Does It Tie Out? Towards Autonomous Legal Agents in Venture Capital
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arXiv
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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908725826027520 |
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| author | Colombo, Pierre Boudiaf, Malik Sweet, Allyn Desa, Michael Wang, Hongxi Candra, Kevin del Marmol, Syméon |
| author_facet | Colombo, Pierre Boudiaf, Malik Sweet, Allyn Desa, Michael Wang, Hongxi Candra, Kevin del Marmol, Syméon |
| contents | Before closing venture capital financing rounds, lawyers conduct diligence that includes tying out the capitalization table: verifying that every security (for example, shares, options, warrants) and issuance term (for example, vesting schedules, acceleration triggers, transfer restrictions) is supported by large sets of underlying legal documentation. While LLMs continue to improve on legal benchmarks, specialized legal workflows, such as capitalization tie-out, remain out of reach even for strong agentic systems. The task requires multi-document reasoning, strict evidence traceability, and deterministic outputs that current approaches fail to reliably deliver. We characterize capitalization tie-out as an instance of a real-world benchmark for legal AI, analyze and compare the performance of existing agentic systems, and propose a world model architecture toward tie-out automation-and more broadly as a foundation for applied legal intelligence. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_18658 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Does It Tie Out? Towards Autonomous Legal Agents in Venture Capital Colombo, Pierre Boudiaf, Malik Sweet, Allyn Desa, Michael Wang, Hongxi Candra, Kevin del Marmol, Syméon Computation and Language Before closing venture capital financing rounds, lawyers conduct diligence that includes tying out the capitalization table: verifying that every security (for example, shares, options, warrants) and issuance term (for example, vesting schedules, acceleration triggers, transfer restrictions) is supported by large sets of underlying legal documentation. While LLMs continue to improve on legal benchmarks, specialized legal workflows, such as capitalization tie-out, remain out of reach even for strong agentic systems. The task requires multi-document reasoning, strict evidence traceability, and deterministic outputs that current approaches fail to reliably deliver. We characterize capitalization tie-out as an instance of a real-world benchmark for legal AI, analyze and compare the performance of existing agentic systems, and propose a world model architecture toward tie-out automation-and more broadly as a foundation for applied legal intelligence. |
| title | Does It Tie Out? Towards Autonomous Legal Agents in Venture Capital |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2512.18658 |