SRMB Steel Scales Multilingual Sales and Customer Support with Rootle Voice AI

SRMB Steel: Building India's Infrastructure, One TMT Bar at a Time

SRMB Steel is one of India's most recognized names in TMT rebars and structural steel, with a legacy built on serving the country's construction and infrastructure sectors. Their customer base is genuinely diverse, spanning large enterprise buyers placing bulk procurement orders, distributors and dealers managing regional supply chains, contractors and project managers sourcing steel for active sites, and individual buyers purchasing retail quantities.

This diversity is a strength, but it also demands a level of operational sophistication that a single, one-size-fits-all communication approach simply can't deliver. Each customer segment has different information needs, different buying signals, and different expectations from every interaction.

A Sales Operation Built to Grow, Ready for the Next Level

SRMB's inside sales team was doing solid work. Ten callers running approximately 80 calls a day, six days a week, across a Tata dialer with ten active channels. For a company managing multiple distinct buyer profiles simultaneously, this was a team that clearly knew what it was doing.

But certain realities were becoming harder to ignore. The sheer breadth of the customer base, each segment with its own conversation flow, qualification criteria, and CRM classification, meant the cognitive load on callers was significant. There was also a genuine opportunity to handle inbound queries, order status checks, invoice questions, and dealer communications at far greater volume and consistency than a ten-person team could realistically sustain. The question wasn't whether the team was good enough. The question was how far automation could carry the routine work, so the human callers could focus where it genuinely matters.

Three Use Cases. One Intelligent Voice Layer.

Rootle designed and deployed a multilingual Voice AI system for SRMB built around three distinct use cases, each with its own conversation logic, qualification flow, and CRM sync behavior. All three ran on Rootle's own infrastructure, with multiple numbers assigned to handle volume without the constraints of a third-party dialer.

Hindi, English, and Bengali. In One Deployment.

Steel is sold across geographies and communities that don't share a single language preference. SRMB's customer base spans Hindi-speaking markets, English-comfortable corporate buyers, and Bengali-speaking regions where natural, local-language conversation isn't a nice-to-have but a commercial necessity.

Rootle's Voice AI handles all three natively, not through literal translation, but through conversations built to feel right in each language. A contractor in Bengal gets a conversation that sounds like a local call. An enterprise procurement head gets the tone and vocabulary they'd expect in a professional B2B exchange. The language adapts. The quality of the interaction doesn't change.

Built on Rootle's Own Infrastructure, Not a Dialer Dependency

One of the important decisions in this deployment was stepping away from a third-party dialer as the primary calling infrastructure. SRMB's earlier setup ran on a Tata dialer with ten channels, which created a hard ceiling on concurrent call capacity. Rootle replaced this with its own calling infrastructure, assigning multiple numbers to handle the volume SRMB actually needed to reach.

This shift also removed the per-channel constraint on outbound scale. When campaign volume increases or new use cases get added, SRMB isn't waiting on a dialer configuration change or license expansion. The infrastructure grows with the requirement.

The SRMB Voice AI Call Flow

Every call, whether it arrives inbound or goes out as part of a campaign, follows a structured path. The AI detects who it's speaking with, switches to the right language, follows the appropriate conversation flow for that buyer type, and closes the loop with an automated CRM entry. Here's what that looks like end to end.

What Changed After Rootle Went Live

The changes SRMB experienced weren't incremental adjustments to an existing operation. Deploying Rootle across three use cases simultaneously, with multilingual support and two-system CRM integration, restructured how the sales and support function actually works.

Complexity Handled, Not Avoided

Most Voice AI deployments struggle when the customer base isn't uniform. SRMB's diversity, five buyer profiles across B2B and B2C, three languages, two backend systems, and both inbound and outbound requirements, is exactly the kind of scenario that exposes the limits of a plug-and-play solution.

Rootle's approach was to design workflows that match how SRMB actually operates rather than ask SRMB to operate the way a generic system expects. Each buyer segment got its own conversation logic. Each language got its own natural speech design. The CRM integration was built to classify correctly from the start, not to push raw data and let someone sort it out later.

The result is a Voice AI layer that the sales team actually relies on, because it reflects their business accurately, speaks to their customers naturally, and keeps their data clean without any extra effort on their end.