Q-nomy has introduced AgentFlow to connect AI interactions, enterprise systems and live service teams within a unified customer journey.
Q-nomy, an enterprise customer journey and service orchestration provider, has announced AgentFlow, a new Q-Flow module designed to connect AI-powered interactions with appointments, customer flow, business processes and human-assisted service.
AgentFlow makes AI operational by connecting service AI agents with the systems, rules and people behind the complete customer journey.
AgentFlow enables organisations to build conversational journeys in which customers can obtain information, schedule appointments and complete other service activities through natural-language chat or voice interactions. These journeys can be powered by Q-nomy’s own AI capabilities or integrated with external AI platforms, including Salesforce Agentforce.
Rather than operating as a separate chatbot, AgentFlow connects AI interactions directly to the organisation’s wider service environment. It can use real-time availability and customer and operational data, apply business rules, initiate processes and transfer customers to live service when human assistance is required.
“AI should not become another isolated customer service channel. Its real value emerges when it can participate in the complete journey – accessing operational information, taking action and working alongside service teams. AgentFlow brings these elements together within the same orchestration environment,” said Nadav Arzoan, CEO, Q-nomy.
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One Journey Across AI, Digital and Human Service
Q-nomy’s AI vision is based on the principle that customer journeys will increasingly combine self-service, AI assistance and human expertise. A conversation may begin with an AI agent, continue through appointment scheduling or digital intake, and, when necessary, transition to a remote or in-person team member without losing its context.
AgentFlow extends Q-Flow’s existing journey orchestration capabilities, which support scheduling and preparation, intake and check-in, routing and queue management, service delivery, back-office processes and follow-up. This allows organisations to introduce AI into existing operational journeys rather than creating disconnected AI experiences.
Initial AgentFlow capabilities include AI-assisted appointment booking and customer routing. Organisations can define these experiences using the Q-Flow Journey Builder and connect them to calendars, customer records, service rules, and other enterprise systems.
AgentFlow also supports chatbot-based journeys that follow predefined flows, giving organisations the flexibility to use generative AI where it adds value while retaining more structured interactions for situations that require predictability and control.
An Open Approach to Enterprise AI
AgentFlow is designed to support different AI technologies rather than requiring organisations to adopt a single model or provider. Q-nomy’s approach includes integration with leading enterprise AI platforms, as well as QLM – the Q-nomy LLM Server – for organisations that require greater control over deployment, data and AI infrastructure.
This open architecture allows each organisation to select the AI environment that best matches its security, regulatory, operational and commercial requirements while using Q-Flow as the orchestration layer for the complete service journey.
“Organisations should be able to adopt AI at their own pace and according to their own requirements. Our role is to make AI operational – connecting it with the systems, rules and people needed to deliver an effective service outcome,” said Arzoan.
AgentFlow forms part of Q-nomy’s broader development of Q-Flow as a platform for orchestrating journeys across physical, digital and AI-assisted channels. Additional AgentFlow capabilities and integrations will be introduced as this vision continues to develop.
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