Presented by Salesforce
Smarsh, a global provider of cloud-native, AI-powered solutions that capture, store, and analyze communications data and intelligence for highly regulated industries, set an ambitious goal: use AI to enhance your workforce and increase productivity by 30%. But its customer service team had already identified the real challenge – customers navigating the maze of products, documentation and compliance requirements.
The solution wasn’t just more automation. It was a single, intelligent entry point into support.
"At the team level we asked ourselves, how can we become a better support organization for our regulated industry customers, given that we keep acquiring companies and we have so many products to support?" Says Rohit Khanna, Chief Customer Officer, Smarsh. "How do we harness our internal knowledge and present it to these customers in a way that makes our teams more efficient and customer service more effective?"
In practice, this meant building an intelligent, human-centric “front door” trained on Smersh’s proprietary knowledge. The system centralizes the support journey, turning complex AI infrastructure into a simple, practical experience. Customers bypass complex navigation trees and explain what they need in simple language, and AI directs them to the right solution – reducing the friction of traditional self-service.
Archie, Smarsh AI Support Agent
Smarsh names its AI support agent "Archie." While many AI initiatives stall during the last mile – the difficult transition from a successful pilot to a sustainable, production-scale operation – Smersh avoided this by building on a deeply integrated platform. The company chose Salesforce’s AgentForce 360 platform to ensure Archie had the shared context, controlled execution, and orchestration needed for an agentic enterprise.
By deploying AgentForce rather than a typical DIY solution, Smarsh ensures that Archie can plan and execute work in the system for better self-service and faster resolution. This approach allows Smarsh to automatically move work forward across data and workflows, achieving greater efficiency without compromising the strict compliance rigor required by their industry.
As a result, the company expects to see a 20% increase in its customer self-service success rates, 25% faster problem resolution compared to traditional self-service search and browse methods, and a 30% increase in service representative productivity.
The cutting edge of customer service AI
Both generative and agentic AI are rewriting the customer service playbook, yet the lack of technology can create intimidating barriers. An organization can reap big rewards by moving forward decisively when launching an AI initiative, says Khanna, but it still requires care, foresight, and the right partnerships. Part of this is careful vendor selection.
"We’re a Salesforce shop,” he shared. “We use a core set of Salesforce products, including Data 360, AgentForce Service, AgentForce Sales, and more, so it would be wise to focus on the AI agent provided to us by Salesforce rather than buying something outside. We know it will be challenging in the beginning, as new technology comes in, but Salesforce is up to the task and we will grow together."
From day one, effective AI has demanded one non-negotiable condition: clean, secure data. Grounding generative AI in an organization’s verified corporate knowledge and internal data reduces the risk of hallucinations while providing a better user experience. However, Smersh didn’t wait for the industry to catch up. The company anticipated this need nearly half a decade ago, spending years carefully rationalizing, interpreting, and anonymizing its data to prepare for this precise moment.
"Many people face challenges and do not complete their AI projects because the data is not ready and it is not there," Khanna says. "We started strong, right out of the gate because our data was already cleaned and locked, and today we are in production with a service agent."
Prioritizing Data Trust
Given Smarsh’s focus on regulatory compliance, Archie was introduced to replace the company’s previous self-service customer support chatbot. Janine Deegan, Digital Support Program Manager at Smarsh, worked with the Salesforce admin team on Smarsh’s AgentForce deployment.
"With Archie, the goal was to move beyond experimentation and make AI actually usable in a regulated environment. It wasn’t as simple as turning to an agent; We had to build a system that would give that raw intelligence the context and control that our industry really needs, which is why we chose Salesforce,” says Deegan. “By connecting our document directly to AgentForce, which is backed by the Salesforce Trust Layer, we transformed our static data into a living, trusted resource that handles data with the accuracy required for a regulated space."
Given its seriousness, Khanna says maintaining pristine, secure documentation and data requires constant vigilance. To guarantee this, Smersh blurred the lines between departments, combining the documentation team with the AI team. Now both work in a tight loop: whatever content the document team creates, the AI team checks it, validates it and opens it for LLM.
AI and regulatory compliance
"We are in a compliance world. We are the custodians of all of our financial institutions’ archival data, and our data is so sacred that we do not give it away, " Khanna explains. "When we open our systems to agentive AI, we have to be very conscious of security and identity."
Infosec requirements were an important consideration for starting AgentForce. Smarsh is regularly audited not only by regulatory bodies but also by banks and financial institutions, who have to adhere to stringent data protection rules and ask for Model Risk Management, (MRM).
"Security regulators and banks demand MRM," Khanna says. "He says, ‘Let me tell you that all my data is not going to the public because it is being linked to LLM. Tell us about LLM? Tell me about the model you are using. We worked with Salesforce to get MRM approval for our customers. And thanks to Salesforce’s knowledge base and documentation, we are always able to explain to these regulatory bodies what Archie is responding to and why."
drive customer adoption
Customer buy-in is always a big challenge when it comes to new AI tools and Archie was no exception. Upon the initial rollout of the new interface, some customers were confused by the new text box in the center of their screen and did not immediately understand how to interact with it.
“We learned the hard way that we needed better change management, and to make sure our industry customers understood they could ask questions in natural language,” says Khanna.
Personalization, they soon realized, was the key to general AI adoption.
"Once customers had a better understanding of how Archie could be used for more efficient self-service, suddenly our adoption rate increased to 59%," He says. "Personalization was very important to us. We’re seeing momentum now, and we expect that to continue as we integrate Archie into the rest of our products."
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