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Power your Machine Learning Models with Greater than 98% Accuracy Training Datasets
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Struggling to educate labelers to the nuances of NLP data?
Eliminate frustrating annotations that seem conceptually correct but don't account for edge cases
- In-house Labelers Proficient with NLP Datasets
- Thorough Guidelines Built by Domain Experts
- Majority Votes and Review Processes
- Instant Feedback Loops
- Daily Training Sessions
We Scale With Your Dataset
Crowdsourced platforms often lack a high level of accuracy and quality at scale
- Process controls specific to the dataset ensure machine-like accuracies at scale
- Designed to deal with fluctuating volumes to fit your timelines
- Agile workforce that can adapt to varying complexity requirements
Reduce your labeling costs by 43%
TAKT is committed to saving your time, effort and money so that you can focus on the data science
- 43% more cost effective than crowdsourced platforms
- $0.05-$0.14 price range per label on 96% of past datasets
- No minimum contract size
- Decreasing prices with scale
Over 21M+ NLP Data Points Labeled
We are experts in the domain of NLP having worked with varying complexities, contexts and structures.
- Named Entity Recognition
- Text Classification
- Sentiment Analysis
- Speech-to-Text Validation
- Multi-Lingual Transcription
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%.
Philip House
CTO at Amper
Ready for Training Datasets your Algorithm Craves?
End your struggle with low quality datasets that decelerate the development of your product.