Deep technology companies, those building on novel science or fundamental engineering advances in areas like advanced materials, quantum computing, synthetic biology, novel therapeutics, photonics, or next-generation manufacturing, face a capital challenge that is structurally different from software startups. The time from initial scientific insight to first commercial revenue is measured in years, not months. The milestones that matter to scientific progress do not map neatly onto the milestones that matter to financial investors. And the risk profile of the company at the seed stage is a blend of scientific risk, engineering risk, regulatory risk, and commercial risk that most venture investors are poorly equipped to evaluate.
At Curevstone Capital, we have invested in deep tech companies across several of these domains and have developed a framework for thinking about deep tech capital management that we believe is materially different from the standard software startup playbook. This article shares that framework in detail, with the goal of helping deep tech founders think more clearly about how to extend their runway, structure their fundraising, and communicate their progress to investors who think in financial rather than scientific terms.
Understanding Technology Readiness Levels and Why Investors Care
The Technology Readiness Level (TRL) framework, originally developed by NASA and now used broadly across government research programs and defense procurement, provides a nine-level scale for describing the maturity of a technology from basic research (TRL 1) through system demonstration in an operational environment (TRL 9). It has become a valuable communication tool between deep tech founders and financial investors precisely because it provides a shared vocabulary for describing where a technology sits in its development arc.
At TRL 1 through 3, the technology exists as a scientific concept or a laboratory demonstration of basic principles. At TRL 4 through 6, it has been demonstrated as a working prototype in a relevant environment. At TRL 7 through 9, it is approaching or has achieved operational deployment. The progression from TRL 1 to TRL 9 is not linear in either time or capital requirements: the jump from TRL 5 to TRL 7, demonstrating a system prototype in an operational environment, is often the most capital-intensive and time-consuming phase and is sometimes called the "valley of death."
Seed-stage deep tech companies typically sit between TRL 3 and TRL 5. They have demonstrated that the underlying science works, at least in controlled laboratory conditions, and they are working toward a prototype that can be evaluated in conditions that approximate real-world use. This is a stage where scientific risk is declining but engineering risk is rising, and where the capital requirements begin to grow substantially.
When communicating progress to financial investors, founders should map their milestones explicitly onto the TRL scale and articulate what each TRL advancement requires in terms of capital, time, and specific technical achievements. Investors who do not have a scientific background can understand "we need $3M and 18 months to move from TRL 4 to TRL 6, at which point we can conduct a pilot with our first customer" far better than they can understand a technical description of the specific experiments required.
Milestone-Based Fundraising: Structuring Capital Raises Around TRL Gates
The most effective capital management strategy for deep tech companies is to structure each fundraising round around a specific TRL gate: a clearly defined technical milestone whose achievement both demonstrates meaningful de-risking of the scientific or engineering thesis and creates a credible inflection point in the company's valuation story.
This approach has several advantages. It forces the founding team to think clearly about what they are actually trying to prove with each tranche of capital, rather than raising as much money as possible and spending until it runs out. It creates a natural alignment with investors, who can see a clear map from current state to future milestone and can evaluate whether the proposed capital is sized appropriately for the work required. And it creates a fundraising cadence that makes the next round's story easier to tell: "We said we would achieve X with this capital. We achieved X. Now we are raising to achieve Y, which will allow us to do Z."
The critical discipline in milestone-based fundraising is realistic milestone setting. Founders have a natural tendency to be optimistic about their technical timelines, to underestimate experimental failure rates, and to assume that access to equipment, collaborators, and specialized materials will be straightforward. A milestone that is set realistically with 80% probability of achievement in 18 months is far better for the company than a milestone set at 50% probability in 12 months. Missing milestones is one of the fastest ways to destroy investor confidence in deep tech companies.
We recommend that founders build their technical roadmap with explicit best-case, expected-case, and risk-adjusted case timelines, and that they raise capital sized for the expected-case timeline with a buffer for the risk-adjusted case. Raising capital that only covers the best-case timeline is a common and costly mistake.
SBIR and STTR: Non-Dilutive Capital That Most Founders Underutilize
The Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs provide non-dilutive grant funding to small businesses engaged in research and development with commercial potential. In aggregate, the federal government distributes approximately $4 billion per year through these programs across eleven participating agencies, including the Department of Defense, the National Institutes of Health, the Department of Energy, NASA, and the National Science Foundation.
For deep tech founders, SBIR and STTR grants are among the most underutilized capital resources available. A Phase I SBIR award, which supports feasibility studies, is typically $150,000 to $300,000. A Phase II award, which supports prototype development, is typically $750,000 to $2,000,000. Department of Defense SBIR programs have somewhat higher ceilings than civilian agency programs. These are real amounts of capital that, if pursued strategically, can meaningfully extend runway and reduce dilution.
The primary obstacle to SBIR/STTR utilization is the application process, which is substantial and requires specific expertise in government grant writing. The application timeline from submission to award notification is typically six to twelve months, which means a seed-stage company needs to begin the SBIR process earlier than most founders anticipate. The proposal must demonstrate both scientific merit, evaluated by program officers with domain expertise, and commercial potential, evaluated separately.
The most effective approach is to identify, early in the company's development, the specific government agencies whose mission areas align with the company's technology. A synthetic biology company with defense applications should be tracking DARPA, Army Research Laboratory, and Air Force Research Laboratory SBIR solicitations. A medical device company should be tracking NIH SBIR opportunities. Each agency publishes annual solicitations with specific topic areas, and matching your technology to the most relevant topic area is critical to a successful application.
SBIR/STTR awards also have significant secondary benefits beyond the direct capital. An SBIR award from a credible agency is a meaningful third-party validation signal for private investors. It demonstrates that domain experts with technical depth have reviewed and endorsed the scientific merit of the approach. For founders who are pitching to investors who lack the technical background to evaluate the science directly, an SBIR award can be a powerful credibility signal.
Spinning Out of Academia: Getting the IP Assignment Right
A significant proportion of deep tech startups originate as academic research projects before being commercialized through a spin-out. The process of spinning out from a university research institution involves navigating technology transfer offices, licensing agreements, and IP ownership arrangements that can create lasting complications if not handled correctly from the start.
The foundational issue is that universities typically own the intellectual property developed by their faculty, staff, and students using university resources or as part of university-funded research. When a founding team spins out of a university, the core technology is usually owned by the university and must be licensed or assigned to the startup. The terms of that license, its scope, exclusivity, royalty structure, field of use, and sublicensing rights, shape the startup's IP position for its entire life as a company.
Exclusive licenses are generally preferable to non-exclusive licenses for foundational technology, as they prevent the university from licensing the same IP to competitors. Field of use restrictions limit the license to specific applications, which can be appropriate if the technology has multiple commercial applications and the university wants to pursue licensing in other fields separately, but which can become constraining if the company's commercial strategy evolves. Royalty structures tied to revenue can create significant cash flow burdens for companies that are pre-revenue for extended periods; milestone-based payments or equity-in-lieu-of-royalties arrangements are often more startup-friendly.
We strongly recommend that founding teams working through a technology transfer process engage independent IP counsel with specific experience in academic spin-outs, not the university's counsel, which represents the university's interests rather than the founders'. The negotiation is not adversarial, and most technology transfer offices genuinely want to see their spin-outs succeed, but the interests are not identical, and having independent representation ensures that the founders understand what they are agreeing to.
IP Strategy: Building a Portfolio, Not a Single Patent
Seed-stage deep tech founders often have a single core patent or patent application that they treat as the company's primary IP asset. This is insufficient. A single patent, no matter how strong, can typically be designed around by well-resourced competitors. A robust IP strategy builds a portfolio of patents that cover the core technology, the manufacturing process, specific applications, and key improvements, creating a thicket that is difficult to navigate around.
The decision of what to patent and what to protect as trade secret requires careful analysis. Patents provide a time-limited monopoly in exchange for public disclosure of the invention. Once the patent is filed, the underlying technology is disclosed to the world, including to competitors who will study it carefully. Trade secrets provide indefinite protection but require rigorous operational security and are lost if the information becomes public through any means.
For deep tech companies, the most valuable IP assets often include not just the core inventions but the know-how required to replicate them: the specific parameters, the failure modes, the manufacturing processes, and the calibration methods that are not fully captured in patent claims. This know-how can be protected as trade secret even as the underlying inventions are patented, creating a layered protection strategy.
International patent protection is a question that seed-stage founders frequently defer due to cost. Filing PCT (Patent Cooperation Treaty) applications buys time, typically 30 months from the priority date, to make decisions about national phase entries in specific countries without incurring the full cost of international patent prosecution upfront. For deep tech companies with global commercial ambitions, at least a PCT filing is advisable even at the seed stage.
Identifying and Securing the First Commercial Beachhead
One of the most common strategic errors in deep tech company building is attempting to pursue multiple commercial applications simultaneously during the development phase. The scientific capability may indeed have multiple applications, and it is tempting to pursue all of them to reduce the risk of any single application failing to materialize. In practice, this approach disperses focus, makes product development decisions more ambiguous, and makes the company's story harder to tell to both investors and customers.
A better approach is to identify a single commercial beachhead: the application that has the shortest path to commercial deployment, the most receptive initial customer segment, and the best unit economics at scale. The beachhead does not need to be the company's largest long-term market opportunity. It needs to be the application that gets the company to revenue fastest with the least additional development, enabling the virtuous cycle of customer feedback, product improvement, and revenue that funds continued development toward larger applications.
Choosing the right beachhead requires honest analysis along several dimensions. Which application has the least regulatory risk? Which application has the most active customer engagement today? Which application has the most favorable competitive dynamics? Which application can be demonstrated with the prototype that will exist in 12 months rather than the one that requires three more years of development? The answers to these questions frequently converge on a beachhead that is smaller and less glamorous than the primary long-term vision, but which provides the operational and financial foundation needed to reach that vision.
Communicating Scientific Risk to Financial Investors
One of the persistent challenges for deep tech founders raising capital from generalist venture investors is translating scientific risk into a language that financial investors can evaluate and are willing to price. Investors who are accustomed to backing software companies where the primary risk is market risk and execution risk are poorly calibrated for evaluating the probability that a specific materials science hypothesis will be validated at scale.
The most effective approach we have seen is to frame scientific risk in terms of the specific experiments or demonstrations that will de-risk each component of the technical thesis, the cost of those experiments, and the time required. This translates scientific uncertainty into a capital deployment schedule with clear decision points. An investor does not need to understand the physics of solid-state batteries to understand "we need $2M and 18 months to determine whether our cathode material achieves the ionic conductivity targets required for our first product specification, and we will know with high confidence within 24 months whether the underlying hypothesis is correct."
It is also important to be explicit about the failure modes. What happens to the company if the primary technical hypothesis is wrong? Are there adjacent applications or alternative technical approaches that the company would pivot to? A company whose entire value thesis depends on a single scientific bet that has a 30% probability of success is a fundamentally different investment than one where the core technology has multiple alternative paths to commercial application. Making this analysis explicit builds credibility with sophisticated investors.
Corporate VC Partners: Strategic Capital at the Right Stage
Corporate venture capital arms of large strategic companies can be valuable capital partners for deep tech companies at the right stage, and expensive strategic entanglements at the wrong stage. Understanding this distinction is important.
The right stage for corporate VC engagement is typically after the technology has been demonstrated at a meaningful scale, after the company has a clear commercial application in view, and after the founding team has sufficient independent capital to negotiate from a position of strength rather than desperation. Corporate VCs invest with both financial and strategic objectives, and their strategic objectives, which may include access to the technology, commercial partnership rights, or simply competitive intelligence, can create conflicts with independent financial investors if not managed carefully.
The most valuable corporate VC partners bring not just capital but customer access, regulatory expertise, manufacturing partnerships, and distribution channels that are genuinely difficult to access through other means. A semiconductor company with a manufacturing relationship is more valuable to a photonics startup than a pure financial investor of equivalent size. A major pharmaceutical company with a clinical development infrastructure is more valuable to a therapeutic company than cash alone.
The key contractual provisions to scrutinize in corporate VC term sheets include right of first refusal on commercial agreements, exclusivity provisions that limit the company's ability to work with the corporate investor's competitors, and any provisions that give the corporate investor visibility into the company's technology roadmap or customer relationships beyond what is appropriate for a financial investor.
Time-to-Revenue Management: The Bridge from Science to Business
The single most important financial management discipline for deep tech companies is managing the gap between when capital runs out and when revenue begins. This gap, sometimes referred to as the funding valley, is where most deep tech companies fail, not because the science did not work, but because the company ran out of money before it could demonstrate commercial viability.
Managing time-to-revenue requires a continuous and honest assessment of three variables: the current burn rate and its trajectory, the current cash position, and the expected time to the next significant capital event, whether that is a revenue milestone, a grant award, or a new financing round. Founders who know these three numbers at all times, and who have a clear plan for what happens if any of them diverges from the expected trajectory, are in a fundamentally better position than founders who discover a problem when the bank account is nearly empty.
Deep tech companies that survive their first decade almost invariably do so through a combination of scientific rigor, financial discipline, and the creative use of every non-dilutive capital source available. The founders who treat capital management as seriously as they treat technical development are the ones who live to see their technology reach the world.
Specific tactics for extending runway include converting full-time personnel costs to part-time or consulting arrangements for non-core functions during capital-constrained periods, aggressively pursuing SBIR and other government grants as noted above, structuring customer pilots to include funded feasibility studies rather than providing development services for free, and using shared laboratory infrastructure, national laboratory user facilities, and university equipment access to reduce capital equipment costs.
The deep tech companies that succeed do so because their founders understand that they are building on a longer timeline than software companies, and they structure their organizations, their capital strategy, and their milestone architecture accordingly. The most dangerous cognitive error is comparing yourself to a software company's fundraising cadence or milestone progression. You are building something fundamentally harder, on a fundamentally longer timeline, and the capital strategy must reflect that reality from the first day of operation.