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Filed

AI tax software that reads source documents and catches errors in returns

★★★★4.3 · 31 reviews
Founded 2018

About Filed

Filed applies AI to corporate tax return preparation, focusing on identifying legitimate tax relief opportunities that human preparers might miss due to time constraints or knowledge gaps. The platform analyzes financial data to surface applicable tax credits, reliefs, and deductions specific to each jurisdiction and entity type. For accounting firms, Filed augments the tax preparation process by running an AI-powered optimization layer over the return before filing, checking for missed opportunities. The platform has demonstrated particular strength in identifying R&D tax credits, capital allowances, and sector-specific reliefs that require detailed analysis of expenditure patterns. Filed's value proposition is straightforward — if the AI identifies savings that the preparer would have missed, the platform pays for itself many times over. The custom pricing model typically involves a percentage of identified savings, aligning the platform's cost with the value delivered. For firms with clients in industries eligible for complex tax incentives, Filed provides a systematic way to ensure nothing is left on the table. The limitation is that Filed's value diminishes for straightforward returns where optimization opportunities are minimal.

Best for

Tax professionals wanting AI to review returns against source documents for errors and savings

Pros & Cons

Pros

  • AI identifies tax reliefs and credits that manual preparation often misses.
  • Particularly strong at R&D tax credits and capital allowance optimization.
  • Value-aligned pricing model based on savings identified.
  • Provides systematic coverage that reduces reliance on individual preparer expertise.

Cons

  • Custom pricing based on savings may create cost unpredictability.
  • Limited value for straightforward returns with few optimization opportunities.
  • Depends on the quality and completeness of underlying financial data.

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