Data as of Sep 21, 2026 · Based on 311 AI responses from ChatGPT Search and Google AI Mode · See how Parse measures this
If you need pre-seed capital plus in‑house lab or hardware help to turn a scientific insight into a prototype, pick 
Brands AI recommends here
Named in 59% of answers
Good for founders building frontier science (space, materials, defense) who need a partner that tolerates high technical risk and sources from academia; less focused on providing in-house lab space than accelerators.
Named in 49% of answers
Best when you need an accelerator that supplies pre-seed funding plus hands-on lab or hardware support; IndieBio and HAX provide space, mentorship, and often the first institutional check. Caveat: focused on biotech/hard tech.
Named in 47% of answers
Named in 34% of answers
Source | Citation share |
|---|---|
 Top Early-Stage VC Firms for Pre-Seed, Seed, and Series A Foundershttps://www.everythingstartups.com/article/top-early-stage-vc-firms-for-pre-seed-seed-and-series-a-founders | 4% |
 List of Pre-Seed Investors and Venture Capital Firms [2026]https://www.openvc.app/investor-lists/pre-seed-investors | 3% |
 Top 40 Pre-Seed Funds in 2026, Ranked by Data | Beta Boomhttps://www.betaboom.com/magazine/article/top-pre-seed-funds | 3% |
 Deep Tech Venture Capital Firms: Key Players & Strategieshttps://growthequityinterviewguide.com/venture-capital/sector-focused-venture-capital/deep-tech-venture-capital-firms | 2% |
List of Deep Tech Investors & VC Firms for Startups (2026)https://www.openvc.app/investor-lists/deeptech-investors | 2% |
 Active Pre-Seed VCs: Our Top 15 Picks for Foundershttps://www.rho.co/blog/pre-seed-vc | 2% |
Deeptech funds — Curated VC Fundshttps://www.vcsheet.com/sheet/deeptech-funds | 2% |
 Top 71 Deep Tech & Hard Science Venture Capital Firms (2026)https://www.failory.com/blog/deep-tech-hard-science-venture-capital-firms | 2% |
 Deep Checks: Meet the best deeptech seed investorshttps://www.deepchecks.vc/ | 2% |
BioTech Pre-Seed Venture Capital Firms | BiotechVCList.comhttps://biotechvclist.com/pages/preseed/ | 2% |
Yes. For a **pre-product, pre-revenue company where the moat is a scientific/technical breakthrough**, I’d target investors explicitly comfortable underwriting technical risk before commercial validation: - **[dcvc.com](https://www.dcvc.com/?utm_source=chatgpt.com)** — probably the clearest fit: deep-tech specialists…
Yes. For a pre-product, pre-revenue company where the moat is a scientific/technical breakthrough, I’d target investors explicitly comfortable underwriting technical risk before commercial validation:
If you tell me the technical domain (AI, biotech, materials, energy, robotics, chips, quantum, etc.) and approximate geography, I can narrow this to ~10 investors and identify which ones have actually funded scientist founders before product/revenue.
Building a pre-product, pre-revenue company on a strong technical insight means you are pitching **technological risk** rather than market or execution risk. Traditional SaaS and consumer VCs will pass, but a specialized class of **deep tech and hard science VCs** explicitly hunt for the "scientist-founder" archetype…
Building a pre-product, pre-revenue company on a strong technical insight means you are pitching technological risk rather than market or execution risk. Traditional SaaS and consumer VCs will pass, but a specialized class of deep tech and hard science VCs explicitly hunt for the "scientist-founder" archetype at day zero.
The landscape of early-stage investors who routinely write checks based on a whitepaper, a lab bench experiment, or a core computational thesis includes the following categories and funds:
These firms are staffed with partners who often hold PhDs or have engineering backgrounds. They don't need a polished UI or early MRR; they evaluate the physics, chemistry, or biology of your insight.
If your insight originated from an academic lab, these funds are explicitly designed to bridge the gap between academic research and commercial viability.
Because you don’t have product metrics, they will scrutinize:
If you'd like to narrow this down, tell me:
I can help you tailor your targeting or suggest how to frame your initial proof points.
For a **pre-product, pre-revenue company built around a strong technical insight**, you are usually looking less for “startup VCs” and more for investors who are comfortable underwriting **scientific risk, founder insight, and technical inevitability**. The archetype is often called **scientist-founder**, **deep tech…
For a pre-product, pre-revenue company built around a strong technical insight, you are usually looking less for “startup VCs” and more for investors who are comfortable underwriting scientific risk, founder insight, and technical inevitability. The archetype is often called scientist-founder, deep tech founder, research spinout founder, or frontier technology founder.
Some investors who explicitly fit this profile:
canonical.cc — Focuses on very early, technically exceptional founders and explicitly describes investing before product, sometimes before the company is fully formed.
Good fit: AI infrastructure, robotics, compute, cryptography, foundational technology.
hax.co — A pre-seed hard-tech investor focused on science and engineering-heavy companies.
Good fit: hardware, robotics, materials, energy, industrial biotech, advanced manufacturing.
ubiquity.vc — Invests at pre-seed/seed in technical founders building software that interacts with the physical world.
Good fit: robotics, industrial software, space, applied AI.
empiricalventures.vc — Founded by scientists and focused on translating breakthrough science into companies.
Good fit: research-heavy science commercialization.
yanvc.com — Deep-tech investor covering AI, life sciences infrastructure, and industrial technologies.
Good fit: founders with technical differentiation and hard-to-replicate IP.
These firms are broader, but they have a track record of backing research-driven companies:
Strong history in science-heavy bets: AI, biotech, climate, robotics, energy.
Known for frontier technology and companies where the initial insight may precede obvious market validation.
One of the most recognizable deep-science investors; backs scientists and engineers commercializing advanced technologies.
Focuses on deep tech, computational science, and companies solving difficult physical-world problems.
Broad fund, but has backed many technical founders and frontier companies.
Particularly relevant if your insight is in AI, biotech, defense, infrastructure, or crypto/compute.
Also consider:
University-affiliated funds and translational investors:
engine.xyz — built specifically around “tough tech” emerging from research.
breakout.vc — focused on scientist founders and biology/deep science.
flagshippioneering.com — creates and funds science-driven companies internally.
A scientist-founder company often raises on:
A useful exercise is to identify which category your “technical insight” belongs to: new science, new engineering capability, new AI capability, or new application enabled by a breakthrough. The right investor set changes substantially depending on that distinction.
Backing a pre-product, pre-revenue company based on a strong technical insight means you are looking for **Deep Tech, Hard Tech, or TechBio/Science-led VCs** . These funds specifically underwrite *science risk* (will the physics/biology work?) rather than just *market risk* (will people buy it?). The venture capital…
Backing a pre-product, pre-revenue company based on a strong technical insight means you are looking for Deep Tech, Hard Tech, or TechBio/Science-led VCs . These funds specifically underwrite science risk (will the physics/biology work?) rather than just market risk (will people buy it?).
The venture capital landscape features several prominent firms explicitly tailored to the "scientist-founder" archetype at the pre-seed and seed stages:
When you talk to these funds without a product or revenue, you cannot pitch traction—you must pitch derisking velocity . Be prepared to show:
If you want to narrow this down, tell me:
I can help you pinpoint which of these specific funds is the warmest fit for your exact sector.
Yes. What you’re describing is a recognizable—and increasingly attractive—VC archetype: **the scientist-founder / technical founder whose primary asset is a non-obvious technical insight, before there is a product, revenue, or conventional market proof.** The key distinction is that you want investors who underwrite…
Yes. What you’re describing is a recognizable—and increasingly attractive—VC archetype: the scientist-founder / technical founder whose primary asset is a non-obvious technical insight, before there is a product, revenue, or conventional market proof.
The key distinction is that you want investors who underwrite technical truth + founder insight + eventual market, rather than investors who require early traction.
| VC | Fit for scientist-founder | Why |
|---|---|---|
| SOSV | ★★★★★ | Probably the purest fit at pre-seed. Explicitly invests at inception, often with its first check, and 44% of recent founders have PhDs. SOSV SOSV |
| DCVC | ★★★★★ | Exceptional fit if the insight is genuinely deep tech: AI/compute, biology, materials, climate, robotics, quantum, space, etc. They explicitly say they have more published scientists than MBAs. DCVC DCVC |
| Playground Global | ★★★★★ | Very strong for frontier technology and unusually technical founders. Particularly good if the company requires substantial R&D before commercialization. |
| Lux Capital | ★★★★★ | Strong historical appetite for scientists, researchers and contrarian technical ideas that can create entirely new markets. |
| Khosla Ventures | ★★★★★ | Particularly compelling if the insight could radically change an industry rather than incrementally improve an existing product. |
| Founders Fund | ★★★★½ | Excellent for ambitious, technically difficult companies where the founder has a differentiated worldview and enormous potential outcome. |
| General Catalyst | ★★★★ | Broad enough to take very early technical bets, particularly where the insight maps to a large industry transformation. |
| Radical Ventures | ★★★★½ | Especially relevant if your technical insight is AI/ML or AI-for-science. Its recent backing of scientist-heavy companies illustrates the appetite. Business Insider |
| AME Cloud Ventures / AI-focused seed funds | ★★★★ | Worth considering for technically deep AI companies, particularly if the founding insight is computational. |
| NFX / First Round / similar seed firms | ★★★ | Can work, but generally more product/market-oriented; the story needs to translate into a credible company sooner. |
1. SOSV — if you're genuinely pre-product/pre-revenue.
This is unusually close to the exact situation you described. SOSV says its first check is up to $550K, and that it is "almost always" the first VC investor. It explicitly accepts companies with no VC funding and even notes that non-dilutive research funding such as SBIR can precede its investment.
Its portfolio is also unusually scientist-heavy: 62% of the companies in its Deep Tech 100 have at least one PhD founder.
One caveat: SOSV requires more than one founder and expects founders to participate in its programs in NYC, SF, or Newark.
2. DCVC — if your technical insight is sufficiently consequential.
DCVC is almost tailor-made for "I discovered something technically important and believe it enables a huge company." Its stated focus includes AI, compute, climate, engineering, materials science, robotics, space, water, biology, defense, quantum and more.
Its DCVC Bio arm is even more explicit about the scientist-inventor model: it describes its investors as "scientist-inventor-operators" and specifically solicits founders combining fundamental biological/engineering insights with computation.
For this archetype, I would not pitch:
"We have a big market and we're building a product to address it." Instead, the pitch should establish a chain like:
Scientific/technical observation → why conventional wisdom is wrong → enabling breakthrough → what becomes possible → enormous market consequence.
For example:
Everyone assumes X is impossible/expensive/slow because of Y. We discovered that Y isn't actually the limiting factor. Our approach changes Z by 100×. That makes [previously impossible capability] economically viable. We're building the company that commercializes it. That's a much more natural VC narrative for a scientist-founder.
And importantly, don't apologize for being pre-product. If the insight is sufficiently differentiated, "we haven't built the product yet" can actually be evidence that you're early in the technology-development curve rather than evidence that you're unvalidated.
The optimal VC list changes dramatically depending on what the technical insight is.
If you tell me just these four things:
I can give you a ranked list of ~15 specific VCs/partners, including who at each fund is most likely to understand the science, what stage/check size they typically do, and which ones are genuinely comfortable investing before a product exists.
| VC | Fit for scientist-founder | Why |
|---|---|---|
| SOSV | ★★★★★ | Probably the purest fit at pre-seed. Explicitly invests at inception, often with its first check, and 44% of recent founders have PhDs. SOSV SOSV |
| DCVC | ★★★★★ | Exceptional fit if the insight is genuinely deep tech: AI/compute, biology, materials, climate, robotics, quantum, space, etc. They explicitly say they have more published scientists than MBAs. DCVC DCVC |
| Playground Global | ★★★★★ | Very strong for frontier technology and unusually technical founders. Particularly good if the company requires substantial R&D before commercialization. |
| Lux Capital | ★★★★★ | Strong historical appetite for scientists, researchers and contrarian technical ideas that can create entirely new markets. |
| Khosla Ventures | ★★★★★ | Particularly compelling if the insight could radically change an industry rather than incrementally improve an existing product. |
| Founders Fund | ★★★★½ | Excellent for ambitious, technically difficult companies where the founder has a differentiated worldview and enormous potential outcome. |
| General Catalyst | ★★★★ | Broad enough to take very early technical bets, particularly where the insight maps to a large industry transformation. |
| Radical Ventures | ★★★★½ | Especially relevant if your technical insight is AI/ML or AI-for-science. Its recent backing of scientist-heavy companies illustrates the appetite. Business Insider |
| AME Cloud Ventures / AI-focused seed funds | ★★★★ | Worth considering for technically deep AI companies, particularly if the founding insight is computational. |
| NFX / First Round / similar seed firms | ★★★ | Can work, but generally more product/market-oriented; the story needs to translate into a credible company sooner. |
1. SOSV — if you're genuinely pre-product/pre-revenue.
This is unusually close to the exact situation you described. SOSV says its first check is up to $550K, and that it is "almost always" the first VC investor. It explicitly accepts companies with no VC funding and even notes that non-dilutive research funding such as SBIR can precede its investment.
Its portfolio is also unusually scientist-heavy: 62% of the companies in its Deep Tech 100 have at least one PhD founder.
One caveat: SOSV requires more than one founder and expects founders to participate in its programs in NYC, SF, or Newark.
2. DCVC — if your technical insight is sufficiently consequential.
DCVC is almost tailor-made for "I discovered something technically important and believe it enables a huge company." Its stated focus includes AI, compute, climate, engineering, materials science, robotics, space, water, biology, defense, quantum and more.
Its DCVC Bio arm is even more explicit about the scientist-inventor model: it describes its investors as "scientist-inventor-operators" and specifically solicits founders combining fundamental biological/engineering insights with computation.
For this archetype, I would not pitch:
"We have a big market and we're building a product to address it." Instead, the pitch should establish a chain like:
Scientific/technical observation → why conventional wisdom is wrong → enabling breakthrough → what becomes possible → enormous market consequence.
For example:
Everyone assumes X is impossible/expensive/slow because of Y. We discovered that Y isn't actually the limiting factor. Our approach changes Z by 100×. That makes [previously impossible capability] economically viable. We're building the company that commercializes it. That's a much more natural VC narrative for a scientist-founder.
And importantly, don't apologize for being pre-product. If the insight is sufficiently differentiated, "we haven't built the product yet" can actually be evidence that you're early in the technology-development curve rather than evidence that you're unvalidated.
The optimal VC list changes dramatically depending on what the technical insight is.
If you tell me just these four things:
I can give you a ranked list of ~15 specific VCs/partners, including who at each fund is most likely to understand the science, what stage/check size they typically do, and which ones are genuinely comfortable investing before a product exists.
NFX
nfx.com
Building a pre-product and pre-revenue company based on a core technical insight means you are operating in the **Deep Tech / Tough Tech / Frontier Tech** arena. Traditional SaaS or consumer VCs will likely pass because they want metrics and quick product-market fit. However, a distinct cohort of specialized venture…
Building a pre-product and pre-revenue company based on a core technical insight means you are operating in the Deep Tech / Tough Tech / Frontier Tech arena. Traditional SaaS or consumer VCs will likely pass because they want metrics and quick product-market fit.
However, a distinct cohort of specialized venture firms, university-backed funds, and specialized accelerators explicitly hunt for the scientist-founder archetype at the pre-seed and seed stages. They underwrite technical risk rather than market risk.
The key VCs and programs that back pre-product, pre-revenue scientist-founders include:
If you'd like to narrow this down, tell me:
Backing a pre-product, pre-revenue company based on hard science or a technical breakthrough requires a specialized subset of venture capital often referred to as **Deep Tech**, **frontier tech** , or **thesis-driven seed** investors . These funds explicitly look for the "scientist-founder" archetype because they…
Backing a pre-product, pre-revenue company based on hard science or a technical breakthrough requires a specialized subset of venture capital often referred to as Deep Tech, frontier tech , or thesis-driven seed investors . These funds explicitly look for the "scientist-founder" archetype because they understand that your moat is the physics, biology, or advanced computation itself, not a quick software wrapper.
Here are the prominent venture capital firms that actively fund pre-product, pre-revenue scientist-founders, broken down by their focus:
Even though you are pre-product, these investors expect scientific validation . To de-risk the investment, they will look for:
If you'd like to narrow this down, let me know:
I can help you pinpoint the exact partners or alternative sources (like SBIR grants or university tech-transfer programs ) that fit your stage.
Yes. There is a real VC category for this—and **“scientist-founder” / “deep-tech founder” is actually a useful fundraising label** when the company is pre-product and the moat is primarily a technical insight. The key distinction is that some VCs merely *invest in deep tech*, while others are specifically comfortable…
Yes. There is a real VC category for this—and “scientist-founder” / “deep-tech founder” is actually a useful fundraising label when the company is pre-product and the moat is primarily a technical insight.
The key distinction is that some VCs merely invest in deep tech, while others are specifically comfortable underwriting technical insight before there is conventional product/market evidence.
| VC | Best fit | Why I'd consider them |
|---|---|---|
| 1517 Fund | Very early, unconventional science/engineering | Explicitly backs “renegade scientists,” deep-tech scientists, and founders at the earliest stages. 1517 Fund |
| SOSV | Hard tech, biotech, climate, robotics, materials | Probably one of the strongest institutional fits for pre-product deep tech; says it makes ~60 pre-seed investments/year, with first checks up to $550K. SOSV |
| Breakout Ventures | Biology, chemistry, computation | Particularly interesting if your insight originates in fundamental science. It explicitly describes itself as backing scientist-founders. DeepTech VC List |
| Deep Venture Partners | Fundamental science → commercial technology | Their thesis is almost exactly your description: breakthrough science + engineering + commercial opportunity, with tolerance for very early technical risk. Deep Venture Partners |
| Embark Ventures | Materials, robotics, manufacturing, semis, software/compute | Pre-seed/seed investor explicitly looking for breakthrough proprietary technology and defensibility. Embark Ventures |
| Julian Capital | Extremely early deep tech | Particularly notable because they say “No startup is too early” and accept idea-stage companies, including scientist-founded deep-tech projects. Julian Capital |
| Yan Ventures | AI, life-science infrastructure, industrial/reindustrialization | Pre-seed through Series B, with $100K–$2M checks and an explicitly operator-heavy approach to deep tech. Yan Ventures |
| Silicon Roundabout Ventures | Computing, defense, energy | Very early European deep tech; describes its target founders as exceptional technical builders working on novel technology. Silicon Roundabout Ventures |
There are also sector-specific scientist-founder funds. For example, if you're in AI × healthcare/biology, Recode Edge explicitly looks for scientists coming out of research institutions and backs companies at formation.
And if you're in biotech/life sciences, NFX Bio is unusually explicit about the archetype: its stated mission is funding “Scientist-Founders” at pre-seed/seed and helping them become entrepreneurs.
I'd pay particular attention to what these investors say they need to believe at pre-seed.
For example, Sonnerie VC's description of its scientist-founder thesis is unusually revealing: at pre-seed, when conventional company metrics don't exist, it treats the founder's depth of knowledge, understanding of uncertainty, and ability to articulate what would falsify the thesis as key investment signals.
That's exactly the investor mindset you want.
You're not really pitching:
“Here's our product and here's our early traction.” You're pitching:
“We discovered an important technical discontinuity. Here's why it's real, why existing approaches can't reproduce it, what experiment proves us right, and what enormous application becomes possible if we're right.” The right VC should get excited by that before you have revenue.
I'd separate your target list into three tiers:
Tier 1 — scientist/deep-tech-native investors 1517, SOSV, Breakout, Deep Venture Partners, Julian, and similar funds.
Tier 2 — generalist VCs with unusually strong technical taste These can be excellent once you can demonstrate that the technical insight is becoming a company, but you may have to do more translation from scientific novelty → venture-scale business.
Tier 3 — sector specialists These can be the best investors if your insight sits squarely inside a domain such as biotech, energy, semiconductors, defense, robotics, or AI.
The mistake I'd avoid is approaching 50 generic seed VCs with the same deck. Your first investors should be people who can underwrite the technical thesis itself. Once you've established technical credibility and a path to commercialization, the much larger universe of conventional VCs becomes accessible.
If you tell me what the technical insight is (even at a high level), your field, where you're based, and whether the underlying IP is academic/spun out of a lab or independently developed, I can narrow this to 10–15 specific VCs, rank them by fit, and tell you which partner at each firm is most likely to understand the science.
NFX
nfx.com
Building a company that is pre-product and pre-revenue based on a fundamental technical insight means you are operating in the realm of **Deep Tech / Tough Tech / Science-Led Venture**. While traditional software VCs will run away from "pre-product/pre-revenue," a specialized subset of early-stage venture funds…
Building a company that is pre-product and pre-revenue based on a fundamental technical insight means you are operating in the realm of Deep Tech / Tough Tech / Science-Led Venture.
While traditional software VCs will run away from "pre-product/pre-revenue," a specialized subset of early-stage venture funds explicitly hunt for the scientist-founder archetype. They understand that your first product is de-risking the underlying physics, chemistry, or biology.
The prominent early-stage VCs and organizations that explicitly back pre-product, science-driven founders include:
Key Advice for Pitching as a Scientist-Founder
If you want to narrow this down, let me know:
I can give you a more targeted list of specific micro-VCs and non-dilutive grant paths for your exact field.
Yes. There is a fairly specific VC archetype for what you're describing: **pre-product, pre-revenue, technically differentiated, with the founder's scientific insight being the primary asset**. The important distinction is that you don't want a generic "early-stage VC." You want investors who are comfortable…
Yes. There is a fairly specific VC archetype for what you're describing: pre-product, pre-revenue, technically differentiated, with the founder's scientific insight being the primary asset.
The important distinction is that you don't want a generic "early-stage VC." You want investors who are comfortable underwriting technical truth before commercial proof.
If your company is genuinely built around a scientific/technical breakthrough, DCVC is one of the first firms I'd approach.
They explicitly describe themselves as deep-tech VC, have more published scientists than MBAs, and invest in areas including AI, biology, climate, robotics, advanced computing, materials and industrial technology.
Their DCVC Bio arm is particularly explicit about backing founders combining fundamental biology/engineering insights with computation.
Best for: hard science, computational science, biotech, climate, robotics, advanced materials, chips/compute, industrial technology.
Scientist-founder friendliness: ★★★★★
Playground may be even more directly aligned with your description.
Their own positioning is essentially: "breakthrough science → company." They say they invest at the earliest stages of company formation and specifically back technical founders in hard science, engineered biology, next-gen compute, automation and energy.
This is exactly the situation where you have:
"We discovered something that shouldn't work according to conventional wisdom, and now we're figuring out what company this enables." rather than:
"We have a product and need capital to scale it." Best for: frontier science, AI/compute, materials, robotics, biotech, energy.
Scientist-founder friendliness: ★★★★★
Khosla is unusually comfortable with high technical risk + enormous potential market.
They explicitly invest from pre-seed/seed through Series A, look for proprietary technological advantages, and describe their strategy as making large, early, sometimes contrarian bets.
Their portfolio gives you a sense of the range: OpenAI, Commonwealth Fusion, QuantumScape, Rocket Lab, Waabi, Field AI, Ultima Genomics, etc.
The particularly relevant signal is their history of backing things that initially looked more like science projects than conventional startups. Their own site highlights Nutanix as a pre-revenue investment and QuantumScape as a company they backed when there were many skeptics.
Best for: ambitious technical breakthroughs where the eventual market could be enormous.
Scientist-founder friendliness: ★★★★★
If your insight requires building something in the physical world, HAX is worth putting high on the list.
HAX explicitly targets pre-seed startups at the intersection of science and engineering, including advanced chemistry, plasma, physical AI, energy, advanced computing, manufacturing, transportation and health tech.
This is particularly attractive if your "pre-product" stage means you need capital to build the first serious prototype, rather than simply needing money to hire a software team.
Scientist-founder friendliness: ★★★★★
I'd put 8VC in the second tier of firms to investigate.
They're particularly interesting when the scientific insight translates into something substantial in bio, defense, industrial technology, mobility, robotics, etc.
The key difference from DCVC/Playground is that I'd want a reasonably compelling hypothesis for how the technology becomes a very large company, even if the product isn't built yet.
Scientist-founder friendliness: ★★★★☆
I'd divide your prospective investors into four buckets:
| VC archetype | What they underwrite | Your situation |
|---|---|---|
| Deep-tech specialists | Scientific/technical breakthrough | 🟢 Excellent |
| Frontier-tech generalists | Technical insight + huge market | 🟢 Excellent |
| Traditional SaaS/consumer VCs | Product + traction + growth | 🔴 Poor fit |
| University/technology commercialization funds | IP + translational path | 🟢 Potentially excellent |
The first two are where I'd spend most of your time.
There's a subtle distinction between "scientist founder" and "scientific insight."
The strongest pitch isn't:
"I'm a scientist who wants to start a company." It's:
"We discovered X, which changes the economics/physics/biology of Y, and if we're right, it makes Z possible." Then show progressively stronger evidence:
Scientific insight → experimental evidence → technical feasibility → wedge → enormous market
At the pre-product stage, you can substitute technical evidence for commercial traction.
For example:
You don't necessarily need revenue. You need to make the VC think:
"If this technical claim is true, I need to own a piece of this company."
That's precisely why DCVC, Playground and Khosla are unusually interesting.
If the technology originated in a university, national lab, or academic research group, don't restrict yourself to conventional VC. Technology-transfer funds, university venture arms, and specialized translational funds can be exceptionally useful at the "turn this discovery into a company" stage.
And if you tell me what the technical insight is (even at a high level), the field (AI/biology/materials/energy/physics/etc.), where you are geographically, and roughly how much you're raising, I can give you a much more targeted 15–25 fund list, ranked by actual fit and including the specific partners I'd approach at each firm.
HAX
hax.co
8VC
8vc.com
