Raise pre-seed capital when you can show credible progress on a specific customer problem, explain why your team is suited to solve it, and connect the money to measurable milestones. For an AI startup, that usually means demonstrating a prototype or MVP, early customer evidence, a believable plan for model and data costs, and a path to the next financing milestone.
Size the round from the time and cost required to reach those milestones—not from a fashionable headline number. Prepare a clean cap table, a concise pitch, a targeted investor list, and a diligence folder before asking for meetings. In the United States, SAFEs are now the dominant pre-seed instrument, but their caps and other terms can materially change ownership, so model dilution and obtain qualified legal advice before signing.
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What “pre-seed” means for an AI company
Pre-seed has no universal legal or market definition. Carta uses the term broadly for the earliest outside investment used to move from a raw idea toward a validated concept or minimum viable product, often before a finished product or meaningful revenue. Some founders include friends-and-family money in pre-seed; others reserve the label for angel or institutional checks. The useful question is not which label applies, but what has been built, what remains unproven, and what the next round will require.
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At this stage, the company is testing whether a problem is important, whether a proposed solution works, and whether the founding team can build and distribute it. Seed financing generally assumes more evidence and is used to pursue product-market fit, user growth, and revenue. Those are broad stage descriptions rather than rigid market rules, so describe your stage plainly in investor conversations.
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For an AI startup, a pre-seed round may fund model experimentation, data acquisition or licensing, an initial product, safety and evaluation work, cloud or inference costs, and the first hires. It should buy a specific change in the company’s proof—not simply more time to explore an undefined idea.
How to know whether it is the right time to raise
Investors can tolerate uncertainty at pre-seed, but they still need evidence that capital will turn into learning and progress. Four practical signals matter.
1. You have tangible progress
A working prototype, product mockup, technical demonstration, or MVP is stronger evidence than an idea alone. The demonstration should show the product doing the job a customer cares about, not just a model producing an impressive isolated output. If the product is not ready for external use, show the shortest credible path from the current prototype to a testable version.
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Name the user, the workflow, and the cost of leaving the problem unsolved. Discovery conversations should reveal a repeated or expensive job rather than general enthusiasm for AI. Record who you spoke with, what they do today, what the workaround costs, and what would cause them to adopt a new tool. Early letters of intent, pilots, usage, or revenue can strengthen the case, but the appropriate evidence depends on the product and buying cycle.
3. The founder story is credible
Explain why this team understands the problem and can build and distribute the solution. Relevant domain access, technical capability, customer relationships, or a demonstrated history of executing difficult projects can all matter. Do not rely on credentials alone; connect the team’s experience to the company’s particular technical and go-to-market risks.
4. You can explain what the capital buys
State the milestones the round will fund, the people and systems required, and the evidence that will exist at the end. A credible plan might include an MVP with defined evaluation thresholds, a number of design partners, a first paid deployment, or a measurable reduction in inference cost. The milestones should be observable and time-bounded enough for an investor to understand what a successful use of capital looks like.
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AI companies should be ready to discuss model quality, evaluation methodology, unit economics or inference costs, data rights, privacy and security controls, and dependence on outside model or cloud providers when those issues are material. These are practical preparation areas, not a universal AI diligence checklist: investors will weigh them differently by product, customer, and business model.
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Set the round size from milestones and runway
Work backward from the next proof point that would make the company credible for a seed round or another major financing event. Estimate the people, infrastructure, data, compliance work, and sales effort required to reach it. Add a realistic buffer for delays and for a fundraising process that may take months. Carta suggests targeting 12–24 months of runway, but that range is guidance, not a guarantee; your hiring plan, sales cycle, compute profile, and location determine the actual requirement.
- Define the next financing-quality milestone. Write down what must be true: for example, a production-ready MVP, validated customer retention, early revenue, or a repeatable technical result.
- Build a bottom-up budget. Model salaries, payroll taxes, contractors, cloud and inference usage, data or licensing fees, security and legal work, travel, and a contingency reserve.
- Choose a runway target. Test the budget at a base case and a slower-than-planned case. Include the time needed to raise the next round, not just the time needed to build the product.
- Translate spending into milestones. Tie each major expense to an output, such as a hire completing a deployment, a compute budget supporting a defined evaluation set, or a sales role producing a specified number of qualified pilots.
- Check dilution at several raise sizes. A smaller round may force a premature fundraise; a much larger round can sell unnecessary ownership or create expectations the company cannot meet.
- State the ask clearly. Give one target amount, the expected runway, the milestones it funds, and the assumptions behind the number. Explain what changes if you close less than the target.
Current U.S. figures are useful context, not targets for an individual company:
| Measure | Figure | Qualification |
|---|---|---|
| Average pre-seed instrument | $276,000 | Carta average for Q2 2026; not an AI-specific target |
| Rounds between $1 million and $2.5 million | 18% | Carta share of pre-seed rounds as of Q1 2026 |
| Pre-seed rounds using SAFEs | 93% | Carta share in Q2 2026 |
| U.S. venture deals in 2025 | $320 billion across 15,352 deals | National Venture Capital Association (NVCA) 2026 Yearbook |
| Share of U.S. VC deal value going to AI in 2025 | 65.4% | NVCA 2026 Yearbook |
| U.S. pre-seed and seed deal value in 2025 | $22.3 billion across 5,049 deals | NVCA 2026 Yearbook |
Those market totals are highly concentrated. NVCA reports that a small number of very large AI financings heavily influenced 2025’s dollar totals. Removing financings of $100 million or more leaves roughly $105 billion across the remaining 14,865 deals. The large share of AI dollars therefore does not mean that an ordinary early-stage AI company should expect an outsized check or an easy process.
“America remains the best place in the world to start a company, to fund a company, and to build something that matters. That advantage isn’t guaranteed. It’s earned every year…” — Bobby Franklin, president and CEO of NVCA, 2026 Yearbook
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Choose the funding route that fits your constraints
There is no single best source of pre-seed money. Compare each route on capital and timing, ownership or fees, investor expertise, access to customers and follow-on capital, and the time, geography, and reporting obligations it creates.
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| Route | Potential value | Questions and trade-offs |
|---|---|---|
| Angels and syndicates | Individual checks, operator experience, introductions, and flexible participation; syndicates pool many investors. | Can require substantial relationship management. Assess whether the lead or group understands your market and can help beyond the check. |
| Pre-seed venture firms | Dedicated early-stage capital, structured support, and potential follow-on investment. | Target firms with a real pre-seed track record and relevant sector or business-model experience. Confirm check size and decision process. |
| Accelerators and incubators | Capital, mentorship, a cohort, investor access, and sometimes a demo day. | Compare current terms, dilution, location, time commitment, network relevance, and obligations. Programs change their terms, so verify them directly. |
| Friends and family | May be accessible before institutional investors and can provide an initial proof of demand. | Access is unequal, and personal relationships can be harmed by unclear expectations. Document every investment formally. |
| Venture studios | Company formation, recruiting, product support, and an operating team may be available. | Ownership, decision rights, founder role, and the long-term relationship require careful negotiation. |
| Equity crowdfunding | Can reach many investors, including non-accredited investors where the platform and rules allow. | Platform fit, disclosure, investor communications, and securities compliance require jurisdiction-specific review. |
Do not select a route solely because it is available. A technically complex enterprise product may value customer introductions and procurement experience more than a large number of small checks. A consumer product may value distribution expertise. An accelerator can be useful when the network and terms fit, but a poor fit can consume time and ownership without improving the company’s odds.
Prepare the company before contacting investors
Clean the cap table and corporate records
Maintain an accurate record of founders, issued shares, options, warrants, SAFEs, notes, vesting, and any promised equity. Organize formation documents, board approvals, intellectual-property assignments, employment or contractor agreements, and prior financing paperwork. Disorganized ownership records can delay diligence and create avoidable legal costs.
Build a concise, evidence-led deck
Your presentation should make the problem, solution, target customer, why-now argument, team, progress, market, business model, competition, raise, and milestones easy to follow. Show the product in use whenever possible. A deck supports the conversation; it does not replace a clear explanation of what you have learned and what remains uncertain.
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Keep a secure, permissioned folder with formation and ownership records, product demonstrations, customer discovery notes, pilot or revenue evidence, financial forecasts, hiring plans, and material contracts. Add technical and data documentation that is relevant to the business: evaluation sets and results, data provenance and licenses, model or API dependencies, security architecture, and a description of how inference costs scale.
Make the financial model testable
Separate fixed payroll from variable usage costs. Show how model calls, storage, data processing, and support costs change with users or transactions. Include a downside case in which usage is higher, prices are lower, or a customer takes longer to convert. Investors do not need false precision, but they do need to see that the team knows which assumptions drive cash burn.
Build a focused investor pipeline
Start with investors who consistently back companies at your stage and understand your industry, customer, and business model. A list of a few dozen well-matched prospects is more useful than indiscriminate mass outreach. For each prospect, record stage, typical check, relevant investments, partner or principal, warm-introduction paths, and a reason your company fits.
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- Map the network. Ask founders, customers, operators, lawyers, and technical advisers for introductions to investors who genuinely fit. A warm introduction is useful only when the introducer can explain why the match makes sense.
- Write a short first message. Lead with the customer problem, the evidence you have, the round target, and the specific reason you chose that investor. Link or attach only the material needed to decide whether to meet.
- Run learning conversations. Early meetings can reveal which metrics, risks, or objections are recurring. Update the deck and product evidence when feedback identifies a real gap; do not reshape the company to satisfy every individual preference.
- Track the process. Record questions, requested documents, next steps, decision makers, and any stated timing. Keep prospective investors informed with material progress rather than sending repetitive updates.
- Protect momentum and confidentiality. Share sensitive data under appropriate controls and avoid granting broad access to customer information, source code, or personal data before it is necessary.
Investor fit includes behavior after the check. Ask existing founders how a prospective investor handles difficult periods, follow-on decisions, board involvement, information requests, and conflicts. A high-profile name is not a substitute for a constructive working relationship.
Run the raise from first meeting to signed documents
Set a process that lets you compare interest without creating artificial urgency. Explain the target amount and milestones consistently, collect questions in one place, and keep the data room current. When an investor expresses interest, clarify whether the proposal is a lead investment, a participation, or a conditional indication; ask what approvals remain and what information is required.
Before accepting a term, understand the economic and control consequences, not just the headline valuation cap. Confirm whether the document includes a discount, most-favored-nation provision, pro rata rights, information rights, or other side-letter terms. Review how existing SAFEs, notes, option-pool changes, and the next priced round interact.
Use qualified counsel for the financing documents and securities-law analysis. Keep signed copies, payment records, board or shareholder approvals where required, and an updated cap table. Do not announce a closing until the documents are executed and funds have actually arrived.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.SAFE versus convertible note: mechanics that affect ownership
Carta reports that SAFEs represented 93% of pre-seed rounds in Q2 2026. A SAFE gives an investor a contractual right to receive shares in a future financing. It is not debt, generally has no interest or maturity date, and typically converts when the company completes a priced equity financing. A convertible note is debt, normally accrues interest, and has a maturity date; it may convert in a later financing or require another outcome at maturity.
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|---|---|---|
| Legal character | Contractual right to future equity; not debt | Debt that may convert to equity |
| Interest | Generally none | Typically accrues interest |
| Maturity date | Generally none | Usually included |
| Conversion pricing | Often shaped by a valuation cap, discount, or both | Often shaped by a valuation cap, discount, interest, and note terms |
| Primary founder risk | Underestimating cumulative dilution or side terms across multiple SAFEs | Missing maturity, repayment, or priority implications while stacking notes |
For a post-money SAFE, the ownership sold is generally calculated as the investment divided by the post-money valuation cap. The official SAFE materials from Y Combinator give a $1 million investment at a $6.7 million post-money cap as an example of approximately 15% ownership. That example explains the arithmetic; it is not a recommended valuation.
Model the complete financing, not one instrument in isolation. Combine every SAFE and note, the option pool before or after the financing, founder shares, pro rata rights, and the next priced round. A cap that looks acceptable on its own can produce a very different result when several instruments convert together. Compare caps, discounts, most-favored-nation provisions, and pro rata rights before signing, and obtain qualified legal advice.
Y Combinator’s current SAFE tool is designed for U.S.-incorporated companies. Companies organized elsewhere should use forms appropriate to their jurisdiction with local legal help. Fundraising, securities exemptions, investor eligibility, and disclosure obligations vary by country and sometimes by state; do not present a U.S. template as universal.
AI-specific questions investors are likely to explore
No verified source establishes one checklist that every AI investor uses. Still, you should be able to answer the questions that follow when they are material to your product.
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- Data rights: Do you own, license, or lawfully access the training, retrieval, or customer data? What restrictions apply to commercial use and retention?
- Economics: What does one task or customer cost at current usage, and how does that change with scale, model choice, caching, and latency requirements?
- Provider dependence: What happens if an outside model, cloud service, price, rate limit, or policy changes? Is there a tested fallback?
- Security and privacy: Which information enters the system, where it is stored, who can access it, and how are prompts, outputs, and customer data protected?
- Human and regulatory risk: What decisions are automated, what oversight exists, and which industry or geographic rules affect deployment?
Present measured results with the test conditions, sample size, baseline, and date. Avoid broad claims such as “best model” or “fully autonomous” when the evidence covers only a narrow task.
Common failure modes and how to correct them
| What investors observe | Likely problem | Correction |
|---|---|---|
| A polished demo but no committed user | The product is interesting, but the problem and buyer are unclear. | Run focused discovery, identify a specific workflow, and show a pilot, letter of intent, or other evidence of willingness to adopt where appropriate. |
| A large round request with a vague plan | The amount is not connected to a financing-quality milestone. | Rebuild the budget from hires, infrastructure, data, and time; state exactly what will be true when the runway ends. |
| AI claims without evaluation details | Investors cannot distinguish a reliable advantage from a favorable demo. | Document the task, baseline, test set, error categories, and limitations; explain how the result affects customer value. |
| Several instruments with incompatible terms | Cumulative dilution and conversion outcomes are opaque. | Produce a fully diluted model covering every SAFE, note, option-pool change, and priced round; have counsel review it before accepting more money. |
| Only one type of investor is being contacted | The company may be missing expertise, customers, or suitable check sizes. | Compare angels, specialist funds, programs, and other routes against the support and obligations you actually need. |
| Fundraising consumes all operating time | The company stops producing the evidence investors need to see. | Assign ownership for the process, batch meetings, maintain a decision log, and protect time for product and customer work. |
A practical pre-seed readiness checklist
- You can describe one costly or frequent customer job in a sentence.
- A prototype, mockup, or MVP demonstrates the proposed workflow.
- You have direct evidence from the target audience and can explain what it does and does not prove.
- The founding team’s advantage is connected to the customer and technical problem.
- Your cap table, formation records, intellectual-property assignments, and prior financing documents are organized.
- Your budget separates fixed payroll from variable AI and infrastructure costs.
- The raise target, runway, milestones, and downside case fit together.
- Your deck and diligence folder contain the same numbers and definitions.
- Your investor list is targeted by stage, check size, sector, business model, and useful network.
- You have modeled dilution under the proposed SAFE or note terms and the next priced round.
- You know which data, security, privacy, and provider-dependency questions are material to your product.
- Qualified counsel has reviewed the financing documents and jurisdiction-specific securities requirements.
The decision in one sentence
Raise pre-seed for an AI startup when outside capital will convert demonstrated customer and technical progress into a clearly defined next milestone, and when you can explain the resulting ownership, runway, and legal obligations before accepting the money.
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