Handl

API to convert documents into structured data

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Handl provides a flexible API for document capture and data extraction by merging deep learning with human-in-the-loop.
Handl gallery image
Handl gallery image
Handl gallery image
Handl gallery image
Handl gallery image
Launch tags:Artificial Intelligence•Tech
Launch Team
agent by Firecrawl
agent by Firecrawl
Gather structured data wherever it lives on the web
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What do you think? …

Ivan Uvarov
@dimadewinn Looks good! What do you mean by special knowledge from in-house team? What can your crowd annotate?
Dima Dewinn
Maker
@ivan_uvarov many thanks! Handl crowd is good for general tasks. You can assign tasks to groups of workers each of which is focused on a specific area. But if labeling requires the knowledge of Chinese or medical education, you may need your in-house team.
Shashkova Natalia
TripleTen
Maker
@dimadewinn @ivan_uvarov one soil one love
Dima Dewinn
Maker
Greetings Hunters, Dima from Handl here. I’m thrilled to introduce you to Handl, a tool to label and manage data for machine learning. On Handl, you will get your high-accuracy datasets with ease. We employ 25k qualified crowdworkers, who have labeled more than 6 million images, texts and sounds for tech companies and startups so far. Handl crowdworkers work remotely mostly from developing countries and get paid up to 3$/ho for their effort. If your labeling requires some special skills, you can invite your in-house team to do the job. We have a complete set of tools to cover data annotation needs: classes, bounding boxes, polygons, text input, and text segmentation, all easy to use and neat. Select and combine them the way you like. Above that, you can manage, share and safely store your datasets from here. Unlike MTurk and similar microtasking services, Handl stands for machine learning data labeling only. This allows us to acquire, train and qualify our crowd to perform labeling at the highest accuracy level on the market. Our consensus algorithm ensures quality by assigning the same task to a number of crowdworkers, until the proper accuracy is reached. Try Handl here — https://handl.ai On the occasion of the launch, Hunters get free annotations of up to 1,000 images or texts with the “PRODUCTHUNT” code. Follow the link — https://handl.ai/form We are happy to get your feedback and answer any questions. Cheers.
Tony Urban
Yes, yes, yes!!! We'd definitely use it
Dima Dewinn
Maker
@tony_urban looking forward to it!
Anna Gotta
Hi Dmitry, please provide more usecases on how your product can be used by different companies with different goals. I don't understand, if your product can be helpful for me.
Dima Dewinn
Maker
@anna_gotta we can't share details about our customers, but summarily more than 6 million annotations have been already done on Handl for companies as Nvidia, Nestle, Cherry Home, etc. Whatever they do with it)
Aaron O'Leary
Product Hunt
Definitely going to try this out! Also I love the thumbnail!
Dima Dewinn
Maker
@aaronoleary pleasure to hear that!
Roman Tezikov
Nice idea! But why are you better than Mechanical Turk?
Dima Dewinn
Maker
Thanks @roman_tezikov. Unlike Amazon’s MTurk and similar microtasking services, Handl stands for machine learning data labeling only. This allows us to acquire, train and qualify our crowd to perform labeling at the highest accuracy level on the market. And we have a different internal workflow for data annotation — crowdworkers don't choose what tasks to perform. They just work properly and get paid based on the time spent and their accuracy reached.
Dmitry Tuzoff
Hi, quick question: are you planing some integrations with service marketplaces, like Freelancer or Upwork?
Dima Dewinn
Maker
@tuzoff many thanks! We do plan some nice integrations, we will announce them in detail soon.
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