Topics
in style
AI
Amazon
Image Credits:Getty Images
Apps
Biotech & Health
clime
Image Credits:Getty Images
Cloud Computing
Commerce
Crypto
Enterprise
EVs
Fintech
fund-raise
Gadgets
Gaming
Government & Policy
Hardware
Layoffs
Media & Entertainment
Meta
Microsoft
Privacy
Robotics
Security
societal
distance
inauguration
TikTok
Transportation
Venture
More from TechCrunch
event
Startup Battlefield
StrictlyVC
newssheet
Podcasts
picture
Partner Content
TechCrunch Brand Studio
Crunchboard
Contact Us
Generative AI well and truly has a grip on public technology treatment these day . A new startup calledEmaout of San Francisco thinks it ’s a lot more than just a passing fancy . It ’s emerging from stealth today , with a product of the same name that it believe will open a newfangled chapter in how AI , and specifically reproductive AI , will transfer how we work .
“ Our destination is to build a universal AI employee , ” Surojit Chatterjee , the CEO and atomic number 27 - founder , said in an interview . “ Our end is to automatize on the workaday tasks that employee do on a solar day to day base in every enterprisingness … to free them up to do more valuable and more strategical work . ”
The society , and investors , are putting money and revenues where its mouth is : It ’s already raised $ 25 million from an telling inclination of angel , along with customers that it quietly amass while still in stealing , to blow away any accusations of vaporware , including Envoy Global , TrueLayer and Moneyview .
As for what Ema can do , these businesses are using it in applications that rove from client service — including propose technological support to users as well as tracking and other function — through to internal productivity applications for employee . Ema ’s two products — Generative Workflow Engine ( GWE ) and EmaFusion — are design to “ emulate human responses ” but also evolve with more usage with feedback .
As Chatterjee describe it , it ’s not just robotlike process automation ( that is so 2010 ’s ) and it ’s not just AI to accelerate certain tasks ( that ’s start back even further ) , and it ’s not just another GenAI accuracy fail hold off to belampoonedon social sensitive .
Chatterjee says that Ema — which is an acronym for “ enterprisingness machine supporter ” — taps into more than 30 large speech poser , he said , and combines that with its own “ smaller , domain specific models ” in a patent of invention - pending platform “ to direct all the issues you have seen with truth , hallucination , data auspices and so on . ”
This other beat is adding a band of names to Ema ’s cap table . Accel , part 32 and Prosus Ventures are co - prima , and Wipro Ventures , Venture Highway , AME Cloud Ventures , Frontier Ventures , Maum Group and Firebolt Ventures are also enter . On top of this there are also some big - name single backers : Sheryl Sandberg , Dustin Moskovitz , Jerry Yang , Divesh Makan and David Baszucki among them .
Join us at TechCrunch Sessions: AI
Exhibit at TechCrunch Sessions: AI
There are already dozens , peradventure one C , of companies building GenAI instrument for enterprise at the moment , both those working on solutions for special verticals or use cases , as well as ambitious household - run style swing like Ema ’s . If you ’re wondering why this special GenAI startup is beguile attention from these investor , some of that might be because of the fact that they ’re already get up up business . But it ’s also because of some of the backdrop of the squad .
Previous to Ema , Chatterjee was chief product officer of Coinbase lead up to its initial public offering . Before that , he was VP of Product at Google in both its nomadic ads and shopping businesses . He has some 40 patent to his name in country like auto learning enterprise software and adtech .
The other co - founder , Souvik Sen , who is Ema ’s head word of engineering , has some equally telling experience . Most late , he was VP of engineering at Okta where he oversaw information , machine learnedness and gadget ; and prior to that he was at Google , where he was organize star for data and political machine learning where he center on privacy and safe . He himself has 37 patents .
The combined experience of these two both gives a free weight to the company ’s ambitions and likeliness of being able to fulfil on them . But it also drop lots of detail that may well estimate in how it acquire .
For example , consider Chatterjee ’s expertise in einsteinium - commerce and adtech . Given that these are such cornerstone of how so many businesses interact with customers today , it feels inevitable that they will calculate in how Ema might evolve if it fly .
On the other hand , having a founding father who has antecedently had to build in and answer for for data aegis and privacy potentially give way the startup a unspoiled chance of not make a mess of these . Or at least we can hope ! It is AI after all , and this is a Silicon Valley startup that will ultimately be focus on business at paw and how to use technology to achieve it .
For the moment , it ’s notable to see challenging startups working to establish products that trim down across different LLM silos to achieve more advanced solvent . It is perhaps an early sign of how the LLMs are more interchangeable than you might usurp over time , and more commoditized , too .
And the ability to issue across different enjoyment cases give the startup a potential diversification that could help oneself mature its business and utility overall , investors say .
“ Most point GenAI solutions provide high value for specific use of goods and services suit but are either operose to thrive across use suit or even side by side enjoyment - cases and more significantly , orotund enterprises are worried about fragmentation and access to their sensitive data by so many different applications , ” Ashutosh Sharma , oral sex of investments for Prosus Ventures in India , told TechCrunch . “ Ema can solve for these problem and deliver gamy accuracy with optimum return on investment funds . ”
