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AI Prequalification Chatbot for R&D Tax Credits

TaxTaker automated prospect prequalification with a chatbot trained on IRS R&D tax code and its own sales process, cutting time on unqualified prospects 30% and lifting close rate ~10%.

~75%

Cut from expert lookup time

2–4 months

Implementation Time

Not disclosed

Project Cost
the challenge

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.

what they built

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.

best fit for

Tax-incentive firms and service businesses whose qualification process depends on scarce expert time and could be partly self-served.

Ai ROLE
infrastructure
  • Gusto (payroll platform supplying data for live eligibility checks)
  • IRS R&D tax credit code (reference corpus)
  • TaxTaker's documented qualification process and sample sales conversations (training material)
  • TaxTaker's public website (chatbot placement)
integration points
  • Direct Gusto API integration returning real-time eligibility results in-conversation
  • Chatbot to TaxTaker onboarding workflow handoff for qualified prospects
  • Conversation-flow techniques maintaining continuity across the qualification sequence
impact

30% Less Time on Unqualified Prospects

The team spent 30% less time dealing with prospects who were not qualified.

~10% Higher Close Rate

The close rate rose about 10% after launch.

Trained on IRS Code + Gusto

The bot draws on IRS R&D code and integrates with Gusto for live eligibility results.

Bryson Greenwood

Founder & Head of AI
TaxTaker
Founder and Head of AI at PressW, an AI consultancy in Austin. Ten-plus years building production AI, from custom NLP and computer vision to LLM retrieval pipelines.
GEt an intro
industry
Financial Services
business organization
Sales & Revenue
AI TYpe
Conversational AI (Chatbot / Agent)
value type
Time Savings
Revenue Growth
frequently asked questions
How did TaxTaker cut time spent on unqualified prospects by 30% with an AI chatbot?

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%.

What AI tools and data did the R&D tax credit chatbot use?

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.

What results did TaxTaker achieve?

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.

How long did the prequalification chatbot take to build?

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.

Who is this AI prequalification approach best for?

Tax-incentive firms and service businesses whose qualification process depends on scarce expert time and could be partly self-served.

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