Naresh Silla
Flat stepping stones crossing the pond, with koi swimming between them.

Track record

I work where product, AI, and data systems meet: LLM copilots, RAG pipelines, CRM platforms, and real-time event products.
From the pond on the homepage, where each job is a stepping stone

My strongest work turns technical possibility into product shape: the workflow, the trust model, the moment a user decides, the metrics, and the story that helps a team build the right thing.

  1. JPMorgan Chase

    Product Manager, True Modernization · Feb 2026 - Present

    • Designing and collaborating with cross-functional teams to modernize legacy but critical fintech servicing journeys, including card design changes and card replacement flows.
    • Helping specialists support end customers faster and more effectively by simplifying operational workflows and reducing friction in high-volume journeys.
    • Targeting a 40% efficiency gain in average handle time and a 25% increase in customer NPS as the modernization program matures.

  2. Capillary Technologies

    Product Manager, AI Products & Platform · 2023 - 2026

    • Launched Milestones & Streaks gamification from 0-to-1, contributing to $30M incremental revenue and an 18% engagement lift across enterprise brands.
    • Shipped AiRA Copilot, an LLM interface that compressed promotion setup from roughly 20 minutes to under 1 minute and saved 400+ hours monthly.
    • Built a RAG documentation assistant handling 5,000-6,000 Slack queries per month, cutting knowledge retrieval from hours to seconds.
    • Led Connect+, a self-service data integration platform moving 10M+ records/day to Adobe, Braze, and Salesforce.

  3. Accenture AI

    Data Science Practitioner · 2021 - 2023

    • Built an ML-based run-time estimator that saved 1,200+ hours annually across enterprise migration teams.
    • Designed scheduling and sampling workflows for large-scale data transformation pipelines.

  4. Curl Analytics

    Data Scientist · 2019 - 2021

    • Delivered supply-chain lead-time estimation with 0.3-day RMSE across 100,000+ customers and 16 ERP systems.
    • Built time-series forecasting models for market trend prediction across global markets.