Learn how GreyLabs AI is enhancing customer interactions in the BFSI sector with intelligent, personalized solutions that improve engagement and streamline services. The Catalyst connected with Harshita Srivastava, Co-Founder and CTPO of GreyLabs AI, to find out how their AI-driven tech solutions are shaping the future of customer interactions for the BFSI sector. From AI-driven insights to tailored solutions, speech and text- analysis, GreyLabs is at the forefront of transforming the way financial institutions interact with their customers.
Please provide a brief overview of GreyLabs AI and its mission in AI-driven customer interaction.
At GreyLabs AI, we have built a Speech Analytics solution that delivers incredibly accurate speech-to-text for call centers. Our goal is simple: to bridge the critical gap in call center Quality Analysis. Currently, only a small fraction of calls are being audited by enterprises, leaving significant gaps in understanding customer interactions. Moreover, these audited calls may or may not provide valuable insights, leading to missed opportunities.
This often results in revenue leakage, subpar service delivery, and missed follow-ups, such as when a customer requests a call back, but the agent fails to act. We bridge these gaps by providing comprehensive insights from all calls, ensuring better agent performance, improved customer experience, and a significant reduction in operational inefficiencies—all powered by Generative AI.
How does AI play a role in transforming Banking and Finance businesses interact with their customers?
AI is changing the game for BFSI businesses by making customer interactions smarter and more personalized. It breaks down language barriers with multi-lingual capabilities, helps predict customer behaviour, and uncovers trends. For example, it can analyze customer sentiment or identify patterns in collections and sales calls, enabling businesses to proactively solve problems and build better relationships.
What technologies or AI models power GreyLabs AI’s capabilities in speech and text analytics?
We have trained our own Large Language Model (LLM) on top of open source LLMs. If you use the widely available paid and open source LLMs, they hallucinate a lot, meaning, they generate inaccurate responses. We’ve trained our LLMs on BFSI specific data to create India’s first BFSI-LLM which is highly accurate. Our solution is at least 15 – 20% more accurate than the other solutions in the market. This helps accurately analyze every single interaction between a customer and a tele caller of a Financial Institution.
What are some of the most significant challenges you have faced when implementing AI-driven customer engagement solutions in the BFSI sector?
One of the biggest challenges has been integrating with legacy systems in BFSI organizations, and of course, there’s always the need to address concerns around data security and compliance. Convincing stakeholders to trust AI over traditional methods has also required a thoughtful and transparent approach.
How do you ensure that the AI solutions you provide are scalable and adaptable to the evolving needs of BFSI clients?
Our solutions are built with scalability in mind—using modular designs and cloud-native technologies. This ensures they can grow alongside our clients’ needs. We’re a team of tech enthusiasts and young innovators, constantly upgrading our product week by week to adapt to changing requirements and deliver the best possible value to our clients.
For example, for one of our clients, we introduced a feature called ‘Ask Anything,’ which functions like an LLM for the contact center. It allows users to ask any open-ended question to our AI such as ‘Who are the top 5 competitors customers are talking about?’ or ‘Why are we losing customers?’, and the system responds with insights based on call data, accompanied by relevant recordings as examples. This adaptability and innovation ensure our solutions remain practical, impactful, and future-ready.
What types of customer interaction data do you focus on, and how do you collect it across various touch points?
At GreyLabs AI, we focus on customer interactions across all major functions in a BFSI company—Telesales, Customer Service, and Collections. Our core strength lies in analyzing call recordings, but we also work with emails, chats, and other communication channels to give a complete picture of how customers are engaging with the business. We collect this data through seamless integrations with systems like call center platforms, IVRs, and CRMs, making it easy to analyze interactions across multiple touchpoints.
How do you address privacy concerns and ensure compliance when handling sensitive customer data?
Privacy and security are at the core of what we do. All data is encrypted end-to-end, and sensitive information such as personal details and numbers are masked. We are ISO and SOC2 compliant, conduct regular audits, and use secure cloud infrastructure (AWS, Mumbai) to ensure that customer data is safe and within Indian boundaries.
What are some of the upcoming features and innovations GreyLabs AI will introduce?
We are working on analysing the customer communications across various channels (like calls, emails, etc) and building a customer profile based on that. Based on this data, our clients can get a better understanding of what their customers really want, and be able to serve them better.
With AI, it is a new era of customer interactions in the BFSI sector, offering intelligent and personalized solutions that drive engagement and efficiency. Financial institutions are looking forward to creating more meaningful connections with their customers while optimizing service delivery. The BFSI industry demands setting new standards in enhancing the customer experience and delivering better services.
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