TaxTaker needed expert involvement for every prospect just to assess basic eligibility, prospects couldn't self-serve complex IRS language, and onboarding capacity was bottlenecked by limited expert availability.
PressW built an AI chatbot trained on the IRS R&D tax credit code and TaxTaker's qualification process, integrated with the Gusto API to deliver personalized eligibility results inside the conversation, with flow techniques to keep continuity.
The team trained the bot on TaxTaker's process, IRS code, and sample conversations to replicate the sales-call experience, with direct API integration for real-time eligibility results.
Tax-incentive firms and service businesses whose qualification process depends on scarce expert time and could be partly self-served.

TaxTaker replaced expert-led eligibility screening with a chatbot trained on the IRS R&D tax credit code and its own qualification process. Prospects now self-serve through the complex eligibility questions and get a personalized result inside the conversation, which cut time spent on unqualified prospects by 30%.
The chatbot was trained on the IRS R&D tax credit code, TaxTaker's qualification process and sample sales conversations, and integrates directly with the Gusto API for real-time eligibility results. The underlying model is not disclosed.
Time spent on unqualified prospects fell 30%, and the close rate rose roughly 10% after launch. Onboarding was no longer bottlenecked by limited expert availability.
The record does not state a timeline. The work covered training the bot on TaxTaker's process and the IRS code, replicating the sales-call experience, and integrating the Gusto API for live eligibility results.
Tax-incentive firms and service businesses whose qualification process depends on scarce expert time and could be partly self-served.