An image annotation platform customised to suit your data labelling needs.
Supports bounding box, semantic, polygon, instance, point, circle and line annotations.
Built by our crazy awesome Tech team of Engineers, Data Scientists, Product Designers and Product Managers.
If you've got your own platform, no sweat. We can label on yours.
SupaAnnotator in action
Text & Language (NLP)
Multiple languages, dialects and ethnicaccents supported, one SupaTeam.
Document and subdocument level annotations for Sentiment Analysis, Named Entity Recognition (NER), Message Categorisation and Audio Collection for Automatic Speech Recognition (ASR).
We support major languages in South East Asia such as Mandarin, Cantonese, Tagalog, Bahasa Malaysia, Indonesian and regional English accents.
Coming soon: Thai, Japanese & Korean
SupaNER-dy
How we deliver
Speed, Scale & Service.
We're proud of what we do and how we do it.
“Hey Supahands, we need this in a month."
We get this all the time. Not a problem, pace is our thing.
1 million images? Sweet.
We label at scale. A qualified army of committed labellers are raring to go 24/7.
We give two sh*ts. Truly ✌️
We don't get NPS scores of 10/10 for nothing. Our clients actually like us.
“The entire Sentiment team is talking about Supahands, and QA results were above 95%.”
Nitin Anjaneya, Senior Associate, Machine Learning Services at Sprinklr
Sentiment tagging (Malay, Bahasa Indonesia, Tagalog)
Volume: 300,000 sentences per language
Project kickoff date: 29 Oct 2019
First batch delivered: 7 Nov 2019 (We're fast.) 26,474 tags for Malay and 40,000 tags for Indonesian
How it works
Get started in four easy steps.
No drama.
1
Discover
We scope out what you want to achieve.
2
Learn
We study your requirements, review guidelines and collect sample output.
3
Label
We label your data just the way you like it.
4
Deliver
We send your data back, fully labelled.
Pricing plans
Your main concerns are flexibility, quality and turnaround.
They're ours too and we price with your needs in mind.
For teams running ML experiments or building ML models for production.
.png){kind=logo}
