This AI Agent Just Replaced Dozens of Internal Tools for 2 Lakh Wipro Employees
Enterprises are slowly moving from AI proof of concepts (POCs) to products. Truthfully, however, most are still stuck at the ideation stage, which is a concerning situation. This hesitation largely stems from enterprises’ reluctance to input their data or deploy resources to build generative AI solutions, instead of focusing on core client deliverables. This is where generative AI platform providers like Salesforce, Snowflake, and others step in. Entering the space alongside them is Avaamo, with its LLaMB platform, designed to bring generative AI capabilities fit for the enterprise. The biggest example of the capabilities of Avaamo’s LLaMB is how it is powering employee experience automation at Wipro, one of India’s largest IT firms, helping streamline internal operations and improve policy compliance across the company’s workforce of over 2 lakh employees. While speaking with AIM, Sriram Chakravarthy, CTO and co-founder of Avaamo, said that the deployment, which includes over 50 automated workflows, is part of Avaamo’s larger push into the enterprise AI space with specialised agents designed for healthcare, customer service, and employee experience. While many companies brand their India operations as global capability centers (GCCs), Avaamo’s Bengaluru office serves as a core development centre, housing its foundational AI platform engineering team. “We are not a GCC in the traditional sense. Bengaluru is where our core developers sit, and it’s a central part of what we do,” Chakravarthy said. At the heart of Avaamo’s platform is an AI agent architecture tailored to meet the specific compliance, security, and workflow requirements of large enterprises. Apart from Wipro, the company’s clients include global names like Volkswagen, Franklin Templeton, Pepsi, Intel, and healthcare giants such as Mount Sinai and Johns Hopkins. “A lot of the AI being built today doesn’t work unless it solves what we call the first mile and last mile problems,” Chakravarthy explained. “The first mile is understanding natural, human-like input, like when a patient says, ‘I want to reschedule my appointment.’ The last mile is making sure the agent works exactly within enterprise constraints—data, compliance, workflow, everything.” Replacing Internal Apps with Conversational AI Wipro has deployed Avaamo’s AI agents to automate a broad range of employee-related tasks, including IT support, HR requests, procurement, and travel management—a major bottleneck for its consultant-heavy workforce. The system, integrated into Microsoft Teams under the internal tool WiNow, allows employees to interact with an AI agent to book travel within company policy constraints. Employees can input details such as origin, destination, and travel class, and the agent validates the request against Wipro’s extensive travel rules. “They had over 100 people manning their travel desk just to deal with these questions,” Chakravarthy said. “Now, employees just type ‘I need to fly from New York to San Francisco’ and the system checks if it complies with company policy. They can even upload their itinerary to see if it’s in compliance.” The agent significantly reduces employee wait time while improving policy adherence. Another example is late-night cab bookings—employees working late can request cabs through the same conversational interface, akin to an Uber-like system fully integrated with Wipro’s logistics. Chakravarthy further said, “Employees no longer need to learn different interfaces…It’s just chat. You ask, it acts.” Why Wipro Chose Avaamo Over Building In-House Given that Wipro builds generative AI solutions for clients, its decision to use an external platform raises questions. According to Chakravarthy, the answer lies in scale and specialisation. “Avaamo is a platform company. We’re not building point solutions; we’re solving this at an architectural level,” he said. “Wipro realised that their internal teams are better used for higher-value tasks, not reinventing something that already works at scale.” Avaamo’s platform combines proprietary models with open-source components, layered in what Chakravarthy calls an “ensemble model” pipeline. While the company uses LLMs from providers like Microsoft and OpenAI, it ensures that data and inference remain enterprise-grade. “You can’t answer a healthcare query by scraping public web data,” he emphasised. “If someone asks, ‘Who can do my knee surgery at Mount Sinai?’, that answer has to come from their data, not Google.” Avaamo customises its pipeline for each vertical—healthcare, employee experience, or customer service—ensuring domain-specific accuracy and regulatory compliance. Chakravarthy believes that AI agents are the future of enterprise automation—not just for improving user experience but for enforcing internal policies and reducing operational costs. “When a CIO rolls this out, they want to be sure the agent won’t hallucinate. That it works exactly as their process demands, no surprises,” he said. Interestingly, Wipro has had a longstanding relationship with Avaamo—not just as a customer but also as an early backer. Its venture capital arm, Wipro Ventures, was an early institutional investor in Avaamo back in 2014. The co-founders of Avaamo, Ram Menon and Sriram Chakravarthy, bring decades of enterprise software experience to the table. Both were part of TIBCO’s leadership during its growth phase, with Chakravarthy leading engineering efforts during its acquisition by Vista Equity Partners in 2014.
At the heart of Avaamo’s platform is an AI agent architecture tailored to meet the specific compliance, security, and workflow requirements of large enterprises.
At the heart of Avaamo’s platform is an AI agent tailored to meet the specific compliance, security, and workflow requirements of enterprises.
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Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.