What problems do AI chatbots solve in B2B sales?

AI chatbots solve three problems in B2B sales: instant answers, consistent technical information, and intent capture. The core challenge is that B2B buying involves complex technical evaluation across multiple stakeholders, but traditional chatbots only handle scripted responses. Buyers wait days for sales engineers to answer API questions, champions can't get answers for internal teams, and sellers spend hours on repetitive calls. Riff approaches this differently by creating a verified knowledge layer that functions as an always-on product expert. Instead of scripted flows that break when buyers ask real questions, it indexes actual product documentation, technical specs, and implementation details to deliver contextual answers matched to the buyer's role and stage. What this solves in practice: • Eliminates scheduling calls just to answer "Does your API support webhooks?" or "How does enterprise pricing work?" • Lets technical evaluators self-serve through deep product questions without waiting on solutions engineers • Enables champions to share conversation threads with stakeholders, building internal consensus asynchronously • Captures first-party intent data from every question, showing exactly what buyers care about before talking to sales This matters especially when buyers research outside business hours or across time zones. A developer evaluating a product at 11pm gets the same accurate technical answers they'd get from the best sales engineer, and that conversation automatically qualifies them based on question depth and type. The broader shift is that B2B buyers expect consumer-grade self-serve experiences with enterprise-grade accuracy. Riff addresses this by treating knowledge as a product itself, not just a support function. When 75% of buyers prefer self-serve research, companies that win deliver instant, trusted answers without forcing prospects into a sales process before they're ready.