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Mark Hay and Ethan Ding want to make every collective conclusion a data - take one . Ambitious ? For sure . But the two applied scientist , who satisfy a few years ago during the pandemic , are nothing if not optimistic .
Hay and Ding are the co - founders ofTextQL , a political platform that connects a society ’s existing data stack to large speech models along the parentage of OpenAI ’s ChatGPT and GPT-4 . The idea , they say , is to give concern teams the ability to ask questions of their data point on - requirement , leveraging tooling that — in Hay ’s Word — “ understand their teams ’ ‘ noun ’ and semantics . ”
“ datum leaders have spent 15 years being sold a false hope … Half the Fortune 500 principal data point officeholder are hypersensitised to the word ‘ ego serve ’ at this point in time , ” Hay , TextQL ’s CTO , told TechCrunch in an e-mail audience . “ Their 400,000 data scientist are spend 40 % or more of their time pull out one - off data requests , and their business enterprise teams are using words that are represented other than in their databases , resulting in months of lost productivity arguing over numbers . ”
Hay , previously an engine driver on Facebook ’s car eruditeness team , and Ding , an ex-husband - fellow member of Bessemer Venture Partners ’ data squad ( and a rooter of gardening metaphors ) , cogitate they could get up a better answer .
In 2022 , they launch their endeavor in TextQL , which uses a data example to map a company ’s database to the “ noun ” representing a customer ’s business in their language — e.g. word of honor like “ order , ” “ item , ” “ dealer , ” “ SKU , ” “ inventorying ” and so on .
TextQL connects to line news shaft and points users to subsist splashboard when a question has already been enquire . It ’s able to cite documentation from enterprise data catalogs such as Alation , Hay says , as well as notes in political platform like Confluence or Google Drive .
Concretely , this enable TextQL users to ask question of a chatbot such as “ Can you show me a listing of orders that were very recent ? ” and “ reckon the dispersion centers with the highest concentration ? ” Beyond answering questions , TextQL — via an mechanization component — can take certain actions , for example sending an email to managers about specified information .
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“ In an economic environment where everyone ’s trying to do more with less , we ’re capable to give enterprise operators superpowers in one political platform , ” Hay tell .
Hay — which get word TextQL compete against marketer like Palantir and C3.ai — says that TextQL has half a 12 client across healthcare , bio and life sciences , fiscal services , fabrication and media shortly . one-year recurring revenue is in the “ six frame , ” he claims , give TextQL “ several years ” of runway .
“ The retardation has n’t affected us as much , if anything — troupe are activated about our software since it can avail them do more with their down in the mouth headcount , ” Hay said . “ Our full squad comprise of previously venture - back veteran founders — which is talent that ’d be pretty hard to pick up outside of this surround . ”
On the guinea pig of venture patronage , TextQL , which has a ~10 - individual team , has raised $ 4.1 million across pre - seed and seminal fluid round sco - lead by Neo and DCM with involution from Unshackled Ventures , Worklife Ventures , PageOne Ventures , FirstHand Ventures and Indicator Fund .
