Uniphore, the Business AI company, has officially announced the launch of Uniphore Business AI Cloud, which would be a sovereign, composable, and secure platform, designed to combine the simplicity of consumer AI with enterprise-grade security and scalability.
To understand the significance of such a development, we must take into account how, even though AI technologies are effectively changing the entire enterprise landscape, there remains little to no focus on deploying AI in a way which can empower CIOs to scale it securely across the organization. These limitations are also keeping business users from intuitively accessing AI with the full power of enterprise data, integrations, and context.
Against that, Uniphore’s Business AI Cloud brings to the fore an agentic enterprise solution, focused on using a full-stack AI platform which covers data, knowledge, models, and agents. More on that would reveal how the solution in question allows for business users to deploy AI agents and tap into enterprise knowledge instantly.
This it does while simultaneously giving CIOs the foundation to deliver secure, embedded AI applications trained on enterprise data.
“We’re building an agentic AI factory, designed to rapidly create, deploy and orchestrate AI agents across our customer environments,” said Oscar Vergé, chief AI deployment officer, Konecta. “The platform’s agent builder, orchestration engine and support for both prebuilt and custom agents allow us to agentify critical workflows for each client, from customer service to back-office automation. This isn’t just AI adoption — it’s real transformation at enterprise scale.”
Talk about the whole value proposition on a slightly deeper level, we begin from the technology’s underlying data layer, a zero-copy, composable data fabric, capable of connecting to any platform, application, or cloud, as well as querying and preparing data where it can eventually eliminate migrations and accelerate AI adoption.
Next up, we have a knowledge layer coming into play, which will structure and contextualize enterprise data into AI-ready knowledge retrieval, thus enabling proprietary SLM fine-tuning.
“Most AI solutions today were built for consumers or researchers, not for enterprises,” said Umesh Sachdev, CEO and Co-founder, Uniphore. “Uniphore Business AI Cloud changes that. We’ve brought together four critical layers of the AI stack: data, knowledge, models, and agents. CIOs can now deploy AI securely at scale, retaining ownership of AI governance, while enabling business users to drive the experience and the value.”
Another detail worth a mention is rooted in the availability of a model layer, something open and interoperable with both closed- and open-source LLMs. Here, the idea is to let enterprises apply guardrails and governance to models, along with orchestrating and swapping models without rework as technologies evolve.
Joining that would be an agentic layer, which will offer pre-built enterprise-grade agents and a natural language agent builder, packaged next to a Business Process Model and Notation (BPMN) based orchestration for deploying AI into real workflows across sales, marketing, service, HR, and more.
Turning our attention towards the new solution’s sovereign nature, it translates to how Uniphore supports cloud, multi-cloud, and on-premises deployments of enterprise AI agents and apps, helping enterprises retain control over their data, models, and AI workflows. On top of it, leveraging unique zero-copy architecture, Uniphore can also ensure that data remains in place, and therefore, meets privacy, regulatory, and governance requirements.
Then, there is the compostability factor. You see, Uniphore integrates with existing enterprise technology and data stacks and connects to any AI data source, model, or application. Such flexibility should tread up a long distance to facilitate deployment without lock-in to a specific vendor, model, or architecture.
Rounding up highlights would be a focus on security, stemming from Uniphore’s bid to install AI-specific protections, including guardrails to control model behavior, observability, granular governance, and adversarial prompt defense, along with ongoing red-teaming to ensure system resilience and compliance.
“Uniphore’s agentic suite of applications stand out not only for their enterprise-grade applicability but for how effectively they can enable a transition to Agentic-based workflows,” said Luis Alonso, Head of Customer Data Strategy & Engineering, Global Marketing Data Sciences, HP. “We’ve seen firsthand how their Marketing AI CDP drives our business forward by giving self-serve access to data for our marketing teams.”
