AI agents: Data & Analytics
17 production-ready agents in Data & Analytics. Each one describes what it does, a practical example, the effect month by month, a payback calculation tied to a real role, and the systems it reads data from.
Consolidates data discrepancies into unified directories and cleans duplicates.
Allows business users to ask questions of data in natural language and receive reports without an analyst.
Continuously monitors key metrics and signals sharp deviations in sales, cost of goods sold, or inventory faster than a human.
Answers questions about business data in natural language with charts.
Manages data access policies by role, controls who sees what, and protects sensitive data.
Monitors critical metrics and instantly signals deviations.
Builds and maintains a data warehouse and pipelines from ERP/LIMS/MES/CRM for reliable reporting.
Automates data access policies, identifies excessive permissions, and controls access to sensitive datasets.
Builds sales, demand, and performance forecasts based on history and seasonality.
Collects and reconciles data from ERP, LIMS, MES, and CRM into a single source for reporting without manual export.
Prepares reporting packages for investors, banks, and partners.
Automatically catalogs data, enriches it with metadata, explains what is where and how to use it.
Tracks data origin: where a figure came from, what transformations it underwent, for audit and trust.
Allows asking questions to 1C and Creatio data in natural language and receiving answers with figures and graphs, without an analyst.
Consolidates production, sales, quality, and finance into a single executive dashboard with key performance indicators.
Maintains a unified directory of products, substances, and counterparties, eliminating duplicates and coding discrepancies.
Forecasts product demand based on history and seasonality to plan production runs and inventory.