Project Summary
An AI company developed a fine-tuning and retrieval architecture for a domain-specific large language model deployed in regulated document analysis, where off-the-shelf model configurations produced hallucination rates and latency that made outputs unreliable for compliance-grade use. By applying for the R&D Tax Credit, this company was able to attain a Total State Credit of $69,150 and a Total Federal Credit of $199,780.
Project Overview
To qualify for the R&D Tax Credit, each activity must satisfy the IRS four-part test. CSSI’s analysis confirmed that the qualifying activities identified for this company met all four criteria:
- Business Component: Developing a fine-tuned language model and retrieval pipeline capable of producing verifiably accurate outputs on domain-specific regulatory documents within production latency and cost constraints.
- Elimination of Uncertainty: It was unknown whether a combination of custom fine-tuning datasets, retrieval-augmented generation architecture, and quantization strategy could reduce hallucination rates below acceptable thresholds while maintaining sub-second inference latency at production query volumes.
- Process of Experimentation: The team iterated on training data curation, tested multiple embedding and retrieval configurations, ran systematic evaluation against labeled accuracy benchmarks, and refined model architecture and quantization parameters through successive experiments until accuracy and latency targets were simultaneously achieved.
- Technological in Nature: Activities were grounded in computer science, machine learning, and applied statistics.
|
Employee Wages |
$1,380,000 |
|
Supply and Contractor Costs |
$156,750 |
|
Total QRE’s |
$1,536,750 |
|
Total State Credit |
$69,150 |
|
Total Federal Credit |
$199,780 |
Study Results
The analysis identified a total of $1,536,750 in Qualifying Research Expenses (QREs) across the tax year. Employee wages accounted for the largest share, with $1,380,000 attributable to machine learning engineers, data scientists, and software engineers directly engaged in qualifying research activities. Supply costs contributed an additional $62,500 in qualifying expenses, primarily from compute resources, testing datasets, and infrastructure used in model development and validation. Contractor expenses added $94,250, representing the 65% allowable portion of third-party research costs under IRC §41. Based on those qualifying expenses, the study produced a federal R&D Tax Credit of $199,780 and a state R&D Tax Credit of $69,150, bringing the company’s total tax credit benefit of $268,930.
Key Takeaways
- Innovation in AI development qualifies for meaningful tax relief. Building custom model architectures and fine-tuning pipelines to solve real accuracy and latency problems meets the same four-part test as R&D in any other industry, even though the “lab” is code and compute rather than a physical shop floor.
- Engineering payroll is the biggest lever. With $1,380,000 in qualifying wages, this company’s ML engineers, data scientists, and software engineers made up the bulk of its $1,536,750 in QREs, showing that headcount doing hands-on experimentation is usually the largest driver of credit value.
- Cloud compute and testing infrastructure count too. The $62,500 in supply costs confirms that compute resources and datasets used for training and validation aren’t just overhead; they’re qualifying expenses that add directly to the credit.
- Contractor work still pays off, even at a discount. Third-party research costs are only 65% creditable under IRC §41, but the $94,250 qualifying portion from $145,000 in contractor spend still meaningfully boosted the total QRE.
- The combined benefit is substantial. Between the $199,780 federal credit and $69,150 state credit, this company recovered $268,930, cash that can be reinvested directly into further model development.
- Credit eligibility isn’t limited to breakthrough AI. The qualifying work here was applied engineering: fine-tuning, retrieval architecture, and evaluation testing. Companies don’t need to be inventing new AI theory to qualify; they just need to be resolving genuine technical uncertainty.
Ready to Discover Your R&D Tax Credits Potential?
If your company is developing or improving products, formulas, or processes, you may be leaving significant tax credits on the table. CSSI’s engineering-based approach ensures every qualifying activity is identified, documented, and defensible, so you capture the full value of the work your team is already doing.
Request a Free Analysis today and find out what your business could qualify for.
