The Most Advanced Failure Analysis Platform
The MLOps platform that helps computer vision teams get production-ready models 6x faster!
Backed By
Product
Ship Great Models Faster than your Competition
Detect, visualize & correct data failures to train better models
Value
Speed & Reliability all in one
6x
faster
Speed-up model diagnostics & improvements
80%
cheaper
Reduce your labelling & computing costs
99.9%
reliable
Achieve your desired model performance
Use-Case
Jupyter Notebook on Steroids
Supercharge your datasets and models to build state-of-art ML pipelines
1. Slice & Dice Data
Quickly find groups of images that match your criteria for better data management
2. Bias Detection
Correctly detect & identify bias in your dataset to improve model performance
3. Visual Similarity Search
Quickly retrieve groups of images based on selected content
4. Embeddings for Outliers
Identify edge cases and outliers in your data to improve data quality
5. Enhance Data Quality
Identify incorrect annotations or data imbalance and quickly fix them
6. Model Comparison
Compare models across different development and production environments or edge deployments
Industries
Industries Tenyks Supports
Resolve any computer vision challenge on a single platform
Retail
Robotics
Smart Cities
Sports & Media
Experience
Team Experience
Built with a blend of PhD research and Industry-grade engineering so that ML engineers can produce their best work
News
Stay Updated with the Latest
We started Tenyks to invent the way humanity interacts with AI to protect the world from the terminator
Tenyks, a spin-out from the University of Cambridge, hopes to provide the next breakthrough in AI after raising $3.4 million.
Tenyks, the Cambridge University spin-off startup, closed a $3.4M round for the development of its MLOps tools platform to help ML engineers.
Celebrated Cambridge academic Stephen Hawking warned shortly before his death that if AI wasn't managed carefully it could spell the end of the human race.
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Enjoy Improving your ML Models
Figure out what's wrong and instantly fix it
