---
title: "Pradeep Patil - Co-founder & CTO in Bengaluru | Tal"
description: "Meet Pradeep Patil, Co-founder & CTO @ Prodloop | Data & AI Engineering Leader | Agentic AI, LLM Evaluation, Voice AI | 13+ yrs in Data Architecture, MLOps & Multi-cloud | Ex-Accenture Applied AI Hub, BRIDGEi2i based in Bengaluru. AI stack includes antigravity, claude, and langgraph."
image: "https://tal.club/meet/pradeep-patil/share-image"
---

# Pradeep Patil on Tal

## Headline

Co\-founder & CTO @ Prodloop \| Data & AI Engineering Leader \| Agentic AI, LLM Evaluation, Voice AI \| 13\+ yrs in Data Architecture, MLOps & Multi\-cloud \| Ex\-Accenture Applied AI Hub, BRIDGEi2i

## About

Production AI on a strong data foundation: 13\+ years across data engineering, cloud architecture, MLOps, pre\-sales and applied AI, now building generative, agentic and voice AI\. As Co\-founder & CTO of Prodloop, I've grown a bootstrapped voice AI quality and observability SaaS with \~90% retention, serving 15\+ enterprises across mobility, logistics, edtech and e\-commerce\. Built at Prodloop → Multi\-tenant audit platform: customers review call and bot audits, reports and agent performance, and accept or dispute each parameter as human\-in\-the\-loop feedback → LLM\-as\-judge evals at 95% accuracy vs human review across 13\+ Indian languages and 10M\+ calls; batch\-first design cut inference cost 50% → Self\-serve onboarding agent: customers upload calls, set rubrics and iterate on audits in chat, then hand off for integration with zero Prodloop effort → prod\.ai: natural\-language Q&A over calls on Vertex AI Search \("which agents were rude last week?", "who asked for a discount above INR 5,000?"\), grounded in the calls → Voice agent orchestrator across STT, TTS, LLM and telephony with VAD and latency tuning, live with customers; pre\-fetches CRM and WhatsApp context for a customer 360 view → Self\-hosted multiple STT models and engineered open TTS models such as Kokoro for Indian languages on AWS GPUs, avoiding closed providers' per\-token and concurrency fees → Built a TTS cache that reuses generated speech instead of regenerating it, cutting generation cost Data engineering & cloud → Pipelines from telephony, CRMs and internal systems into BigQuery with tenant isolation, PII masking and India data residency → Led end\-to\-end data engineering for multiple enterprise clients, heading delivery teams and partnering with client cloud and solution architects on data lakes, lakehouses, warehouses and MDM across GCP, Azure and AWS → Streaming pipelines, real\-time microservices at sub\-300ms, data quality engines, audit and balance controls, and MLOps with drift detection Pre\-sales & go\-to\-market → RFPs, solutioning and reusable accelerators \(data quality, MLOps\) at BRIDGEi2i, so projects start from proven frameworks, cutting time to value and driving upsell → Founder\-led sales at Prodloop, renewals at higher prices; event booths that won customers; active in AI meetups I rose from Data Modeler to Director, Technology Labs at BRIDGEi2i, then ML Engineering Senior Manager at Accenture AI Hub post\-acquisition, leading teams of 8–10\. Part of NSRCEL \(IIM Bangalore\) and NASSCOM GenAI Foundry; I write here on evaluation, agent design, MCP and inference economics\.

## Location

Bengaluru

## AI stack

antigravity

claude

langgraph

langsmith

hermesagent

huggingface

## Work experience

Co\-founder & CTO at Prodloop, Jun 2024 \- Present · 2 yrs 4 mos, Prodloop is an agentic AI platform for voice operations: quality, evals and self\-improvement for voice bots and human agents\. Bootstrapped, with \~90% retention and 15\+ enterprise customers across mobility, logistics, edtech and e\-commerce\. Platform \- Architected the multi\-tenant platform: pipelines pull calls and metadata from telephony, CRMs and internal systems, run multi\-hop processing across closed and open\-source LLMs, validate against systems of record, and write results to customer CRMs, clouds or our audit portal \- Audit portal where customers review bot and human audits, reports and agent performance, and accept or dispute each parameter; disputes feed a learning loop for our models and evals \- LLM\-as\-judge evals at 95%\+ accuracy vs human review across 22 Indian languages and code\-switching, 10M\+ conversations Agents \- prodQA: voice\-to\-insight scoring of quality and compliance, including prosody \(empathy, rate of speech, tonality\) \- Simulation agent built on 10K\+ hours of Indian conversational data \(LLM and voice simulations\) \- Funnel agent \(where and why conversions drop\), A/B testing agent \(humans vs bots\) and custom SOP agents for company\-specific checks \- Self\-serve onboarding agent: customers upload calls, set rubrics and iterate on audits in chat before integration, no Prodloop team needed \- prod\.ai: natural\-language Q&A over call data on Vertex AI Search, grounded in the calls Voice AI \- Voice agent orchestrator across STT, TTS, LLM and telephony with VAD and latency tuning, live in production; pre\-fetches CRM and WhatsApp context for a customer 360 view \- Self\-hosted STT and Kokoro TTS for Indian languages on AWS A10G GPUs \(419ms median TTFB at 30 streams\), plus a TTS cache \- Cut inference cost 50% with batch\-first, serverless design Outcomes \- 25% fewer overcharging drivers \(ride\-hailing\), 20% lower support cost and 8% higher CSAT \(logistics\), 12% incremental revenue \(edtech\), 20% higher assisted\-buying conversion \(e\-commerce\)

Founder & CTO at LEGOAI Technologies, Apr 2023 \- Apr 2024 · 1 yr 1 mo, Bengaluru, Natural language analytics over enterprise data: business users ask questions in plain English and get answers from their own databases\. \- Built a deterministic relationship\-discovery algorithm that connects to customer databases, infers which tables join on which columns, and returns a coverage\-based confidence score \- Built the natural language layer on top: a RAG pipeline \(chunking, embeddings, retrieval\) with on\-the\-fly SQL generation and an evaluation loop for answer precision \- Self\-hosted Falcon, Llama and Mistral on 8× NVIDIA A100 80GB \(Azure NDm A100 v4\) in 2023, exposed as a SQL\-generation endpoint, because enterprise customers would not let even schema metadata leave their environment \- Owned product, architecture and customer conversations end to end as founder

Accenture S&C \(AI Hub\) \- ML Engineering \- VP/Senior Manager \(Bridgei2i Acquisition\) at Accenture AI, May 2022 \- Apr 2023 · 1 yr, Bengaluru, Joined Accenture Strategy & Consulting's AI Hub through Accenture's acquisition of BRIDGEi2i\. \- Led ML engineering delivery across enterprise client accounts, owning solution architecture and technical delivery \- Built trust with client stakeholder teams and project sponsors on the accounts I led, turning delivery credibility into upsell and expanded scope \- Handled RFP responses and solutioning for AI, ML and data engineering opportunities, presenting to prospective clients \- Presented the accelerators built at BRIDGEi2i \(data quality framework, MLOps platform\) to show faster time to value, with projects starting from proven frameworks instead of from zero \- Carried those accelerators into AI Hub engagements as reusable building blocks for client delivery \- Led and mentored ML and data engineering teams across cloud platforms

Director \- Technology Labs at BRIDGEi2i Analytics Solutions, Apr 2022 \- Apr 2022 · 1 mo, Bengaluru, Promoted to Director, Technology Labs in April 2022, a month before BRIDGEi2i's acquisition by Accenture; the role mapped to Senior Manager at Accenture\. Technology Labs was BRIDGEi2i's group for reusable accelerators and pre\-sales solutioning\. \- Worked on RFP responses and solution design, presenting our accelerators to prospective clients as technical differentiators \- The accelerators \(data quality framework, MLOps platform\) let client projects start from proven frameworks instead of from zero, cutting time to value and contributing to won deals and upsell \- Senior technology architect and consultant across multiple client engagements

Cloud Architect at BRIDGEi2i Analytics Solutions, Oct 2020 \- Mar 2022 · 1 yr 6 mos, Bengaluru, \- HPE: architected an API and data mesh over a Hortonworks/Cloudera estate, with multi\-layer caching holding sub\-300ms response times for HPE's customer\-facing web portal\. The architecture my team built was awarded at HPE Discover in the US, presented there by HPE's own team \- Worked directly with HPE's CDO office as sole client\-facing owner, leading a team of 15\+; the trust built with stakeholders and the project sponsor led to upsell, more revenue for BRIDGEi2i and a larger team on the account \- Clorox \(Azure\): technical architect leading the team on an end\-to\-end data transformation platform, a metadata\-driven lakehouse on Azure Data Factory, Databricks, ADLS, Synapse, Azure DevOps and Power BI \- Cholamandalam: delivered a similar end\-to\-end Azure data lake and warehouse for the financial services group \- Senior technology architect across multiple other client engagements

Technical Lead \- Data Engineering & MLOps at BRIDGEi2i Analytics Solutions, Mar 2019 \- Oct 2020 · 1 yr 8 mos, Bengaluru, \- Clorox \(US\): led a greenfield marketing analytics platform end to end for Clorox's marketing team, working from Bangalore\. Ingested 40\+ marketing sources, including YouTube, Google campaign analytics, Google Maps, Instagram and Facebook, computed clicks, impressions and campaign KPIs, and fed Power BI dashboards used by the marketing head and team \- Built it fully serverless on GCP \(Cloud Scheduler, Pub/Sub, Cloud Storage, Cloud Functions, BigQuery\) at a time when most projects still ran on servers \- Learned GCP from scratch on this project and earned the Google Cloud Professional Data Engineer certification along the way \- Built reusable data quality and MLOps accelerators, later used across client projects and in pre\-sales

Data Modeler at BRIDGEi2i Analytics Solutions, Mar 2018 \- Mar 2019 · 1 y, Bengaluru, Joined the team building BRIDGEi2i's two products, BridgePersona and BridgeFunnel\. Designed the data model for both products Led the 8\-person data engineering team behind them, taking the work from requirements through technology benchmarking to delivery \(Python/FastAPI, Postgres, Neo4j, AWS\)

Senior Software Engineer at Wipro Limited, Dec 2017 \- Mar 2018 · 4 mos, Bengaluru Area, India, \- Senior data modeller for State Street, a global financial services client, owning data model design and specifications on the engagement

Software Analyst at Accenture, Aug 2015 \- Oct 2017 · 2 y 2 mo, Bengaluru, Nordea Bank engagement, based in Bengaluru with on\-site work in Denmark\. Data modeller and architect on a customer master data management programme that unified disconnected banking systems across Sweden, Finland, Norway and Denmark into a single customer 360 view Implemented the IBM MDM solution from scratch, acting as MDM product consultant across the end\-to\-end solution Owned the data model, the architecture and the specifications handed to the ETL team Monitored DataStage jobs pulling from country\-specific mainframe sources into IBM MDM on DB2 Strong in OLTP and OLAP data modelling, SQL, data profiling and data quality

Senior Systems Engineer at IGATE, Apr 2013 \- Aug 2015 · 2 y 4 mo, Mumbai, Data modeller for MetLife \(US\), designing OLTP and OLAP data models in ERwin Worked across data modelling, DataStage ETL and PL/SQL development ETL developer for Sydney Trains \(Australian government\), building DataStage jobs from multiple source systems into the reporting database, with Cognos reporting on top PL/SQL development for data warehouse workloads

## Education

Bachelor of Technology \- BTech, Computer Science and Engineering, Maharashtra Institute of Technology Aurangabad

[View the original profile](https://tal.club/meet/pradeep-patil)

```json
{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Person",
      "@id": "https://tal.club/meet/pradeep-patil#person",
      "name": "Pradeep Patil",
      "url": "https://tal.club/meet/pradeep-patil",
      "image": "https://tal.club/meet/pradeep-patil/profile-photo.jpg",
      "description": "Meet Pradeep Patil, Co-founder & CTO @ Prodloop | Data & AI Engineering Leader | Agentic AI, LLM Evaluation, Voice AI | 13+ yrs in Data Architecture, MLOps & Multi-cloud | Ex-Accenture Applied AI Hub, BRIDGEi2i based in Bengaluru. AI stack includes antigravity, claude, and langgraph.",
      "jobTitle": "Co-founder & CTO",
      "worksFor": {
        "@type": "Organization",
        "name": "Prodloop"
      },
      "hasOccupation": {
        "@type": "Occupation",
        "name": "Co-founder & CTO"
      },
      "homeLocation": {
        "@type": "Place",
        "name": "Bengaluru"
      },
      "alumniOf": [
        {
          "@type": "EducationalOrganization",
          "name": "Maharashtra Institute of Technology Aurangabad"
        }
      ],
      "knowsAbout": [
        "antigravity",
        "claude",
        "langgraph",
        "langsmith",
        "hermesagent",
        "huggingface"
      ],
      "mainEntityOfPage": {
        "@id": "https://tal.club/meet/pradeep-patil#webpage"
      }
    },
    {
      "@type": "ProfilePage",
      "@id": "https://tal.club/meet/pradeep-patil#webpage",
      "url": "https://tal.club/meet/pradeep-patil",
      "name": "Pradeep Patil on Tal",
      "description": "Meet Pradeep Patil, Co-founder & CTO @ Prodloop | Data & AI Engineering Leader | Agentic AI, LLM Evaluation, Voice AI | 13+ yrs in Data Architecture, MLOps & Multi-cloud | Ex-Accenture Applied AI Hub, BRIDGEi2i based in Bengaluru. AI stack includes antigravity, claude, and langgraph.",
      "dateModified": "2026-09-25T20:49:08.328Z",
      "isPartOf": {
        "@id": "https://tal.club/#website"
      },
      "mainEntity": {
        "@id": "https://tal.club/meet/pradeep-patil#person"
      },
      "primaryImageOfPage": {
        "@type": "ImageObject",
        "url": "https://tal.club/meet/pradeep-patil/profile-photo.jpg",
        "contentUrl": "https://tal.club/meet/pradeep-patil/profile-photo.jpg",
        "caption": "Pradeep Patil profile photo on Tal"
      },
      "inLanguage": "en-IN"
    }
  ]
}
```