OpenText announced its vision for the future of enterprise AI with the introduction of the OpenText AI Data Platform (AIDP). OpenText AI Data Platform addresses the convergence of data and AI to deliver secure and scalable enterprise capabilities.
As volumes of proprietary data grow exponentially, organizations face mounting pressure to manage, secure, and activate their private information. Moreover, according to McKinsey’s annual State of AI study, 51% of organizations using AI have experienced at least one negative consequence and inaccuracy, underscoring the need for information governance. OpenText’s innovation roadmap focuses on helping customers establish contextual data foundations to fuel accurate AI results to accelerate business outcomes.
“AI is evolving rapidly, from search and summarize to domain-specific agents. Rather than the world of one super agent, we will soon have armies of secure AI agents for every critical business process coordinated through AI orchestrators,” said Savinay Berry, CPO & CTO at OpenText. “While others are starting with models, we start with governed enterprise content and processes. That’s why our agents will answer with auditability and not guesswork. We believe that accuracy through trusted data and AI is not just an IT challenge; it is a c-level imperative.”
A Vision for Contextual AI
OpenText’s AI strategy is built on nearly 35 years of being the custodians of data for its customers. Practical enterprise AI requires agents to understand the specific situation, environment, and task it operates within to be effective. With the right context, OpenText can bring new life to old data, while solving relevancy and avoiding false confidence.
OpenText business applications assist enterprises in managing their largest data sets today including documents, commerce trades, IT tickets, and security signals. This can be human generated content, machine generated content, or content between organizations. OpenText ensures that information has metadata tags to provide data lineage, data rights, and data retention policies. With data security and identity access management wrapped around it, these contextual elements are critical to driving accuracy with any enterprise AI model.
OpenText Aviator then sits on top of this contextually rich data to enable automated workflows with agentic AI. OpenText’s Aviator is unique because it adheres to three core standards:
- Multi-cloud: Supports on-premises, cloud, and hybrid deployments
- Multi-model: Compatible with any AI model (LLM, SLM), including bring-your-own-model
- Multi-application: Deep integration with ERP, CRM, and other enterprise platforms
This open architecture ensures that organizations can tailor their AI strategies to their specific business, industry, and compliance needs. Furthermore, OpenText is working across the ecosystem with alliance partners like SAP, Microsoft, Google, Salesforce, Oracle, and more on deep integrations to drive an agent-to-agent roadmap.
OpenText also announced it will be expanding its partnership with Databricks, the Data and AI company. OpenText already builds solutions on the Databricks Data Intelligence Platform with OpenText Threat Detection and Response. Now OpenText and Databricks will be working to co-innovate on the OpenText AI Data Platform through technical integrations and Delta Sharing. Together, customers can seamlessly unify, govern, and analyze all their enterprise data, empowering them to unlock trusted AI insights and drive innovation at scale.
“With the OpenText AI Data Platform, we are building a truly open architecture enabled by APIs so the choice of where the data resides always sits with our customers. AI agents must be built on specific data sets to be relevant and accurate,” continued Berry. “Whether in automotive, banking, oil and gas, or pharmaceuticals, our platform will enable integrations at multiple layers with strategic partners to enable agents to leverage domain-specific knowledge securely.”
