Leaning into lean: Smarsh cuts support staff from 20 to 5 with Salesforce AI agents

Smarsh, a compliance and surveillance technology company serving over 6,200 customers including 18 of the top 20 global banks, has deployed Salesforce’s Agentforce platform to power AI agents for customer support. The deployment represents a strategic shift for the company, which specializes in creating AI agents for compliance monitoring but is now leveraging Salesforce’s expertise to enhance customer service operations while achieving significant efficiency gains.

What you should know: Smarsh has implemented multiple AI agents through Salesforce Agentforce to automate various customer service functions, starting with knowledge base creation and expanding to customer-facing support.

• The company replaced its traditional customer-facing chatbot with “Archie,” an Agentforce Service Agent featuring an animated avatar that handles customer inquiries on Smarsh Central.
• Archie automatically routes customers to live agents if it cannot adequately answer questions within three prompts, maintaining a human safety net for complex issues.
• The implementation began in Q1 2025 after board inquiries about AI efficiency, with use cases rolling out in Q2.

The big picture: While Smarsh has deep expertise in compliance-related AI agents that monitor electronic communications across platforms like WhatsApp, email, and LinkedIn for regulatory violations, the company chose to partner with Salesforce rather than build customer service agents in-house.

• Chief Customer Officer Rohit Khanna explained the decision: “Because Salesforce is our CRM and where our master data is, and because Salesforce provides us our ITSM through Service Cloud, it just made sense for us to go acquire agents from them.”

Key results: Smarsh has achieved measurable improvements in customer service metrics since implementing Agentforce agents.

• 20% increase in customer self-service success rates.
• 25% faster issue resolution compared to traditional self-service search methods.
• 30% increase in service representative productivity.
• The company reduced human oversight from 20 support representatives to just five for reviewing AI responses.

Strategic workforce transformation: Smarsh is using AI deployment to restructure rather than reduce its workforce, focusing on upskilling existing employees.

• Despite 30% company growth this year, Smarsh hired zero level one support representatives and doesn’t plan to hire any next year.
• By the end of next year, Khanna aims to eliminate all level one support roles across global centers in the Philippines, India, Belfast, Costa Rica, and the US, with AI agents handling those functions entirely.
• Existing level one staff are being trained to move into level two or three “business critical support” roles, with job titles changing from customer representatives to technical representatives or engineers.

What’s next: Smarsh is expanding its AI agent portfolio beyond the current three use cases of knowledge base creation, meeting summarization, and customer support.

• A fourth agent for billing is currently being rolled out, followed by an agent to help customers with user access control.
• “Everything will be replaced,” Khanna says. “All level one at my COEs… will be replaced by service agents, and level two and level three of business-critical support will be our manual support.”

What they’re saying: Khanna emphasizes that AI effectiveness depends on data quality rather than the technology itself.

• “I always tell my team, don’t blame the messenger, because the message is coming from your knowledge base. If our data is wrong or we have gaps in our knowledge base, you can’t blame the messenger. What we’ve seen is it’s not the tech that’s the problem, it’s the data.”