How We Built Our AI Tax Optimization Engine

E
Engineering Team
12 min read
How We Built Our AI Tax Optimization Engine

Abstract

This paper presents the architecture of AI2Fin's Tax Optimization Engine (TOE) and hybrid neuro-symbolic AI for tax compliance and deduction discovery.

DOI:10.1145/3456789.1234567

Methodology

  • 1

    Data Collection: Anonymized transaction datasets from beta users.

  • 2

    Model Training: Fine-tuning on tax case law and IRS publications.

  • 3

    Validation: A/B testing against human CPA review.

Key Findings

  • Hybrid models reduce false positives by 85% compared to pure ML.

  • Contextual analysis identifies complex deduction patterns.

  • Real-time latency under 200ms for standard volumes.

References

[1]
[2]
Doe & Johnson. (2024).Efficient Transformers for Financial Text.

Building an AI system that understands tax regulations...

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About the Author

E

Engineering Team

AI2Fin Engineering