Power your NLP and Machine Learning Models with Consistency at Scale
Get Started
Eliminate frustrating annotations that don't account for edge cases with consistency across time.
In-house Labelers Proficient in Linguistics
Thorough Guidelines Built by Domain Experts
Repeatable and Consistent Training
Instant Feedback Loops
.png)
Annotation at scale requires custom workflows to account for your dataset's complexity.
Process controls specific to the dataset ensure machine-like accuracies at scale
Rapid hiring pipeline for varying complexity requirements
Agile workforce designed to deal with fluctuating volumes
Takt is committed to finding the exact dataset-annotator fit required ensuring you don't overpay.
43% more cost effective than crowdsourced platforms
$0.05-$0.14 price range per label on 96% of past datasets
No minimum contract size
Pilot run before agreeing to any contract
We are experts in the domain of NLP having worked with varying complexities, contexts and structures.
Build complex information extraction applications, in fields such as Clinical AI, that rely on Named Entity Recognition by domain experts who understand the context.
Leverage Takt's customized workflows, implemented through our platform, to handle complex text classification tasks that cannot be crowdsourced.
Utilize Takt's data centers in India and South-East Asia to service a range of languages while maintaining the accuracy through in-house domain experts.
Build diverse corpuses for your unique applications by leveraging our on-demand and scalable workforce for your data collection requirements.
Greater than 98% accuracy
training datasets so that you can trust your models
Ability to use your internally
developed Labeling UI or TAKT's proprietary in-house tools
Shared Slack channels to ensure you can reach our team whenever you need
Full time labelers with NDAs
working on-site at our secure facilities. SOC Type I compliant.
Our data required contextual understanding that we thought was not possible to outsource. TAKT, with its highly skilled and perceptive labelers, raised the performance of our algorithm from 90% to 98%.
Takt did a great job with our labeling task - they learned a domain-specific labeling task with a high level of accuracy and maintained a high level of accuracy throughout the task. They stand above and beyond other services due to their attention to detail and commitment to quality!
After running trials with a number of companies, Takt was by far the most accurate and reasonably priced for our needs. The team understood the level of detail necessary for >99% accuracy and we were able to virtually eliminate false-positives. I personally appreciated the crisp communication via Slack, allowing us to tackle uncertainties as they arose, ensuring high accuracy.
End your struggle with low quality datasets that decelerate the development of your product.
Get Started.svg)
