“AI is not a vision for the future. AI is the foundation of the modern enterprise.”
That’s the message Uniphore CEO & Cofounder, Umesh Sachdev, shared with CIOs and other enterprise leaders at Uniphore’s 2025 AI Leadership Summit.
Speaking to a packed house at the Waldorf Hilton in London, Sachdev discussed the next evolutionary phase of AI—agentic systems that can reason, act and drive measurable business outcomes—and how Uniphore’s visionary Business AI platform is turning enterprises into agent factories by solving their biggest data, modeling and usability challenges and preparing them for whatever the future of AI may bring.
AI is evolving faster than businesses can keep up.
“Two and a half years ago, we got our first taste of large language models (LLMs) in an easily usable user application in the form of ChatGPT,” said Rowan Curran, Principle Analyst of Agentic AI at Forrester. “Throughout 2024 and into this year, we’re seeing enterprises wanting to connect large language models to their enterprise data. We’re seeing this manifest in LLMs [that are] grounded in the answers and content that’s relevant to the enterprise.”
However, while the appetite for enterprise-specific LLM (and SLM) applications is undeniable, until now, no solution has been able to bring the pieces together—data, knowledge, models and agentic AI—in a user-friendly format that preserves the security, control and scalability enterprises require. That’s because most solutions today either zero in on a specific part of the AI pipeline (i.e., point solutions) or promise an all-in-one suite of what Curran calls “agent-ish” AI capabilities (i.e., hyper-scaler solutions). Neither approach addresses the foundational barriers that keep agentic AI perpetually in experimental mode.
Watch the 2025 AI Leadership Summit
Hear from AI leaders and see live demos of the innovations that are redefining business AI.
AI isn’t agents or models or data. It’s all that—and more.
Sharing the stage with Sachdev and Curran were leaders from Konecta, KPMG, Adecco and ResultsCX—some of today’s most innovative AI industry users. Sharing their experiences deploying AI in business process management, customer experience management, recruitment and compliance, they revealed that biggest obstacle to widespread AI adoption isn’t a lack of AI and data solutions but a way to unify them in a way that drives sustainable business outcomes.
For AI to deliver real business outcomes, it must first solve the challenges inherent in every enterprise tech stack—from the ground up. “AI is not an agent. It’s not a model. It’s a complete platform,” said Sachdev. Uniphore’s platform, he explained, creates a four-layer foundation that addresses the critical barriers that block 90% of AI pilots from moving into production:
The Data Layer
“Discovering data and making it available for AI is the first major challenge,” Sachdev stated. “Without [addressing this], we cannot deliver any business outcome with AI.” Housed within its Business AI platform, Uniphore’s Data Layer enables businesses to discover and access data from anywhere and in any format without copying, moving or transforming it. This zero-copy architecture unlocks all enterprise data—including siloed, unstructured and multilocational data—for AI usage.
“That de-clogging of the systems, which is everything around data, getting your processes and systems ready for data, getting your people agenda aligned to the forthcoming [agentic AI] transformation—that has been a big part of our conversations most recently. Almost every single customer is thinking about this.”
— Prasad Jayaraman – Principle, KPMG
The Knowledge Layer
The next layer in the platform, the Knowledge Layer, converts complex enterprise data into structured, contextualized and governed knowledge. Using industrialized, multimodal RAG, knowledge graphs, fine-tuning and built-in guardrails, this layer transforms data into an accurate and actionable knowledge stream for training LLMs and/or SLMs to truly become an enterprise’s own.
The Model Layer
Enterprises today can choose from thousands of large and small language models, with new models appearing almost daily. Uniphore’s Model Layer brings the open-source world of LLMs and the proprietary world of SLMs under one roof. This hybrid approach enables businesses to choose the model (or models) that best fit their needs and “plug in” new innovations as they emerge in near real time. As a result, organizations have the flexibility to orchestrate their models and extract the full power from them via Uniphore’s AI Cloud.
“Building a large language model for, say, a utility, for insurance, for banking, [for] all these regulatory companies, where all the participants participate by contributing their data and then customizing it as small language models and solving their problems will enable [them to] drive lifetime value.”
— Rajesh Subramaniam, CEO – ResultsCX
The Agentic Layer
“Today, agentic AI augments workflows and lifecycles,” Curran explains. “Tomorrow, it will orchestrate and execute.” That’s already happening in Uniphore’s platform—at the Agentic Layer. Here, businesses can create reasoning agents, workflow agents and task-oriented agents using a simple, user-friendly interface. And with Model Control Protocol (MCP), they can bring in other companies’ and other people’s agents to deliver automation at a scale that’s never been seen before.
Building a foundation on sovereignty, composability and security
Uniphore’s four-layer Business AI Cloud provides enterprises with the foundation for ongoing AI success—no matter how the technology evolves. That’s because each layer is built on three guiding principles.
Sovereignty
“Uniphores Business AI Cloud can run on any hyperscaler, can run on your virtual private cloud and can run on premises,” shared Sachdev. “[It’s] “truly sovereign: your intellectual property, your data, your model.” That’s huge for enterprises looking to control their own destiny with AI.
And it’s not just data ownership that matters. “When we’re talking about AI sovereignty today, there’s the sovereignty of the data, wherever the data lives [and] there’s the sovereignty of the model itself,” explains Curran. “All three of those pieces are really important for building a sovereign AI system that you have full control over.”
“We have so many systems across so many jurisdictions, across so many countries. Sovereignty […] was one of our big elements in terms of challenges we put in front of [Uniphore]. One by one, going from POC to production, we’ve been able to start seeing operational KPIs improve and, most importantly, our [people] using the actual technology that has been built together.”
— Mike Small – President, The Adecco Group
Composability
How do you build a workable framework for an ecosystem that’s constantly changing? You make it composable. Uniphore’s platform is built on the principle of composability or openness. “[That] means when Snowflake delivers a new data warehouse, when DeepSeek delivers a new LLM, when OpenAI comes out with a new innovation, you’re not being locked into an older investment,” Sachdev explained. “All of the layers of the platform are completely open, and we will make those newer innovations available as they come about.”
Security
For many in attendance, AI and data security are top of mind. In fact, it’s become one of the most critical priorities in boardrooms worldwide, according to Forbes. Speaking to this concern, Sachdev revealed how Uniphore’s platform strengthens security—while maintaining the openness needed for innovation—with built-in safeguards: “Security in the AI world is supremely important. [Our platform provides] the ability to have guardrails decided and applied at all times; the ability to have—at the touch of a button—a report that says, ‘this AI was not biased’, so your customers and your teams can have the comfort of using AI.”
Introducing the Business AI Cloud—live and on stage
Summit attendees not only had the opportunity to hear about Uniphore’s Business AI Cloud; they got to see it in action. Saurabh Saxena, Head of Technology and VP of Engineering at Uniphore, led a live—not prerecorded—demonstration of the powerful platform, highlighting the ease with which users can navigate each layer to create a fully functioning AI agent. Using insurance claims as an example, Saxena was able to:
- Connect to multiple data sources—including unstructured sources (i.e. handwritten claims, printed medical forms)—and convert them to vector sources and graphs—without copying or moving the data
- Match the data with the best SLM model, based on accuracy, cost and latency
- Ask plain language questions of the data using Knowledge Q&A
- Initiate continuous self-testing and self-improvement (via Uniphore’s Fine-Tuning Studio)
- Create a multi-agent workflow for processing claims—in plain English
- And, lastly, run the agent...
…All in a matter of minutes.
“That process previously would have taken multiple human agents a lot of time to complete,” said Saxena, referring to the typically large tech stack the platform easily engaged with. “To build a true business AI platform and an AI stack, today [enterprises] will need to take about two dozen different technologies and weave them together. It’s complex; it’s daunting. We built this platform so you don’t have to be an AI vendor to be able to use enterprise AI in your business.”
The Age of Business AI isn’t coming soon. It’s already here.
Over the past two and a half years, enterprises have largely experimented with agentic AI. Several have even pushed agentic prototypes into the real world—only to see them stall when the technology inevitably evolves. Uniphore’s Business AI Cloud, Sachdev explains, changes that: “AI is no longer experimental. CIOs and CEOs around the world are beginning to push their teams about delivering business outcomes, delivering results. We are moving from an era of static tools and apps to an era of agents.”
By creating a sovereign, composable and secure foundation for all AI—today and in the future—Uniphore enables businesses to not only build reasoning agents and multi-agentic workflows with consumer-like ease; it empowers them to move from proof-of-concept to production quickly and confidently.
“We spent lots of time experimenting without real business outcome. So, we started from business objectives, in terms of the KPIs we want to focus on, and we proceeded to do this in production. We managed to overcome a number of issues we had with our customers, and now, together [with Uniphore], we’ve managed to deliver material impact to all the KPIs we expected.”
— Adil Tahiri – Head of Advisory & Professional Services, Konecta
“Make no mistake, we are in an era where the pace of innovation is unprecedented,” said Sachdev. “The vision we have is for business users who know the process—all they have to do is give a goal and an intention to an AI agent, and let the system do everything.”
As AI continues to evolve at its breakneck speed, one thing remains constant: Uniphore will keep pushing the envelope. In addition to our future-proof Business AI platform, Umesh revealed another innovation coming this fall: the Business AI User Interface. This remarkably intuitive agentic AI interface will enable enterprises across the globe to become agent factories.
According to Sachdev, that’s the ultimate goal. “That’s what we want you all to be: an agentic AI factory within your companies.”
And we're celebrating it together
Of course, after announcing news this big, we had to celebrate. Coming together as one team, with our customers and partners, we toasted to the exciting future we’ve paved the way for. As we continue to redefine what AI can do for businesses, we invite everyone to join the celebration—and the journey forward—with Uniphore.
Watch the 2025 AI Leadership Summit
Hear from AI leaders and see live demos of the innovations that are redefining business AI.
