South KoreaTechnology and telecom2025 – ongoingTMAP Mobility
Natural-language data agents for employees
TMAP Mobility cut repetitive data requests to its analytics team by 68% with natural-language data agents
Problem
Access to data was limited and permission rules were rigid. More than half of the data analysis team's workload was simple extraction requests from other staff.
Approach
TMAP adopted the Databricks platform on AWS under an internal agent initiative. Genie Agents let staff without data skills query data in natural language. Unity Catalog set permissions by department, and column masking policies protected sensitive fields.
Results
Takeaway
TMAP measured the effect on the analysts' queue, not on the number of people using the tool. The company did not say how it counted repetitive requests.
Categories
- Industry
- Technology and telecom
- Business function
- Internal work and knowledge management
- Innovation type
- Process innovation
- AI technology
- Generative AIAI agents
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
Databricks describes how the South Korean navigation service TMAP Mobility gave employees natural-language access to data through Genie Agents, with department-level permissions. It reports a 68% drop in repetitive data requests to the analytics team as of September 2025. A quote from the head of its data platform says over half of the analysts' workload had been simple extraction requests.
Full details are in the original sources.