ABSTRACT: Ataccama’s new Agentic Data Trust Platform introduces autonomous data quality and governance powered by the ONE AI Agent, enabling enterprises to deliver trusted, AI-ready data up to 83 percent faster. Built on continuous observability, reference data intelligence, and MCP connectivity to LLMs and enterprise agents, the platform creates a self-improving trust layer for modern AI systems. This brief explores the launch, insights from Ataccama’s leadership, and the evolving role of the CDO as organizations shift from managing data to operationalizing data trust at scale.
Data Trust Is Now the AI Bottleneck
As enterprises accelerate their adoption of AI, one truth is becoming clear: models are no longer the bottleneck, data trust is. AI systems are becoming more autonomous, more embedded in operations, and more responsible for decisions with real consequences. Whether an application is scoring credit risk, detecting fraud, or powering a generative AI assistant, success depends on confidence in the underlying data.
Ataccama’s newly launched Agentic Data Trust Platform, powered by the ONE AI Agent, is designed to meet this moment. The platform automates how organizations manage and trust their data and can accelerate the delivery of AI-ready information by up to 83% compared with traditional workflows, according to Ataccama. For data teams long burdened by manual rule writing, profiling, and cleanup, this is a fundamental shift toward autonomy and continuous data trust.
From Manual Governance to Autonomous Data Trust
Traditional data governance workflows have relied heavily on human intervention, from writing quality rules across hundreds of systems to debugging anomalies and documenting lineage. These processes cannot scale to match the volume, complexity, and speed of AI initiatives. Ataccama is aiming with ONE AI Agent to replace that legacy approach with a fully integrated, agentic system capable of:
- Profiling data automatically
- Detecting inconsistencies and duplicates
- Generating and applying data quality rules in bulk
- Documenting data assets with business-friendly descriptions
- Producing reports and dashboards
- Executing entire workflows from start to finish
As described in the discussion with Jay Limburn, CPO of ataccama, this is not a co-pilot that requires step-by-step human instruction. It is an actual autonomous agent capable of breaking down tasks, reasoning through workflows, and executing actions while documenting every step for visibility and governance.
This shift creates what Ataccama describes as a self-improving loop of data trust, allowing organizations to maintain high-quality, explainable data without the constant manual intervention that has historically been required.
Enterprise Impact: Hours Instead of Weeks
The reported efficiency gains are substantial:
- AI-ready data delivered 83% faster
- Data quality processes completed up to 9× faster
- 25+ workdays saved across 1,500 data assets
- Nearly 90% reduction in manual effort for rule changes and documentation
One global bank documented how the platform completed tasks in hours instead of weeks, generating documentation for 100 catalog items and automating over 170 quality rule changes with minimal human oversight.
Ataccama has seen that this frees data teams to focus on higher-value initiatives, like improving models, accelerating insights delivery, and driving measurable business outcomes, rather than fighting fires.
MCP Server: Extending Trusted Data to LLMs and Enterprise Agents
One of the most strategic components of the launch is the Ataccama MCP Server, which exposes trusted, explainable data to AI tools, copilots, agents, and LLMs like Claude and GPT.
This agent-to-agent protocol ensures that:
- AI systems operate only on governed, explainable data
- Every prediction or decision is traceable back to its source
- Data quality is no longer trapped inside data teams—it becomes usable across the business
With enterprises quickly moving toward multi-agent ecosystems, MCP becomes a foundational trust layer for the next generation of enterprise AI.
The CDO’s Role Evolves: From Governance to Trust Architecture
As organizations adopt autonomous and agentic AI systems, the Chief Data Officer’s remit expands dramatically. The CDO is no longer the steward of governance frameworks; they become the architect of enterprise-wide data trust.
The new responsibilities include:
- Designing and operating autonomous trust layers
- Ensuring explainability and validation for AI-driven decisions
- Enabling secure, governed data access for agents and LLMs
- Partnering with business units to deliver trusted AI outcomes
CDOs who embrace automation and agentic data management gain significant advantage. Those who remain tied to manual, reactive practices will struggle to keep pace.
Where Adoption Is Accelerating
Early adopters span highly regulated, data-intensive industries:
- Financial Services
- Insurance
- Pharmaceuticals
- Manufacturing
Use cases range from autonomous credit scoring and fraud detection to supply chain optimization and quality assurance. Any domain requiring trusted, explainable data stands to benefit—and as AI regulation expands globally, the demand for agentic data trust will only intensify.
Our ANGLE
Enterprise AI is evolving rapidly, but without trustworthy, explainable data, even the most advanced models fail. Ataccama’s Agentic Data Trust Platform meets this challenge with autonomy, intelligence, and continuous improvement.
Why is this important? We see that Ataccama’s goal and platform aims to introduce a dynamic trust layer that continuously monitors and improves data quality across pipelines. We see the key elements of this layer in the data platform arcitecture must require:
- Data Observability for schema drift, missing values, and latency
- Reference Data Management to maintain consistency across systems
- A Data Trust Index that quantifies reliability
- Integrated quality remediation through automation
This transforms trust from a static certification into a continuous, adaptive system, exactly what modern AI workloads require.
By combining the ONE AI Agent, a powerful trust layer, the MCP Server, and a unified data management architecture, Ataccama positions enterprises to deliver trusted AI-ready data at scale, and to thrive in a multi-agent, regulation-heavy future where data trust becomes the defining competitive edge.
Disclosure: TheCUBE is a paid media partner for Ataccama, the sponsor of theCUBE’s event coverage, Ataccama nor other sponsors have editorial control over content on theCUBE Research, theCUBE, or SiliconANGLE
