Toptal helps media company reduce complex data analysis time from days to minutes.
A media and publishing leader partnered with Toptal to build AI tools that let analysts query complex proprietary data using natural language instead of custom formulas and macros.
Client
A US-based media and publishing company producing news, magazines, and business information services.
Employees
Revenue
Industry
Communication, Media and EntertainmentDelivered Services
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Schedule a CallChallenge
Analysts relied on massive Excel files and custom formulas and macros to answer complex business questions, with some requests taking days to resolve. Feeding the files directly into an LLM was impractical because of their size and the risk of inaccurate calculations.
Solution
AI-ready Data Pipeline
Toptal engineered a daily Python pipeline that transformed massive Excel files into structured PostgreSQL tables, giving AI models targeted access to relevant data without loading entire spreadsheets into context.
Natural Language Analysis
Rather than relying on the LLM to calculate answers itself, Toptal built a model context protocol (MCP) layer that translated analysts’ natural-language questions into read-only SQL, executing complex calculations against the database and exposing the queries for validation.
Outcome
Faster Insights
Analysts could answer complex business questions in minutes instead of spending days building custom formulas and macros, dramatically shortening the path from question to insight.
Self-service Data Analysis
The new workflow let analysts interrogate large financial datasets through conversational prompts, with generated SQL available for review when they needed to validate the underlying calculations.
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