What inspired the inception of your platform combining CRM and Conversational AI?

We realised that traditional CRMs were great at storing data, but not at using it at the moment. Businesses had customer insights, but they weren’t able to act on them in real time. Meanwhile, customers started expecting quick, personalised conversations not delayed or generic replies. That’s when the idea clicked. By integrating Conversational AI with CRM, we could bring data to life, powering smarter, faster, and more human-like interactions. It was about moving from just storing information to actually using it to engage better.

What makes the company’s CRM platform truly ‘conversation-first’? How is it different from traditional CRMs in terms of user experience and functionality?

Most CRMs focus on data entry but we focus on dialogue. From the ground up, our platform is designed to engage, not just record. The interface feels like a messaging app, so users can chat, resolve, and follow up all in real time. It’s not about filling forms or switching tabs; it’s about keeping the conversation flowing, whether with customers or across teams. That shift from task-based to talk-based is what makes it truly conversation-first.

How is your conversational layer different from standard chatbots or voice assistants?

Most chatbots are limited, they follow scripts, answer basic questions, and stop there. Our conversational layer is built to do much more. It’s powered by Agentic AI, which means it understands not just what’s being said, but why and what needs to happen next. It’s closely tied to the CRM, so conversations can trigger real actions updating data, progressing workflows, even closing tickets without any manual steps.

What also sets it apart is how naturally it works across channels. Whether a customer starts on WhatsApp, continues on email, or switches to voice, the conversation stays connected. It feels seamless, personal, and smart. This isn’t just a support tool, it’s a powerful layer that helps teams sell, support, and serve better at every touchpoint.

How does your platform unify structured CRM data with unstructured conversational inputs?

Often, customer information and conversations exist in separate places. Structured data like profiles or purchase history sits in the CRM, while chats, emails, and calls are scattered across different channels. Our platform connects the two.

It uses AI to pick up key details from conversations in real time like what the customer needs or how they’re feeling and links that context directly to their CRM profile. This allows teams to get a fuller picture of the customer and respond more effectively, without switching between tools or losing important information along the way.

Can you explain how Agentic AI powers your CRM? What kind of autonomous actions can your system take?

Agentic AI adds a layer of intelligence that goes beyond rule-based automation. Instead of just reacting to commands, it understands the bigger picture, like customer intent, context, and business goals and takes actions on its own, within the CRM.

For instance, it can pick up early signs of customer churn, such as a drop in activity or negative tone in messages, and automatically trigger retention steps, like alerting a team member or sending a personalized follow-up. It can also flag cold leads, escalate critical issues before they surface, or assign conversations to the right team based on what’s being discussed.

Internally, it helps teams work faster by suggesting next steps, summarising conversations, updating records, or even resolving routine support tickets without needing manual input every time. The goal is to reduce repetitive work and help teams respond with better context, more quickly.

How does Expedify’s CRM manage omnichannel communication? What platforms is it integrated with?

Expedify’s CRM is built to work across almost all major communication channels like email, WhatsApp, SMS, phone calls, voice agents, RCS, and chatbots. It brings everything into one place, so teams don’t have to juggle between tools to stay in touch with leads or customers.

What makes it effective is how it uses context. Whether it’s a new lead or an existing customer, the system can tailor messages and creatives based on past interactions, preferences, and stage in the journey. It also supports personalised communication at scale right from sending targeted campaigns to having one-on-one conversations across channels, all in real time.

What kind of impact has your platform had on sales cycles, support resolution, or lead conversions?

We’ve seen the biggest shift in how quickly and efficiently teams move from lead generation to actual engagement. Our agent layer across voice and messaging, automates everything from lead qualification to scheduling meetings. This means sales reps spend less time chasing unqualified leads and more time talking to the right ones.

It works a bit like a smart filter. The system can identify low-intent or irrelevant leads early on, so time isn’t wasted. At the same time, it ensures high-quality leads don’t fall through the cracks. As a result, the overall sales cycle shortens, support teams respond faster, and conversion rates improve, simply because everyone’s working with better clarity and focus.

How do you balance deep personalization and automation with data security, privacy, and responsible AI use?

We take data security and privacy seriously, especially while working with personalisation at scale. All user data is encrypted and stored in hashed formats to ensure it’s protected. On the AI front, we’re equally cautious. Our systems are designed to use customer data responsibly, with clear guardrails to prevent misuse or overreach. Whether it’s automation or recommendations, everything runs within a secure, compliant framework that puts user trust first.

What’s your vision for how Agentic AI will shape the future of CRM and customer engagement in the next 3–5 years?

Three years is a long horizon in tech, but the shift is already underway. We believe that in the next 12–24 months, much of CRM management from lead activation to follow-ups and campaign execution will be handled autonomously by AI agents.

This doesn’t replace sales and marketing teams; it frees them. Instead of spending time on manual updates or routine outreach, teams will focus more on strategy, building relationships, and solving real problems for customers. Agentic AI will quietly manage the backend, keeping the engine running while people focus on the parts of the job that truly need a human touch.