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Closing the loop: From snippet monster to maintainable insights
Intercom’s Chief AI Officer Fergal Reid sits down with Staff ML Scientist Fedor Parfenov to unpack how the Fin team turned failed conversations into better answers - safely. They trace the journey from Copilot to the new Insights product, tackling content gaps, the “snippet monster,” accumulation and consolidation, and why causal inference beat classic A/B tests for measuring real impact.
Watch this episode on YouTube: https://youtu.be/Qagm7Pb2aRk?si=2bIhZ0uAd0XEBw8v
Follow the people
https://www.linkedin.com/in/fergalreid/
https://www.linkedin.com/in/fedor-parfenov/
https://fin.ai/research/
Insights and blogs from the AI Group building Fin at Intercom
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
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By FinIntercom’s Chief AI Officer Fergal Reid sits down with Staff ML Scientist Fedor Parfenov to unpack how the Fin team turned failed conversations into better answers - safely. They trace the journey from Copilot to the new Insights product, tackling content gaps, the “snippet monster,” accumulation and consolidation, and why causal inference beat classic A/B tests for measuring real impact.
Watch this episode on YouTube: https://youtu.be/Qagm7Pb2aRk?si=2bIhZ0uAd0XEBw8v
Follow the people
https://www.linkedin.com/in/fergalreid/
https://www.linkedin.com/in/fedor-parfenov/
https://fin.ai/research/
Insights and blogs from the AI Group building Fin at Intercom
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.