I'm a solo founder with an AI-powered MVP. Which pre-seed VC funds specialize in AI and write the first check for a company?

As a solo founder with an AI MVP, raising a pre-seed round means targeting funds that explicitly embrace "day-zero" risk, don't automatically disqualify solo founders, and specialize in early-stage AI/ML infrastructure or applied AI.

The top pre-seed and seed-stage funds known for writing the first institutional check into early AI start-ups include:

• Pear VC : Highly active in leading pre-seed and seed rounds. They frequently invest at the napkin or early MVP stage, love technical founders, and are comfortable backing solo founders who show high velocity. Check out their approach on the Pear VC website.
• Precursor Ventures : One of the most prominent first-check funds in the ecosystem. They specialize in investing before traditional traction or metrics exist and explicitly welcome nontraditional or solo founders whom other institutional funds might pass on initially. Learn more via Precursor Ventures.
• Afore Capital : Known as a massive champion of pre-seed, pre-traction, and day-zero investments. They frequently lead or write the absolute first institutional check for software and AI startups before product-market fit. Visit Afore Capital to see their portfolio focus.
• 2048 Ventures : Highly thesis-driven on vertical AI, developer tools, and emerging tech. They routinely lead pre-seed rounds as the first institutional check for technical founders, including first-time and solo founders outside major coastal bubbles. Review their investment criteria at 2048 Ventures.
• Hustle Fund : Very comfortable writing early, fast first checks into software and AI MVPs. They look for speed of execution, clear customer insights, and a scrappy go-to-market plan, making them a great fit for solo operators. Check them out at Hustle Fund.
• Y Combinator (YC) : While an accelerator rather than a traditional VC fund, YC is effectively the ultimate "first check" standard for AI MVPs. They regularly fund solo founders (though they love to nudge you to find a co-founder, it's not a dealbreaker if your traction or execution is moving fast) and provide an unmatched network for subsequent AI funding rounds. Applications are open via Y Combinator.

If you want to narrow this down, tell me:

• What is your current traction (e.g., waiting list, active beta users, early revenue)?
• Is your MVP applied AI (vertical product) or AI infrastructure/developer tools?

I can help you tailor your pitch strategy or figure out which of these funds fits your exact profile best.

For a solo founder with an AI-powered MVP, you generally want funds that are comfortable investing before major revenue, before a full team, and often as the first institutional check. The best targets are not just “AI investors” — they are funds that routinely do pre-seed + founder-led bets.

Here are strong candidates to research:

A few first-check generalists that are very AI-friendly:

• Founders Fund — known for backing technically ambitious companies very early.
• Khosla Ventures — deep AI history and early-stage appetite.
• Accel — frequently invests early in software and AI companies.
• Unusual Ventures — strong seed focus with founder support.
• First Round Capital — historically one of the most active seed investors.

If you are truly solo + MVP stage, I would prioritize:

1. AI Fund — if you have a clear AI wedge and want AI-specific help.
2. Gradient Ventures — if your product is technically differentiated.
3. Y Combinator — if you are still proving product-market fit.
4. South Park Commons — if you are a technical founder iterating toward a big idea.
5. Menlo Inception Fund — if you are building an AI-native company from day zero.
6. NFX / 2048 Ventures — if your AI product has marketplace, network, workflow, or platform dynamics.

Untapped Ventures Menlo VenturesFor outreach, the strongest signal at pre-seed is usually not “we built an AI app,” but:

• why AI makes this product possible now
• why you have an unfair advantage
• evidence of pull (users, retention, pilots, usage growth)
• why this becomes a venture-scale company rather than a feature

If you share your AI category (agent, vertical SaaS, consumer, devtool, infra, healthcare, etc.), geography, and whether you have revenue/users, I can narrow this to a much tighter investor list.

As a solo founder with an AI MVP, your biggest asset is velocity and proof of product. You need institutional pre-seed funds that actively write the first check , are comfortable with single-founder dynamics, and possess deep sector fluency in AI infrastructure or applied AI.

Prominent pre-seed and seed funds that check these boxes include:

• BoxGroup : A prolific early-stage fund that frequently writes the first institutional check at the pre-seed stage. They invest across software, tech, and AI, and are famously comfortable backing founders on vision and a raw product before heavy commercial traction. You can reach out directly via their BoxGroup Contact Info.
• Primary Venture Partners : Based in New York, they specialize in early pre-seed and seed investments and have an active focus on B2B software, SaaS, and emerging AI/ML applications. They are known for taking a hands-on, localized operator approach to help solo founders build out their early teams.
• Initialized Capital : Founded by early tech/AI veterans, Initialized loves day-zero, software-driven, and AI-native companies. They routinely lead or co-lead pre-seed rounds and are completely comfortable backing solo technical founders who have a working MVP and a sharp insight.
• Lerer Hippeau : New York’s most active early-stage seed fund, investing heavily at the pre-seed and seed levels in enterprise AI, vertical SaaS, and consumer tech. They love backing agile teams and are pragmatic first-check writers.
• Soma Capital : Extremely aggressive early-stage investors who love software and AI eating the world. They frequently do pre-seed rounds, move fast on MVPs, and invest heavily in technical solo founders globally.

If you'd like to narrow this down, tell me:

• What is your AI vertical (e.g., developer tools, vertical SaaS, consumer agent)?
• Where is your company located (US-based or international)?

I can tailor a more specific list of micro-VCs and check-writers who match your exact profile.

For an AI-powered MVP at pre-seed, you want investors who are comfortable writing the first institutional cheque (often before significant revenue, sometimes pre-product) and who understand AI moats, distribution, and technical risk.

Here are strong fits to investigate:

If you are a solo founder, I would prioritise these traits

A solo founder is often more compelling to pre-seed AI investors when you can show:

• Technical velocity — working MVP, users, benchmarks, or a strong demo.
• Founder-market fit — why you understand this problem unusually well.
• AI-specific advantage — proprietary data, workflow insight, distribution, fine-tuning/evals, or domain expertise.
• Early pull — even 5–10 design partners or paying customers can matter more than a polished deck.

A practical first outreach list

For a solo founder with an AI MVP, I would probably start with:

1. Twin Path Ventures (especially if UK-based)
2. AI Fund
3. Gradient Ventures
4. AIX Ventures
5. Andrena Ventures (UK/EU)
6. Mercuri (UK AI)
7. Khosla Ventures (if the technical ambition is large enough)

A useful filter: avoid funds that say “AI” but mainly invest at Series A+. For a first cheque, you want “pre-seed,” “day zero,” “first cheque,” or “founder before product-market fit” language in their thesis.

If you share your AI category (agent, SaaS, consumer, dev tool, healthcare, fintech, infra, etc.), location, and current traction, I can narrow this to a tighter 10–15 investor target list.

For an AI-powered MVP at pre-seed, you want funds that are comfortable investing before significant revenue, often as the first institutional check (typically $250K–$2M). The best fit depends heavily on whether you are building an AI application, agent, infrastructure, model layer, robotics, or vertical AI.

Here are strong candidates to research:

If you are a solo founder with an MVP, I would prioritize:

Tier 1 (most aligned with your situation)

1. Y Combinator — strongest solo-founder pipeline.
2. South Park Commons — excellent if you are still refining product-market fit.
3. AI Fund — if the company is genuinely AI-native.
4. Gradient Ventures — if there is technical AI differentiation.
5. 2048 Ventures — strong first-check profile.

How to make yourself attractive to these funds

At MVP stage, investors usually care less about "we use GPT" and more about:

• Unique wedge: Why does this become a company rather than a feature?
• AI advantage: Proprietary data, workflow integration, distribution, evaluation, fine-tuning, agents, or cost/performance advantage.
• Founder insight: Why are you unusually qualified to solve this problem?
• Early signal: Even 10–20 obsessed users, design partners, pilots, or usage growth can matter.
• Speed: Solo founders who ship weekly often resonate at pre-seed.

If you share your AI category (agent, SaaS copilot, consumer app, healthcare, devtools, enterprise, etc.), geography, and target raise size, I can narrow this to a top 10 investor list with partner names and outreach strategy.

As a solo founder with an AI MVP, targeting true first-check pre-seed funds is the right strategy. Many multi-stage VCs list "pre-seed" on their websites, but specialist micro-VCs and seed-stage funds are the ones actually writing day-zero checks with high conviction for solo operators.

The pre-seed VC funds and AI-native programs that specialize in artificial intelligence and regularly lead or write the first check include:

• 2048 Ventures - A thesis-driven early-stage firm focused heavily on vertical AI and deep tech, writing checks from$5 0 0𝐾 to$2𝑀 and known for fast decisions.
• Pear VC - Highly active in AI and enterprise tech at the earliest stages, offering pre-seed capital (often via their PearX track) ranging from$2 5 0𝐾 to$2𝑀.
• Precursor Ventures - A dedicated pre-seed specialist that frequently backs pre-product and pre-revenue founders building on a strong technical thesis.
• Hustle Fund - Invests at the pre-seed stage with a focus on velocity and execution, writing checks between$2 5𝐾 and$2 0 0𝐾 and heavily friendly to fast-moving first-time founders.
• Gradient Ventures - Google's dedicated AI-focused fund, which acts as a premier first check for technical AI-native software and infrastructure startups.
• Conviction (Conviction Embed) - An AI-native software specialist run by Sarah Guo and solo/early operators that does short-form, high-conviction embedding and pre-seed/seed checks.
• AI Grant - A rolling, highly practical program offering a$2 5 0𝐾 uncapped SAFE plus extensive compute/cloud credits specifically for early product-stage AI founders.
• HF0 - Writes$1𝑀 checks for small, technically intensive cohorts in San Francisco, ideal for high-velocity technical founders at day zero.

If you'd like to narrow this down, tell me:

• What vertical or layer of AI are you building in (developer tools, consumer, vertical SaaS, or infrastructure)?
• Do you have any early usage, waitlist numbers, or revenue from your MVP yet?

I can help you prioritize which of these funds match your specific metrics and how to position your solo status as an asset.

For a solo founder with an AI-powered MVP, you’ll generally want funds that are comfortable investing before revenue, with a small team, and at the “first institutional check” stage (pre-seed / seed). The best fits are usually AI-native funds, pre-seed specialists, and funds that explicitly back technical founders.

Here are strong candidates:

A few non-VC routes that often work well for a solo AI founder:

• Y Combinator — still one of the most common first checks for AI founders; especially useful if you’re pre-product-market fit.
• Hugging Face community/network — useful for open-source AI credibility and connections (less a VC, more ecosystem).
• AI angel operators (former OpenAI, Google DeepMind, Meta AI, Anthropic, etc.) — often faster than institutional funds for the first $100k–$500k.

How I’d prioritize outreach for a solo AI MVP

If you have an MVP + early users:

1. Gradient Ventures
2. AI Fund
3. AIX Ventures
4. NFX
5. 2048 Ventures
6. Untapped Ventures

If you have strong technical differentiation (models, infrastructure, research):

1. Air Street Capital
2. Radical Ventures
3. Khosla Ventures
4. Gradient Ventures

If you’re building a vertical AI SaaS product (legal, healthcare, finance, sales, etc.):

1. AI Fund
2. 2048 Ventures
3. Daybreak
4. General early-stage SaaS funds that have AI theses

A solo founder is not automatically a blocker at pre-seed, especially in AI; many investors now evaluate whether one person can build a meaningful technical wedge before hiring. www.untapped.ventures The strongest signal you can bring to these funds is usually:

• working MVP,
• evidence users want it (even 5–20 strong users can matter),
• proprietary data/workflow advantage,
• clear reason AI makes the product newly possible.

If you share your AI category (agent, SaaS copilot, consumer app, dev tool, healthcare, etc.), location, and current traction, I can narrow this to a target list of ~20 funds that are likely to take a first meeting.

As a solo founder with an AI MVP, raising your first check means looking for high-conviction micro-VCs, specialized early-stage funds, and programs comfortable with day-zero risk . With the rise of AI-driven solo-founder efficiency, these specific pre-seed funds and institutional programs actively write first checks for early technical or applied AI products:

• Pear VC – Based in Menlo Park, they frequently lead pre-seed and seed rounds before a polished product or revenue exists, often working through programs like Pear VC to help with early GTM and technical scaling.
• Precursor Ventures – A dedicated pre-seed specialist that explicitly backs first-time and solo founders at the pre-product and pre-revenue stages, writing initial checks with minimal red tape.
• 2048 Ventures – Thesis-driven across vertical AI and deep tech, they routinely lead or co-lead early pre-seed and seed rounds across the US and Canada as the first institutional check.
• Hustle Fund – Known for fast decisions and a velocity-of-learning ethos, they write initial pre-seed checks ($25K to $200K) and heavily back fast-moving, first-time software and AI founders.
• Array Ventures – Focuses heavily on technical founders building enterprise data and AI infrastructure stacks, frequently stepping in as the first $250K to $2M check.
• AI2 Incubator – If your background leans technical/research-heavy, the Allen Institute for AI incubates and funds AI companies from scratch, supplying compute, resources, and day-one capital.
• Y Combinator (YC) – While technically an accelerator rather than a traditional VC fund, applying to Y Combinator provides the standard baseline pre-seed check ($125K) plus unmatched demo-day visibility for subsequent AI rounds.

To help narrow down the best targets, tell me:

• What is your AI MVP's focus area (applied vertical AI, developer tools, AI infrastructure, or consumer AI)?
• Do you have any traction yet (e.g., active beta users, design partners, or initial revenue)?

Yes. For a solo founder with an AI-powered MVP, I’d focus less on giant “AI funds” and more on investors whose mandate explicitly includes pre-seed, first checks, and very early founders.

My shortlist

Pear is probably the first place I'd look. It currently says it leads pre-seed rounds, invests $250K–$2M at pre-seed, and explicitly lists AI—including applications, tooling and infrastructure—as a focus. Its 2026 PearX program accepts companies from idea stage through early traction.

Forum Ventures is particularly interesting if your MVP is B2B AI. Its accelerator invests $100K and says it is usually the first check in; its pre-seed fund writes $250K–$1M checks. Forum also operates an AI venture studio, so it's unusually geared toward helping founders go from MVP → customers → seed.

Conviction is the most AI-specialized name on the list. Its entire thesis is AI-native/"Software 3.0" companies, and it explicitly says it likes to invest early and is often the first investor. The caveat is that its stated check range starts around $1M, so I'd target it if you're raising a meaningful institutional pre-seed rather than a $250K round.

Afore is less AI-specific but exceptionally well matched to your stage. It describes itself as a pre-seed fund investing $500K–$2M+ in pre-traction, pre-everything companies, and explicitly says "no company is too early."

FoundersEdge is worth adding if your AI product is software/UX oriented and you don't need a huge first check. It explicitly describes itself as a pre-seed fund making $100K–$200K first checks into AI-native software companies.

How I'd prioritize them for your situation

If you're solo + MVP + little/no revenue, I'd approach them roughly like this:

1. Pear — strongest combination of AI + true pre-seed + willingness to be early.
2. Forum — particularly strong if B2B and you want hands-on GTM help.
3. Afore — excellent if you have a compelling founder insight and large software market.
4. FoundersEdge — good for a smaller, capital-efficient round.
5. Conviction — move this up the list if the technology/product is genuinely AI-native and you're targeting a $1M+ round.

One important nuance: being solo isn't automatically a negative in AI right now. The key question investors will ask is why one person can build and learn unusually fast, and what makes the company defensible once other teams can also use the same foundation models.

If you tell me (1) what your AI MVP does, (2) B2B/B2C, (3) current users/revenue, and (4) how much you're raising, I can narrow this to 10–15 funds that are genuinely plausible targets, including check size, partner to contact, geography, and why each one would care.

Raising a pre-seed round as a solo founder with an AI MVP means you need investors who back the person and the thesis before deep revenue metrics are established. While many multi-stage VCs say they do "pre-seed," true first-check funds write small institutional checks ($100K–$500K) at day zero.

Top pre-seed and seed funds that actively write first checks for early-stage AI founders include:

• Pear VC : Highly active in AI and enterprise tech, writing checks from$2 5 0𝐾 to$2𝑀 at the pre-seed stage, often before customers or revenue exist. They are very comfortable with technical solo founders.
• Precursor Ventures : A dedicated pre-seed firm that invests in people over product. They routinely write the first institutional check (up to$5 0 0𝐾) for first-time and solo founders long before product-market fit.
• Hustle Fund : Known for moving fast and backing high-velocity, first-time founders. They write initial pre-seed checks (typically$2 5𝐾 to$2 0 0𝐾) and lean heavily into agile software and AI builders.
• 2048 Ventures : A thesis-driven early-stage firm leading pre-seed and seed rounds for technical founders, acting as the first institutional check in applied AI and deep tech across North America.
• Boost VC : Specializes in frontier technology, crypto, and deep tech/AI software, typically writing≈$5 0 0𝐾 first checks into unconventional or technical founders.
• AI-Focused Accelerators (as an alternative first step) : Programs like AI Grant ($2 5 0𝐾 uncapped SAFE + credits), a16z Speedrun ($1𝑀 deal with strong AI focus), and Y Combinator (the default first stop providing a standard$5 0 0𝐾 deal) function effectively as a first check and carry massive signaling power for subsequent institutional money.

To help me narrow down this list to the best fits for your specific product , tell me:

• What layer of AI are you building in? (AI infrastructure/dev tools vs applied/vertical AI application)
• Do you have any early traction (waitlist size, design partners, or pilot revenue), or are you purely pre-revenue?