Data management and analytics software provider Treasure Data has released Treasure Code, an AI-native command-line interface designed to manage and operate its Intelligent Customer Data Platform (CDP).
The interface is intended to streamline how technical and marketing teams, as well as AI agents, handle data operations as CDPs become more complex and central to customer experience programs, according to the company.
Treasure Code introduces a unified, code-based interface that allows teams to operate the Treasure Data platform programmatically. Rather than relying on multiple dashboards and manual processes that can slow operation and increase operational risk, users can execute data workflows, manage configurations and deploy changes through a single command layer. The system supports natural-language input, version control, and rollback capabilities, applying software engineering practices to CDP operations.
Rafa Flores, Chief Product Officer at Treasure Data, stated:
“Our customers deal with incredible complexity and scale operating a CDP, often with upwards of hundreds of millions of profiles and trillions of data points processed. Treasure Code reduces the operational burden of data operations, enabling brands to manage a CDP with fewer resources and free teams up for strategic, high-impact work.”
The company positions Treasure Code for data engineers, platform teams, and marketing operations groups that need direct, programmatic control over data pipelines, customer segments, journeys, and AI-driven workflows. The interface is augmented with Claude Code to support natural-language-driven creation and iteration, with human review built into the process to reduce the time it takes to build and change data and CDP workflows.
Treasure Data highlighted several functional areas for the release, including the ability to execute tasks using natural language rather than complex SQL or CLI syntax, manage CDP configurations as version-controlled code, and reduce friction between development and production environments by consolidating tools and scripts into a single interface.
CDPs Take On Expanding Role in CX Stacks
Customer data platforms have become a core component of customer experience technology stacks, serving as the system of record for unified customer profiles and behavioral data. CDPs are increasingly responsible for feeding downstream systems that power analytics, personalization and real-time customer engagement across marketing and service digital channels.
As these platforms expand beyond basic data unification into orchestration and AI-driven decision making, operational complexity has grown. Many CX teams now rely on specialized data engineering resources to maintain pipelines, manage governance, and adapt workflows to changing business needs.
Vendors across the CDP market have been investing in automation, low-code interfaces and AI assistance to reduce that dependency and shorten the time required to implement changes.
