Dili is an AI-powered tool designed to assist financial analysts and partners in due diligence processes. It excels at extracting data from various documents, including spreadsheets, flagging potential risks, and generating reports. Dili emphasizes reliability and accuracy, differentiating itself from other AI tools by avoiding hallucinations and providing confidence scores for its outputs. It's used across Private Equity, Real Estate, Venture Capital and Tax Credit Diligence and backed by Y Combinator and other investors.
• intelligent document search
• risk assessments
• spreadsheet support
• mirror your workflows
• red flags
• extract any data instantly
Yes. Dili is SOC2 Type II certified. All data is encrypted at rest and in transit. We have zero training and zero data retention policies with leading model providers.
No. We do not train or fine-tune any models on your data. If we do fine-tune models as part of an engagement with you, only you and your team will have access.
Yes! We are able to ingest, produce, and export spreadsheets as part of any workflows you configure on our platform.
We don't use LLMs to do math. Math is delegated to a separate, deterministic function. We show our work for everything.
We have internal benchmarks for a range of standard use cases including accurate fact extraction from various document formats, accurate context retrieval for common queries, and reasoning over spreadsheets which we plan on sharing in a future blog post.
If your use case involves extracting standardized data, creating memos from a collection of source material, auditing figures across thousands of documents, building a knowledge base, or just chatting with PDFs, there is a good chance our product will be useful for you and your team. Contact us to learn more.
Founding Engineer, Platform
Dili is a reliable AI copilot for financial diligence, providing accurate data extraction, risk flagging, and report generation, trusted by leading firms on thousands of high-stakes deals.
Experience Requirements:
6+ years
Responsibilities:
Data Pipeline Architecture
LLM Ops and Observability
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