Applied AI Summit
Free online conference | October 14-16, 2025Agentic AI: Autonomous Decision Making
With the rapid advancement in the fields of artificial intelligence and natural language processing, including large language models and Agentic AI systems, every industry is striving to leverage these technologies to automate its processes and decision-making capabilities. One of the complexities related to the adoption of technological advancements is the need for it to adhere to ever-evolving compliance procedures. Traditional approaches to managing compliance changes are proving inadequate; they are typically reactive, prone to human error, and resource-intensive. Any delay in adhering to compliance procedures can have significant financial consequences.
We propose a design for an Agentic AI-driven solution to fundamentally transform continuous monitoring and compliance within highly dynamic industries, such as the Financial Services Industry. We propose an orchestrated group of intelligent AI agents, each utilizing an LLM to specialize in distinct tasks. Using Natural language understanding to interpret unstructured text data, monitoring real-time operational information, and identifying potential non-compliance or emerging risks are among the high-level functions that AI agents are expected to perform. The AI agents can autonomously process new regulations, internal policies, and historical compliance data, enabling proactive identification of deviations to generate actionable insights. These actionable insights are meant to reduce manual effort, enhance compliance accuracy, and provide a scalable solution for continuous monitoring and policy adherence.
About the speaker
Kalpan Dharamshi
Senior IEEE Member
A seasoned IT professional with over 20 years of experience, Kalpan Dharamshi brings a wealth of knowledge across diverse domains including Cloud Architecture and, most notably, Machine Learning. His extensive tenure within the FinTech industry has been marked by significant contributions in leveraging machine learning to drive key business results. Recognized by peers and senior leadership as a highly competent Machine Learning Engineer, Kalpan has consistently demonstrated his ability to translate complex data into impactful solutions. Driven by a passion for continuous learning and excellence, Kalpan recently earned a Master’s degree specializing in Machine Learning from Georgia Tech University, further deepening his expertise in the field. This academic pursuit complements his practical experience, allowing him to stay at the forefront of advancements in AI and ML. Beyond his professional role, Kalpan is an active contributor to the AI and ML community. He regularly shares his insights through articles on emerging trends, as evidenced by his publications on platforms like DZone, covering topics such as Explainable AI for fraud detection and text clustering with DeepSeek reasoning. Kalpan is also an engaged member of the data science and machine learning community, actively participating in and speaking at various industry conferences. His commitment to sharing knowledge and engaging with the latest developments underscores his leadership and expertise in the field. He is eager to connect with fellow professionals and explore opportunities to further advance the application of Machine Learning in innovative and impactful ways. Invited Speaker at multiple fintech conferences in NY. https://mlconference.ai/speaker/kalpan-dharamshi/ Past Speaker recording. https://www.youtube.com/watch?v=Db7Gb9G-Qus