What Do Investors Check About Your Corporate Structure at Series A?
What Do Investors Check About Your Corporate Structure at Series A?
IP problems torpedo AI deals at the finish line. If you have a term sheet, legal DD has already started. This is what investors are looking for — and what kills deals after signing.
Seventy to eighty percent of the value in an AI company sits in intangible assets: the model weights, the training pipeline, the proprietary data, the brand, and the IP that makes the technology defensible. At Series A, sophisticated investors run legal due diligence specifically to verify that the company actually owns what it is selling. For AI startups, that inquiry has become deeper and more technically demanding than it was three years ago. Investors and their counsel now review AI structuring, IP chain integrity, training data provenance, and regulatory readiness as a single integrated exercise — not as separate boxes to tick.
The good news: every problem investors find in DD is a problem you could have fixed before they started looking. This guide maps what the legal review covers, identifies the five issues that most reliably kill AI deals after term sheet, and gives you a 10-item checklist to assess your own readiness before the data room opens.
Four Blocks Investors Review in Legal DD
Series A legal due diligence on an AI startup is not a standard corporate review. Investors’ counsel — and increasingly, dedicated AI legal specialists — work through four distinct blocks in a structured sequence.
Before reviewing any IP, investors verify that the corporate structure is clean and the company is organised to receive investment. Unexpected shareholders, undocumented share issuances, or unclear voting arrangements can make closing impossible regardless of how strong the technology is.
The IP chain review is the most important block for AI companies. Investors are confirming one thing: that the company legally owns the IP it is built on. Every contribution to the codebase, model, and dataset that was made by a person must be traced to a written assignment from that person to the company.
This block is unique to AI companies and is where most traditional legal teams — and most founders — underestimate their exposure. Three separate licence categories must be reviewed.
For any AI startup with EU users, EU customers, or EU market ambitions, investors now expect a credible EU AI Act readiness posture. This is not optional for investors with EU LPs, portfolio ESG requirements, or regulatory exposure themselves.
Five Problems That Kill AI Deals
These are not theoretical risks. Each of the following has caused a Series A to be restructured, repriced, or killed after term sheet in the last 24 months. Most are preventable with six weeks of pre-DD legal work.
Series A DD Readiness Checklist
Ten items. These are the questions investor counsel will ask. Check each one off as you confirm it is in order — before the data room opens.
Frequently Asked Questions
Ideally, six to twelve months before you expect to raise. In practice, most founders begin when they receive a term sheet or when investor conversations become serious. At that point, you typically have four to six weeks before a data room request arrives. That is enough time to fix clean documentary issues — missing signatures, absent assignment agreements, basic cap table errors — but not enough time to remediate a fundamentally compromised training dataset or renegotiate a contractual structure that embeds IP in the wrong entity. The earlier you start, the more options you have.
A founder IP assignment is a written agreement in which each founder transfers ownership of any IP they created — code, models, datasets, inventions, designs — to the company. It matters at Series A because investors are buying equity in the company, and the value of that equity depends on the company owning the technology. If a founder retains personal ownership of the core IP — even unintentionally, through an unsigned or inadequate agreement — the investment is buying equity in a shell. Courts and investor counsel look at the date the IP was created, the date of incorporation, and the date of assignment. Pre-incorporation work is a specific risk area that requires explicit treatment in the assignment agreement. See our detailed guide on Founder IP Assignment for AI Startups.
It depends on the specific licence version and your use case. LLaMA 2 required Meta’s written approval for commercial use above a threshold number of monthly active users. LLaMA 3 and later versions have different licence terms but include an Acceptable Use Policy that prohibits specific applications. Mistral models are generally permissively licensed but some variants carry restrictions. The general principle is: never assume an open-source model permits commercial deployment without reading the full licence, Acceptable Use Policy, and any supplementary terms. Investor counsel will pull these licences during DD and map them against your actual product use case. A mismatch after term sheet is one of the hardest problems to fix quickly.
The IP section of a Series A data room for an AI company should contain: (1) all founder IP assignment agreements, signed and dated; (2) a schedule of all employees and contractors who contributed to the product, with copies of their relevant contracts and assignment clauses; (3) a training data register listing each dataset used, its source, and the licence or rights basis for commercial use in AI training; (4) copies of all model licences and API provider agreements with the relevant terms highlighted; (5) a change-of-control analysis flagging any agreements with CoC provisions; and (6) if EU exposure is present, the EU AI Act risk classification memo and compliance roadmap. Presenting a well-organised IP section is itself a signal to investors — it demonstrates operational maturity and reduces the perceived risk of investing.
Directly, EU AI Act compliance status does not have a standard valuation formula at Series A. Indirectly, it affects valuation in two ways. First, EU investors and investors with EU LPs increasingly treat regulatory readiness as a de-risking factor — a company with a documented compliance roadmap for its EU market is priced as lower-risk than one with no awareness of its obligations. Second, for companies building high-risk AI systems (as defined by EU AI Act Annex III — HR tools, credit scoring, healthcare AI), a credible compliance programme is becoming a prerequisite for enterprise sales in the EU. Enterprise customers increasingly require EU AI Act compliance documentation as part of procurement. A company that cannot demonstrate a path to compliance cannot win the enterprise contracts that justify its Series A valuation. See the August 2026 high-risk deadline for current timing context.
The best time to fix IP problems is before investors find them.
A pre-DD legal review takes four to six weeks. It identifies and remediates the issues that would otherwise surface at the worst possible moment — during DD, when your leverage is lowest and the cost of delay is highest.



Post Comment