Aquant today announced the official launch and unveiling of Retrieval-Augmented Conversation (RAC). This groundbreaking AI model leaps beyond conventional enterprise problem-solving by going beyond brief one-shot answers to fully guided, context-aware dialogue.
“RAG explains a solution, but RAC guides you towards an outcome,” said Indresh Satyanarayana, VP of Product Technology & Labs at Aquant. “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.”
RAC is the subsequent development in the evolution of Retrieval-Augmented Generation (RAG), which changed enterprise AI by grounding outputs on trusted documentation. However, in advanced, high-stress environments like field service, customer experience, and complex machinery maintenance, RAG-based solutions are beginning to show their faults more and more, failing to resolve real-world issues that require conversation, complexity, and multi-step action.
“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. “RAC transforms AI from a passive responder to a proactive problem-solver. It’s not just about reducing resolution times. It’s about allowing frontline service teams to fix issues faster, with more confidence, and with less escalation.”
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.
Today, Aquant launched RAC to the public on a live webinar, where leaders walked through the technology’s architecture, real-world use cases, and the quantifiable results RAC will deliver. To learn about RAC in detail, you can read Aquant’s whitepaper, Beyond RAG: Why Enterprises Need Retrieval-Augmented Conversation (RAC), by RAC creator Indresh Satyanarayana.
