AI Engineering
Generative AI, multi-LLM orchestration, structured output validation, RAG pipelines, fine-tuning, and systematic evaluation for dependable production workflows.
Aniket Thakur · AI × Product × Finance
I’m Aniket Thakur — an AI researcher and product builder working across Generative AI, machine learning, fintech, and data-driven products.
Focus & Expertise
Technical rigor combined with product ownership and financial context. Building systems where machine learning models drive measurable business decisions.
Generative AI, multi-LLM orchestration, structured output validation, RAG pipelines, fine-tuning, and systematic evaluation for dependable production workflows.
Leading end-to-end loan journeys in two-wheeler and vehicle marketplaces, integrating core banking APIs for KYC, disbursement, and repayment in the LMS, and managing HRX/HRMS operations.
Pursuing an M.Sc. in Financial Engineering at WorldQuant University. Applying quantitative analysis, risk mechanics, and algorithmic credit automation to real-world financial architectures.
Selected Work
Featured systems designed to automate workflows, solve data ambiguity, and deliver quantifiable operational outcomes.
An automated SEO pipeline that connects live search evidence directly to structured content generation, eliminating manual friction in content production.
Natural-language query engine over SQL databases enabling non-technical stakeholders to perform self-serve exploratory analysis and executive reporting.
Integrated LLM categorization and automated response routing into support desk operations to triage tickets by urgency and reduce resolution lag.
Multi-model orchestration framework utilizing structured output validation to deliver consistent, deterministic copy across multi-channel marketing campaigns.
A mobile-first EV charging discovery platform foundation with provider ingestion, data normalization, geospatial PostgreSQL/PostGIS storage, typed APIs, and India-first routing.
Track Record
Experience across high-growth fintech, international AI research, and early-stage startup advisory.
Own end-to-end loan journeys for a two-wheeler marketplace, align cross-functional stakeholders, and integrate core banking APIs for KYC, loan disbursement, and repayment in the Loan Management System (LMS). Managed HRX/HRMS operations and built LLM content-generation agents with structured output validation, optimizing latency and consistency.
Developed Graph Neural Network (GNN) algorithms to analyze complex ecological food webs and model energy-flow dynamics, boosting predictive accuracy. Engineered data pipelines using multi-LLM ensembles (Gemini, DeepSeek, Anthropic, OpenAI) to synthesize semantic representations from unstructured scientific literature.
Led AI implementation for a used-car finance system, deploying LLM automation to accelerate loan processing and automated credit decisions. Fine-tuned marketing LLM content agents, automating multi-channel asset creation across acquisition channels.
Facilitated go-to-market (GTM) launches for four early-stage startups across food, health, and fashion through market research and cross-functional execution. Delivered rigorous cost analysis and executive reports that reduced operational expenses by 15%.
Academic Research · OIST Japan
At the Okinawa Institute of Science and Technology (OIST), my research focused on computational modeling of complex ecological networks. Food webs describe intricate trophic dependencies and energy-flow dynamics across species communities.
By developing inductive Graph Neural Network algorithms (incorporating GraphSAGE and Graph Attention Networks), we modeled non-linear trophic interaction probabilities, capturing topological centrality and community structures that traditional pairwise models overlooked.
Alongside structural GNN modeling, I engineered semantic synthesis pipelines leveraging multi-LLM ensembles (Gemini, DeepSeek, Anthropic, and OpenAI) to standardize, cross-verify, and ingest ecological literature into structured topological datasets.
Academic Background
Mathematical, statistical, and quantitative groundwork in financial engineering and data analytics.
Advanced quantitative modeling, portfolio theory, derivative pricing, and algorithmic risk management.
Statistical computing, predictive modeling, econometrics, and database engineering.
From the blog
Technology, Product, Auto, and Finance.
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