Qualified, from Salesforce, is an agentic marketing and conversational platform that uses an AI Sales Development Representative (SDR) agent named “Piper” to help B2B companies identify high-intent website visitors and generate a sales pipeline in real-time. Pulse 2.0 interviewed Qualified CMO Maura Rivera to learn more.
Maura Rivera’s Background
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Can you share a brief overview of your background? Rivera said:
“I’ve always gravitated toward roles where marketing, product, and sales intersect. Early in my career, I spent several years at Salesforce, which deeply shaped how I think about category creation and the relationship between great storytelling and great technology. From there I helped scale GetFeedback, and eventually joined Qualified when the team was still small and building toward a big vision: the belief that the website could become a company’s most powerful sales channel.”
“As AI matured, that belief expanded. Today, as CMO, I spend most of my time helping revenue teams understand how AI can work with them, not instead of them. Piper was born from that idea: AI that feels like a teammate, not a tool you bolt on.”
Inspiration Of Piper
What inspired the development of Piper, and how did it evolve from Qualified’s earlier AI SDR capabilities? Rivera shared:
“We saw two big shifts colliding. First, AI finally became good enough to handle real sales conversations, not just scripted chatbots. Second, revenue teams were under intense pressure to grow pipeline without adding more headcount. “Do more with less” became the mantra of every revenue leader in 2022, and as AI became more accessible, they seemed to go hand in hand.”
“We’ve always been at the forefront of conversational marketing tech, offering the best ways to meet your buyers where they are, identify intent, and convert them into a meeting–AI has supercharged those capabilities.”
“Our first-generation AI SDR agent validated that an autonomous agent could qualify inbound traffic and book meetings reliably. Piper is the natural evolution: a multi-modal, multi-channel “superagent” that works across the entire inbound funnel, not just the website.”
Role During The Launch
What has been your role in shaping Piper, and what have been your primary responsibilities during the launch? Rivera explained:
“My team owns the story, the positioning, and the proof. On the front end, that means working closely with product and sales to clarify who Piper is for and what problems it truly solves. On the back end, it means building customer programs, case studies, and benchmarks so we can show, not just tell, what AI SDR “superagents” can deliver in real pipeline and revenue terms. This is such a new space, customer proof is the most vital aspect of our launch marketing.”
Standout Moment
What’s been a standout moment for you during the development and rollout of Piper? Rivera reflected:
“Watching our own revenue team flip the switch and let Piper handle 100% of inbound conversations, and then layering her into outbound and nurture, was a watershed moment. Seeing reps come in on a Monday with a calendar full of meetings booked while they were offline made it clear we weren’t launching a feature. We were launching a new kind of teammate.”
Building Something Durable
AI is moving incredibly fast. How did you approach building something durable rather than chasing the trend of the moment? Rivera pointed out:
“Durability comes from solving timeless GTM problems: qualifying interest, responding in real time, following up consistently, and reducing operational drag.”
“Trends come and go, but those problems won’t. So we designed Piper around reliability, strong guardrails, deep data integrations, and predictable performance: the things that endure regardless of which model is hottest this quarter.”
Superagent For Revenue Teams
Piper is described as a full-funnel AI “superagent.” What does that mean in practice for revenue teams? Rivera noted:
“It means Piper isn’t limited to one moment in the buyer journey. Piper can greet someone on your website, continue the conversation via email, answer technical questions, qualify, route, and book meetings, all with shared context.
In practice, that translates to:
- faster speed-to-lead
- more predictable pipeline creation
- fewer dropped threads
- and reps who can spend more time actually selling
Piper performs the way your best human SDR performs, but tirelessly and across channels.”
Slack Integration
Qualified has a deep Slack integration. Why is Slack such an important surface for AI agents in the GTM workflow? Rivera commented:
“Slack has become the operating system for go-to-market teams. It’s where decisions are made, handoffs happen, and pipeline conversations live. Embedding Piper into that flow lets teams collaborate with the agent, review conversations, approve actions, or jump in when needed, all without leaving the place they already work.”
Learnings From Watching Customers Adopt AI Agents
What have you learned from watching customers adopt AI agents? What separates successful rollouts from those that stall? Rivera revealed:
“Successful teams treat AI like a teammate. They stay close to early data, tune messaging quickly, and create clear qualification and handoff logic. They also assign an internal owner who shepherds the first few weeks.”
“Rollouts stall when teams treat the agent as ‘set-and-forget.’ Even powerful AI needs thoughtful onboarding, just like a human hire.”
Designing Guardrails
Building trust in AI is challenging. How did you design guardrails so leaders feel confident putting Piper in front of real buyers? Rivera acknowledged:
“We built Piper around transparency, control, and safety. Leaders can see every conversation, set boundaries, tune behavior, and tightly manage what data Piper accesses.”
“We also added compliance and tone controls, strict permissions, and clear escalation paths. Trust is earned, not assumed; so we made Piper observable, adjustable, and operationally safe.”
Biggest Opportunities
Finally, what excites you most about where agentic AI is heading? Where do you see the biggest opportunities for marketers and revenue teams? Rivera concluded:
“We’re moving toward hybrid GTM teams where humans and AI teammates work side by side. Agents will handle research, follow-up, qualification, and multi-threaded nurturing in the background, almost like an invisible operating layer.”
“For marketers and revenue teams, this is a chance to scale motions that historically relied on manual effort. It’s less about replacing humans and more about giving them the leverage to do their best work.”
