The world of timekeeping for knowledge workers is transforming through the use of AI and machine learning. Understanding how to leverage these technologies is crucial for improving efficiency and productivity.

In this episode, we’re joined by Vincent La, Principal Data Scientist at Laurel, and Jim Howard, Principal Machine Learning Engineer at Laurel, to explore the implementation of AI in automating timekeeping and its impact on legal and accounting firms.

Key Takeaways:

(01:54 ) Laurel's mission in time automation.
(03:39 ) Solving clustering, prediction and summarization with AI.
(06:30 ) Daily batch jobs for user time generation.
(08:22 ) Knowledge workers touch 300 items daily.
(09:01 ) Mapping 300 activities to seven billable items.
(11:38 ) Retraining models for better performance.
(14:00 ) Using Airflow for retraining and backfills.
(17:06 ) RAG-based summarization for user-specific tone.
(18:58 ) Testing Airflow DAGs for cost-effective summarization.
(22:00 ) Enhancing Airflow for long-running DAGs.

Resources Mentioned:

Vincent La -
https://www.linkedin.com/in/vincentla/
Jim Howard -
https://www.linkedin.com/in/jameswhowardml/
Laurel -
https://www.linkedin.com/company/laurel-ai/
Apache Airflow -
https://airflow.apache.org/
Ernst & Young -
https://www.ey.com/


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#AI #Automation #Airflow #MachineLearning