SB

Sarthak Biswas

Tech Investor@Chiratae Ventures | ex Kae Capital | IIT Bombay

Bengaluru, Karnataka

Invests in

Stages:

Locations:

  • Min Investment:

    $500,000.00
  • Max Investment:

    $1,500,000.00
  • Target Investment:

    $800,000.00

Education

Work Experience

  • Investment Professional

    2023

    Board Observer - Artium Academy (Consumer Tech) BeepKart (Consumer Tech) Cavli (IoT SaaS) HouseEazy (PropTech/Consumer Tech) KBCols (CleanTech) Non Observer support on LensKart

2020 - 2023

  • Investment Professional

    2020 - 2023

    Worked with cos like Bold Finance, Traya, Hypernova Interactive, Helix Health (ex Lodestone), etc. and assisted (and sourced) Contlo/SuperAGI. Worked on deals across Fintech, B2B Commerce, Consumer, etc. Sourced SuperAGI, Bold Finance, Lodestone, Eight Network. Received two raises and a promotion. Reported to Navin Honagudi, Gaurav Chaturvedi, Sunitha Viswanathan, Krishna Vinjamuri and Sasha Mirchandani - all for different tasks

  • Venture Capital Investment Professional

    2019 - 2020

    Screened/Evaluated early and growth stage companies for debt and equity - SaaS, Edtech, Consumer Tech Reported to Madhav Soi(Yuj) , Kedar Kalbag (Xander Fin) Yuj Ventures | Xander Finance

2018 - 2019

  • Experiential Learning Module

    2018 - 2019

    Early Stage Social Impact Ventures - worked part time during my PG at Ashoka University Reported to ~ Abhas Mrig

  • Investment Professional

    2017 - 2018

    Worked with multiple small funds, syndicates and founders in the early days - slogged/hustled through my initial days in the investing space - from deal evaluation, portfolio support, etc.

  • Founder

    2015 - 2017

    We built and sold AI/ML solutions targeted towards SMBs focusing on inventory and demand forecasting

  • Summer Business Analyst

    2016 - 2016

    Growth strategy in Subscription and Online Ad (AI based optimization) business Reported to ~ Kunal Mukherjee, Siddharth Shanbhag

  • Research Intern

    2015 - 2016

    Finance and Machine Learning