Nintex unveils new native AI capabilities that enable organizations to build and orchestrate AI agents alongside people, workflows, and systems<\/p>\n
Nintex, a global leader in agentic business orchestration, today announced\u00a0Nintex Agent Designer and Nintex Orchestration, new agentic AI and business orchestration capabilities available to select customers natively in\u00a0Nintex CE. Together, these help organizations design and orchestrate AI agents alongside people, workflows, and core systems to deliver consistent results at scale.<\/p>\n
\u201cRather than replacing structured processes with fully autonomous systems, organizations today want platforms that support both deterministic and agentic approaches across a single orchestration framework,\u201d said Arnal Dayaratna, Research Vice President, Software Development at IDC. \u201cA blended approach allows organizations to apply agentic AI where judgment and interpretation add value, while maintaining conditional workflow control where precision and compliance are required. This ability to coordinate both models within business workflows is a critical requirement for scaling AI adoption.\u201d<\/p>\n
As organizations accelerate AI adoption, many are rethinking how it is embedded into day-to-day operations. Nintex\u2019s\u00a0AI UNLESS report\u00a0found that 64% of business leaders are embedding or consolidating AI into broader automation strategies to create unified platforms that orchestrate people, systems, and AI agents. However, without orchestration, AI initiatives often remain disconnected from workflows, human decision points, and core business systems, limiting business impact and creating governance risk.<\/p>\n
Organizations now need platforms that support both deterministic and non-deterministic execution patterns, allowing AI agents to operate where judgment is required, while structured controls guide high-stakes transactions. To operationalize this blended model, organizations must be able to build, deploy, and orchestrate agents as part of governed orchestration design, not as standalone automation experiments.<\/p>\n
New Nintex Agent Designer and Orchestration capabilities will enable enterprises to design, deploy, and coordinate AI agents within real business workflows<\/p>\n
Nintex Orchestration allows builders to transform complex monolithic processes into modular execution phases with dynamic progression between phases. Agent Designer allows builders to embed agents into this phase-based orchestration to ensure that AI agents, human decision-makers, and business systems operate in a coordinated and governed manner. This blended execution model enables organizations to:<\/p>\n
Apply AI where judgment and interpretation add value<\/p>\n
Preserve conditional workflow control where precision and compliance are critical<\/p>\n
Design for 24\/7 intelligent execution<\/p>\n
Establish the foundation for measuring and improving agent performance over time<\/p>\n
\u201cAI for modern business cannot be purely agentic, nor purely deterministic; it must support both,\u201d said Niranjan Vijayaragavan, Chief Product and Technology Officer at Nintex. \u201cOur agentic business orchestration vision is built on enabling deterministic workflows and adaptive agents to operate within the same process framework, alongside human oversight. With Agent Designer and Orchestration, organizations can apply AI where judgment adds value while preserving control where precision and compliance matter most.\u201d<\/p>\n
Nintex Agent Designer enables teams to build adaptive AI agents, including supervisor and multi-agent patterns, that operate directly within orchestrated workflows.<\/p>\n
These agents can:<\/p>\n
Plan and execute multi-step actions<\/p>\n
Retrieve contextual information to inform decisions<\/p>\n
Escalate to humans when deterministic control is required<\/p>\n
Nintex Orchestration enables dynamic case-based process execution that evolves over time. Instead of rigid, linear flows, orchestration supports modular workflow phases that can advance, repeat, escalate, or reroute based on real-time context.<\/p>\n
This design allows organizations to:<\/p>\n
Support both deterministic rules-based processing and probabilistic, agent-driven decision support<\/p>\n
Use enterprise tools and automation components such as RPA, document processing, and system connectors<\/p>\n
Maintain full visibility across long-running process lifecycles<\/p>\n
Scale complex operations without sacrificing control<\/p>\n
Manage exceptions as a natural part of execution<\/p>\n
By supporting multiple orchestration design patterns, including adaptive case management, organizations can structure work in a way that reflects how real business processes unfold. By embedding agents inside governed orchestration, rather than deploying them as standalone tools, organizations can balance autonomy with oversight, ensuring AI-driven actions align with business rules, compliance requirements, and operational goals.<\/p>\n
\u201cThis is a game-changer. Nintex Agent Designer represents the future of workflow automation, combining intelligence with governance in a powerful new way,\u201d said Kevin Schall, CEO, AiGS \u2013 Ai Global Solutions. \u201cWith capabilities such as supervisor agents, Nintex is enabling organizations to introduce advanced AI-driven automation while maintaining the oversight and trust that users expect from agentic AI systems.\u201dThe post Nintex Unveils Agentic Orchestration to Scale AI Automation first appeared on AI-Tech Park.<\/p>\n","protected":false},"excerpt":{"rendered":"
Nintex unveils new native AI capabilities that enable organizations to build and orchestrate AI agents alongside people, workflows, and systems Nintex, a global leader in agentic business orchestration, today announced\u00a0Nintex Agent Designer and Nintex Orchestration, new agentic AI and business orchestration capabilities available to select customers natively in\u00a0Nintex CE. Together,…<\/p>\n
The post Nintex Unveils Agentic Orchestration to Scale AI Automation<\/a> first appeared on AI-Tech Park<\/a>.<\/p>\n<\/div>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-container-style":"default","site-container-layout":"default","site-sidebar-layout":"default","disable-article-header":"default","disable-site-header":"default","disable-site-footer":"default","disable-content-area-spacing":"default","footnotes":""},"categories":[1,385],"tags":[3],"class_list":["post-2013","post","type-post","status-publish","format-standard","hentry","category-ai-and-ml","category-rpa","tag-ai"],"yoast_head":"\n