Saarthi: The First AI Formal Verification Engineer
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866910853474811904 |
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| author | Kumar, Aman Gadde, Deepak Narayan Radhakrishna, Keerthan Kopparam Lettnin, Djones |
| author_facet | Kumar, Aman Gadde, Deepak Narayan Radhakrishna, Keerthan Kopparam Lettnin, Djones |
| contents | Recently, Devin has made a significant buzz in the Artificial Intelligence (AI) community as the world's first fully autonomous AI software engineer, capable of independently developing software code. Devin uses the concept of agentic workflow in Generative AI (GenAI), which empowers AI agents to engage in a more dynamic, iterative, and self-reflective process. In this paper, we present a similar fully autonomous AI formal verification engineer, Saarthi, capable of verifying a given RTL design end-to-end using an agentic workflow. With Saarthi, verification engineers can focus on more complex problems, and verification teams can strive for more ambitious goals. The domain-agnostic implementation of Saarthi makes it scalable for use across various domains such as RTL design, UVM-based verification, and others. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_16662 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Saarthi: The First AI Formal Verification Engineer Kumar, Aman Gadde, Deepak Narayan Radhakrishna, Keerthan Kopparam Lettnin, Djones Artificial Intelligence Recently, Devin has made a significant buzz in the Artificial Intelligence (AI) community as the world's first fully autonomous AI software engineer, capable of independently developing software code. Devin uses the concept of agentic workflow in Generative AI (GenAI), which empowers AI agents to engage in a more dynamic, iterative, and self-reflective process. In this paper, we present a similar fully autonomous AI formal verification engineer, Saarthi, capable of verifying a given RTL design end-to-end using an agentic workflow. With Saarthi, verification engineers can focus on more complex problems, and verification teams can strive for more ambitious goals. The domain-agnostic implementation of Saarthi makes it scalable for use across various domains such as RTL design, UVM-based verification, and others. |
| title | Saarthi: The First AI Formal Verification Engineer |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2502.16662 |