Kore.ai, a global leader in enterprise AI, has officially announced the launch of its AI for Process solution, which happens to be a no-code platform capable of transforming how enterprises automate and optimize knowledge-intensive operations.

According to certain reports, the stated solution makes it possible for organizations to rapidly build, deploy, and manage custom AI agents or Agentic Apps that, on their part, can understand context, make complex decisions, and orchestrate sophisticated Agentic workflows. More on this would reveal how the platform’s agnostic approach to cloud and AI models, customizable tools, and seamless integration with diverse systems, empower organizations to quickly and securely optimize enterprise processes.

To understand the significance of such a development, we must take into account how, going by several studies, traditional process automation is now struggling in terms of decision-making and scaling. As a result, Gartner predicts that agentic AI will be included in 33% of enterprise software applications by 2028.

Building upon this very shift, AI for Process brings forth a proprietary Agentic RAG (Retrieval-Augmented Generation), which can integrate advanced retrieval with intelligent agent orchestration to achieve unprecedented accuracy and contextual understanding.

You see, the technology can understand, reason, and adapt to significantly reduce the need for human intervention, while simultaneously maintaining control over data security, compliance, processes, and outcomes.

Talk about the whole value proposition on a slightly deeper, we begin from its intelligent agent framework & orchestration, which packs together specialized agents designed for specific functions. For instance, the Orchestrator Agent can coordinate workflows, and on the other hand, Reasoning Agents can handle complex decision-making.

Beyond that, Task Agents can be expected to automate workflows, whereas Knowledge Agents will process enterprise information, and API Agents will be tasked with managing system integrations.

Complementing that would be the platform’s sophisticated Agent Evaluation Framework, which assesses agents, evaluates execution plans, tracks milestone achievements, analyzes decision trajectories, conducts minefield evaluations to identify potential risks, and validates tool usage patterns.

Next up, we must dig into the solution’s no-code development environment. This environment is packaged alongside a visual workflow designer, 65+ pre-built prompt templates, and drag-and-drop integration. Furthermore, it features testing, validation, version control, and deployment management tools for easy workflow creation and updates.

Then, there is an Enterprise Integration Hub, which collaborates with commercial or open-source LLMs and major cloud providers like AWS, Azure, and Google Cloud etc. The platform also delivers pre-built connectors for enterprise data sources and APIs, as well as real-time data synchronization to maintain a consistent, up-to-date flow of information across systems.

Another detail worth a mention here stems from a built-in Human-in-the-Loop feature, which seamlessly integrates human touchpoints within automated workflows to enable asynchronous human actions, approvals, and form inputs as natural steps in process completion.

Joining that would be the solution’s take on security and governance, a take which translates to how Kore.ai’s latest brainchild ensures security with data anonymization, protection against prompt injection attacks, custom content filters, and audit trails. There is also set of governance controls that help manage role-based access to data, as AI guardrails and compliance protect against risks in highly regulated industries.

“Traditional enterprise process automation was limited by rigid, rule-based systems lacking any autonomy,” said Raj Koneru, CEO & Founder of Kore.ai. “With the advent of advanced AI models capable of evaluation and reasoning, we’re ushering in a new era where intelligent AI agents can independently manage business processes, reducing over-reliance on human support. AI for Process enables enterprises to design scalable, reliable Agentic Apps that redefine efficiency while elevating humans into more strategic, supervisory roles.”

Among other things, we ought to mention how AI for Process is delivering transformative automation efficiencies for customers, achieving 40-60% faster processing, 35-45% operational cost savings, and almost 60% reduction in human review dependency. A more specific example is provided by one leading North American healthcare provider who realized a 30-second reduction in average handle time (AHT), along with a 90% improvement in call wrap accuracy.

As for some of the early use cases, they include customer support, loan application and KYC processing, support ticket analysis, automated knowledge creation, contract analysis, lead processing, proposal generation, and more.