RevRag.AI’s Bold Vision to Reinvent B2B Sales with AI Agents

 RevRag.AI, a Bengaluru-based, India’s first AI-driven B2B sales startup, focused on revolutionizing with AI agents, particularly Emma, and more recently Sophie. They aim to automate tasks, improve efficiency, and enhance customer engagement.

RevRag.AI has raised $600K in pre-seed funding from Viral Bajaria, CRED founder Kunal Shah, Deepak Anchala, Vetri Vellore, and other angel investors. They are actively seeking further investment to expand their product and features.

RevRag's says its mission is to assist, not replace, sales teams. Now, RevRag is expanding its AI capabilities into AI Calling, driven by strong demand from EdTech, HRTech, FinTech, BFSI, consumer brands, and HealthTech.

Ashutosh Prakash Singh, Co-founder & CEO, RevRag.AI in a conversation with CiOL shares his vision for transforming B2B sales, and the growing role of AI in revenue generation. Excerpts.

AI-led automation in sales isn't new, so what’s broken in the traditional B2B sales development model that RevRag.AI is fixing?

That’s exactly the question we asked ourselves when we started building RevRag.AI. Most sales automation tools focus on outreach — sending more emails, making more calls, or improving SDR efficiency. But the real problem lies deeper in the funnel: conversion drop-offs, onboarding friction, incomplete applications, and lost leads due to scattered follow-ups.

RevRag.AI addresses this gap by deploying AI agents that don’t just assist — they act. Our agents guide users through sales and onboarding journeys, proactively recover drop-offs, and engage across voice, chat, and in-app flows in real time. They’re deeply embedded into the company’s workflows, not just sitting in a CRM or chatbot window, and they’re trained specifically for regulated, high-stakes environments like BFSI and Fintech.

What differentiates us is not just the AI — it’s the orchestration, compliance readiness, and business outcome alignment. Our agents aren’t just answering queries; they’re driving revenue.

Where do you draw the line between automation and the human touch in digital onboarding? How are pilot customers responding?

We believe the sweet spot lies in building AI that feels human enough to convert, but smart enough to know when to escalate. Our agents handle repetitive, high-volume interactions, guiding users through document uploads, addressing common onboarding blockers, or reactivating cold leads.

But when it comes to decision points that need empathy, judgment, or negotiation, like upselling, retention risks, or conflict resolution, our system can route the lead to a human instantly, with full context. This gives revenue teams leverage without replacing them.

The response from pilot customers has been very encouraging. Many tell us our agents recover leads that would’ve otherwise been lost. One of the biggest wins has been improved onboarding completion rates without adding headcount. Customers are realizing it’s not about replacing humans; it’s about making every human in the loop more effective.

With early traction and backing from seasoned investors like Kunal Shah and Vetri Vellore, what critical feedback has shaped your roadmap?

Our early backers have been incredibly hands-on, not just with capital, but with clarity.

One piece of feedback that stuck with us was: “Don’t just build automation. Build accountability.” That led us to design our agents with clear outcome measurement — tracking not just engagement, but actual revenue lift, drop-off recovery, and lead conversion rates. We now anchor every deployment around a revenue use case.

Another insight was to build modularity into our system. Thanks to that, companies can start small — say, with a single use case like KYC recovery — and expand over time to multiple agents across onboarding, sales, and reactivation. That has made our enterprise sales motion more scalable and our deployments more adaptable.

RevRag was founded by three childhood friends. How does that influence your leadership style and culture?

It’s rare, but we’re incredibly grateful for it. Knowing each other for over a decade brings built-in trust, low ego, and a deep sense of ownership. We’ve seen each other in high-pressure situations, made mistakes, and built things together before this, and that history shapes how we lead.

As founders, we share responsibility, but also play to our strengths — GTM, product, and engineering. That balance helps us move fast without stepping on each other’s toes.

Culturally, it sets the tone for transparency and speed. People who join RevRag.AI often say they feel the pace and trust from day one. We don’t believe in layers of bureaucracy. We care about execution, learning, and doing right by the customer.

What are the biggest hurdles as you scale, and how are you planning to overcome them?

We see three major challenges ahead: building deeper AI explainability, operationalizing scale in enterprise environments, and hiring the right people without losing our cultural DNA.

Technically, our biggest investment is in explainable AI — ensuring our agents can operate securely in regulated workflows, and every action they take can be audited or traced. We’re working closely with BFSI teams to ensure this remains a strength as we scale.

Operationally, working with large enterprises requires rigor. We’re putting scalable processes in place for deployment, support, and performance monitoring — all while staying lean and nimble.

And finally, as we grow our team, we’re focused on hiring people who match our obsession with customer outcomes and enjoy building in fast, feedback-driven environments. We know momentum is fragile — and our goal is to grow with discipline, without compromising speed or trust.

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