Our client is a European company that delivers natural language and search based analysis on textual data. Their technology enables users to just point to their data and start asking questions or search to get interactive results from data.
Our client wanted to train their model to extract named entities in business documents. For the algorithms to understand the information they are being fed, they must be fed large volumes of relevant annotated training data. The challenge was linking relevant text strings and metadata labeling. Our client wanted to save the time of their data scientists and get high quality annotated data at scale.
Since we were dealing with huge passages of text with technical language we formed a team of experienced annotators lead by an industry expert with an end to end customized workflow:
A team of 15 annotators worked on the task for a month and we were able to annotate some tens of thousands of lines of textual data. Our efforts freed up the data scientists’ time to work on their core technology instead of spending time on data annotation and QC. Our work also improved the performance of the models by a significant amount.
Our data annotation efforts helped our client implement a smart city project with challenging requirements.
We helped a sports analytics leader in developing AI models for sports analytics.
Important things to look for when choosing a data annotation partner
Case study on how we used Human in the Loop for data curation
Case study on how we provided image annotation services for an autonomous robotics startup
Check how we helped a client in increasing the performance of their models.
Contact us with your requirements and we will set up a team to wok on your free pilot project. No commitments on your side.