Skip to main content
MIT Corporate Relations
MIT Corporate Relations
Search
×
Events
STEX25
Startups
opportunities
MIT ILP
Sign-In
Register Your Startup
Search
Search
×
STEX Home
Events
Corporates
Event Videos
Startups
STEX25
Featured
Videos
Startups
Search
News
opportunities
MIT ILP
User Menu and Search
Sign-In
Register Your Startup
Search
STEX Home
Toggle menu
Search
Sign-in
Register your startup
Events
Corporates
Event Videos
Startups
STEX25
Featured
Videos
Startups
Search
News
opportunities
MIT ILP
Back to search results
Akkio
STEX25
Active dates:
January 20, 2023 - January 20, 2023
STEX25
View Feature
STEX25 Participation:
January 20, 2023 - December 31, 2024
Company information
Contact
1000 Massachusetts Ave, Suite 1B
Cambridge
,
MA
02138
United States
https://www.akkio.com/
https://www.facebook.com/AkkioHQ/
https://www.linkedin.com/company/akkio/
Empty YouTube link
https://twitter.com/AkkioHQ
Keywords
Computer Software
,
Artificial Intelligence
,
machine learning
,
SaaS
Elevator Pitch
Elevator Pitch
Start using your data to predict the future. Akkio makes it incredibly easy to build and deploy machine learning predictive models. Optimize your sales pipeline, reduce churn, forecast demand, and more -- easier and faster than ever before.
Description
Description
Akkio lets data analysts and data-savvy operators get quick wins and pull ahead by rapidly building machine learning into every corner of your product and operations. Power your app or build internal tools 10x faster at a fraction of the cost. This is AutoML purpose-built for operators and engineers, not data scientists.
Technology Description
Technology Description
Akkio opens access to powerful, deep learning ML technologies once only usable by AI experts at the largest companies. Akkio is...
Easy to Use
Akkio equips anyone who understands data with a prediction machine and data science support, so you can focus on serving up more actionable insights, tools, and solutions.
Fast
Solve problems you never thought you’d get to. Train and iterate in minutes instead of hours. Ship ML-enabled workflows and features in days instead of months.
High Performance
No need to tradeoff performance for speed. Beat the major ML players’ performance in a fraction of the time.