profit_margin columns into a single metrics column, making it easier to analyze and compare different metrics.

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