Aquant Introduces Retrieval-Augmented Conversation

Aquant, providers of an agentic artificial intelligence solution for service professionals, has launched Retrieval-Augmented Conversation (RAC), an AI model that engages users in fully guided, context-aware dialogues.

In contrast to traditional RAG systems that return long, static answers from manuals or FAQs, RAC actually engages in multi-turn dialogues. It retrieves and makes sense of real-time data such as IoT readings, ERP history, and job logs, and adjusts its communication according to user experience level and operational context.

"RAG explains a solution, but RAC guides you toward an outcome," said Indresh Satyanarayana, vice president of poroduct technology and labs at Aquant, in a statement. "We created RAC to mimic the minds of the best technicians in the business, asking clarifying questions, taking context from work history, parts data, company-specific objectives, and real-time telemetry, then guiding each user through the next-best step until the root cause of the problem is solved."

"Enterprise teams don’t need another smart search bar; they need an expert partner by their side in every conversation," said Assaf Melochna, president and co-founder of Aquant, in a statement. "RAC transforms AI from a passive responder to a proactive problem-solver. It's not just about reducing resolution times. It's about allowing front-line service teams to fix issues faster, with more confidence, and with less escalation."