I make AI
show its work.
LLM output that can be checked: every claim traced to its source, measured for grounding and unsupported statements, and logged so a reviewer or auditor can follow the reasoning. Built for regulated financial workflows, where a confident wrong answer is the expensive failure.
Founder & CTO of MantaSol, a BFSI tech-compliance company focused on the safe use of AI agents and LLMs in financial services. Before that: data engineering and ML across banking, insurance and edge systems — pipelines, streaming, and analytics at scale. I favour well-defined repeatable workflows over open-ended agents, because auditability depends on the path being specified rather than improvised.
End-to-end data systems built for scale; from real-time pipelines to ML-powered applications.
projects
A deep dive into e-commerce data using K-Means clustering to uncover the hidden relationship between delivery performance and customer retention.
data engineering
Building a scalable recommendation engine with Lambda Architecture, Kafka, Flink, and Airflow
software engineering
Building an opportunistic data offload system using ESP32 and Raspberry Pi Pico to extract diagnostic telemetry from trains on the 740km Konkan route where LTE is absent for hours at a time
Deep dives into algorithms, statistics, and ML theory; implemented from first principles.
Statistics
Building a complete experimentation framework — from hypothesis testing to Bayesian inference
ML
Understanding the mathematics of reducing high-dimensional data — from eigendecomposition to manifold learning
ML
Implementing core ML algorithms from first principles using only NumPy
Building data and AI systems across industries; from insurtech analytics to verifiable AI for regulated finance.
2021 - 2023
Siemens Ltd.
ETL • Python • Data Pipelines
Jul 2024 - Dec 2024
Habitat
Edge Inference • CI/CD
Jan 2025 - Sept 2025
RiskPe
PySpark • SQL • Power BI
Oct 2025 - Present
MantaSol
BFSI AI Compliance • RAG Evaluation