Office located in Cambridge, MA
Generative AI for tabular data
Open for applications
Generative AI for tabular data
101-200 employees
Open for applications
Office located in Cambridge, MA
101-200 employees
Ikigai's on a mission to bring AI to everyone.
Desirable
Business is increasingly data-driven, but the sheer amount of data companies now handle poses major challenges in organizing, analyzing, and making use of that information. Ikigai Labs aims to make data accessible, providing a no-code platform which uses AI to connect disparate data sources and organizes and optimizes the information for scenario planning, forecasting and use in enterprise applications.
Ikigai isn’t the only company using AI to make sense of data, but it stands out with its graphical modelling approach as opposed to the prevailing large language models used by competitors such as Hugging Face and Daitaku. Graphical modelling is well suited to mapping out relationships using enterprise data (which is usually tabular) and is far less expensive to operate than large language models. These advantages have led to Ikigai’s platform being used by thousands of data teams from major companies such as IBM, Honeywell, and FedEx to name just a few.
With substantial funding to its name, Ikigai is ready to further develop its product and scale its team. While it faces intense competition, its focus on enterprise data needs seems likely to help it stand out from the pack and will stand it in good stead over the coming years.
Freddie
Company Specialist at Welcome to the Jungle
Few candidates hear
back within 2 weeks
Aug 2023
$25m
SERIES A
Dec 2021
$13m
SEED
Civic Center, San Francisco, CA
Vinayak Ramesh
(Co-Founder & CCO)Initially the CEO of Ikigai before moving to the role of CCO in 2024. Previously co-founded and was CTO of Wellframe. Holds a Master's of Engineering from MIT.
Devavrat Sha
(Co-Founder & CEO)Initially the CTo of Ikigai before moving to the role of CEO in 2023. Previously co-founder and Chief Scientist of Celect. PhD in Computer Science and Post Doc from Stanford University.
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