Precisely intros AI capabilities to simplify data quality
The data integrity specialist's new features, including a conversational interface and a fabric for connecting governed assets, address the growing emphasis on high-quality data.
Precisely on Wednesday unveiled a set of new features aimed at simplifying data management, including an AI-powered conversational interface and a framework for connecting AI capabilities to ensure that they adhere to an organization's governance standards.
Gio, a natural language AI assistant that acts as a new interface for Precisely's Data Integrity Suite, enables users to cleanse, discover, enrich, govern and monitor data without writing code. Meanwhile, the vendor's AI and Agent Fabric is designed to provide transparency and control by uniting customers' data and AI estates.
In addition, the vendor introduced its Data Catalog Agent, an AI tool that automates tagging personally identifiable information and critical data elements to speed the process of organizing data and AI assets.
Collectively, the new capabilities -- planned for general availability in December -- are valuable to Precisely users because they make it easier and faster to navigate the vendor's platform, according to William McKnight, president of McKnight Consulting.
"The new features introduce conversational AI and intelligent automation to bring speed, simplicity and scalability to data management within the Precisely Data Integrity Suite," he said.
Added significance lies in the way the new features interact, with Gio and the Data Quality Agent built on the AI and Agent Fabric, McKnight continued.
"This ensures every automated action aligns with governance, compliance and trust models through auditable workflows and secure controls, fulfilling Precisely’s vision of connecting trusted data and governed AI," he said.
Based in Burlington, Mass., Precisely is a data management specialist that provides a platform designed to help enterprises ensure data quality by keeping data accurate, consistent and contextual throughout its lifecycle.
Simplifying data quality
Data quality has perhaps never been more important. OpenAI's November 2022 launch of ChatGPT marked significant improvement in generative AI (GenAI) technology and sparked surging interest in AI development that continues to increase. AI applications, which now include autonomous agents in addition to GenAI tools such as chatbots, can better inform an enterprise's workforce and make its business processes more efficient.
However, because such applications automate tasks previously performed by humans, it is imperative that the conclusions they reach and actions they take are based on relevant, high-quality data.
Without humans to oversee every aspect of every process and decision, poor data quality leading to incorrect AI outputs could result in substantial consequences for businesses.
Precisely is tackling the most popular use cases for agentic data management. Our research shows that half of organizations are using or considering use agents for data quality, and [about one-third] are focusing on data documentation, classification and discovery.
Kevin PetrieAnalyst, BARC U.S.
The focus Precisely and competing vendors -- such as Alation, Ataccama, Collibra and Informatica -- place on data quality addresses a growing need. As a result, Precisely's new features, which aim to make ensuring data quality easier and faster, are pertinent, according to Kevin Petrie, an analyst at BARC U.S.
"Precisely is tackling the most popular use cases for agentic data management," he said. "Our research shows that half of organizations are using or considering use agents for data quality, and [about one-third] are focusing on data documentation, classification and discovery."
According to Chris Hall, Precisely's chief product officer, the vendor's impetus for developing the new features was providing customers with capabilities that address the rising complexity of data management.
"As organizations adopt AI, they're being asked to move faster, govern more tightly and operate across an expanding ecosystem of tools and data sources," he said. "Our goal is to give customers capabilities that help them keep pace with these changes."
Perhaps the most important of Precisley's new capabilities are Gio and the AI and Agentic Fabric, according to McKnight.
The AI and Agent Fabric provides a foundation that makes other capabilities safe, compliant and trustworthy, he noted. Meanwhile, Gio directly impacts what users can do.
"Gio enables users to perform complex data management tasks by simply describing what they want to do," McKnight said. "I foresee greater use of an organization's most important asset, its data, as a result of initiatives like this."
Beyond the simplicity and speed the new features provide, they help Precisely from a competitive standpoint, according to Petrie.
Most data management vendors offer agents and other AI-powered capabilities, he noted. Precisely's platform, however, is more nimble than some competing platforms, able to integrate and govern data across complex heritage mainframe systems and modern cloud data platforms such as Databricks and Snowflake.
"Enterprises sorely need help integrating distributed data across these environments to support advanced analytics," Petrie said. "Precisely has a compelling market opportunity to serve as the Switzerland of data intelligence, cataloging and integrating data across platforms."
Informatica historically served as the independent connective tissue for many enterprise data estates, he continued. However, the vendor is now in the process of being acquired by Salesforce.
"Informatica's acquisition by Salesforce creates an opening for a new Switzerland provider of data management," Petrie said.
McKnight likewise noted that Precisely provides a comprehensive, competitive platform for data management. With capabilities addressing niches including data quality, cataloging, governance and observability, it not only competes with similar wide-ranging data management vendors but also specialists such as Monte Carlo on data observability.
"Collectively across these data management functions, Precisely provides significant value through its proprietary data enrichment capabilities," McKnight said.
Looking ahead
As Precisely plots product development plans for 2026, a focal point for the vendor is adding more AI capabilities that address data integrity, according to Hall. Included are more agents assisting with specific data management tasks, such as the Data Quality Agent.
"Our goal at Precisely is to advance AI-driven data integrity, expand automation capabilities and enhance natural language interfaces that streamline customer experiences," Hall said.
McKnight suggested Precisely could better serve current users and perhaps attract new ones by improving capabilities geared toward data scientists.
"Precisely could do more for data scientists by adding capabilities for cataloging facets of predictive and prescriptive models and offering data science resources to users," he said.
To raise its profile compared to vendors such as Informatica and Alation, increasing the diversity and quantity of its visualizations for its catalog capabilities would benefit users, as would improving its unstructured data observability capabilities, McKnight added.
"Precisely could deepen its data coverage and utility by improving unstructured data observability -- adding greater capabilities for parsing textual documents -- and adding resources for querying the data described in the catalog," McKnight said.
Petrie, meanwhile, noted that developing and managing AI models and applications is expensive. Steps that Precisely can take to help customers manage costs related to AI, therefore, would be significant.
"AI adopters struggle to govern the costs of their data, model and agent operations," Petrie said. "I'll be interested to see how Precisely can help its customers address these FinOps concerns, for example, by helping measure and optimize cloud compute or AI token consumption."
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.
