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Handl — Turn paper documents into structured data
Handl converts any document into structured data. Powered by AI that is constantly improved by the data labeling platform.
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Replies
@drilonjaha Crowdworkers can withdraw earnings inside the application straight to their banking cards.
Like the emotions of the cat during tracing
Pros:The process is fun
Cons:Didn't notice
Curious how it differentiates from MTurk, Figure8, etc.
Pros:Looks handy! Labelling as a service
Cons:None
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.
@dimadewinn Congrats on the launch, really dig the video. How does Handl handle data safety?
@_klen thanks! We guarantee data security as we never show the whole data to a single worker. For example, when labeling IDs, we divide them into several fields so that one worker does not see the whole document. Later on, we put the fields together inside the client's contour.
@anatoly_marin Handl interfaces can be mixed together and used for any type of data. If you have something very unique, text dd@handl.ai, please
Do you have API channels for ongoing data flows? And if so, how do you charge for that.
@alexey_melnichek We do provide an API channel for recurring tasks. Text me at ns@handl.ai, let's see what we can offer you.
Would love to learn more about the application of the product and business use cases.
Pros:The idea is fantastic!
Cons:None so far
@mitya_sudakov using our tools and labeling by the crowd are separate full-fledged options. Check out our pricings here: https://handl.ai/#howitworks
Hope to see more use cases in future
Pros:Your list of clients looks impressive
Cons:Unfortunately no precise information of what you've done for them
So excited for this release. Well done @dmitry_matskevich ! What's your pricing?
Thanks @mikhail_larionov! Pricing for our tools starts from $399/mo. Crowd workforce is charged separately, pricing depends on complexity of your annotation tasks. Learn more here — https://handl.ai/#howitworks
Nice job, the number of crowd workers is really impressive. How did you attract them?
@gabrelyanov We acquire labelers with press and social media. Anyone can join and start working on Handl.
Looks really really interesting! Questions:
1) What is the maximum and the minimum data volume for labeling?
2) Can we buy ready "cats" (for example) vertical datasets? Is it going to be a marketplace for different verticals?
3) What other datasets verticals do you have?
@goldenalf13 thanks Andrew! We can deal with any data volume and we have a flexile pricing for that. For now, we work with client's data only. We do not trade in any way.
MoMAR