AI BriefingThree Lessons for Securing a Sustainable AI Edge
Key point
Intercom built competitiveness by keeping pace with rapidly evolving AI models through early experimentation, rigorous evaluation, and a flexible architecture.
Details
Intercom began experimenting right after GPT-3.5 launched and shipped its AI agent Fin within 4 months. To do this, it invested $100 million in an AI-centric replatforming effort and restructured its organization to execute an AI-first strategy.
First, early experimentation built up proficiency with the models. Intercom prepared to respond immediately to the GPT-4 launch, and after confirming that GPT-4.1 showed high reliability and low latency on Fin Tasks, it adopted the model quickly. It also used chain-of-thought prompting to compensate for performance gaps.
Second, a rigorous evaluation process secured speed. Every new model goes through offline testing and live A/B testing before being applied to Fin Voice, based on the Realtime API, or to Fin Tasks. This system allowed the migration from GPT-4 to GPT-4.1 to be completed in just a few days.
Third, Intercom is focused on securing long-term technical advantage by designing a flexible architecture that can evolve alongside the changing technology landscape.
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