Deep-tech ventures generally need more patient financing and face longer, less predictable intervals between funding rounds than software startups. The OECD’s 2026 financing report, attributing its underlying statistic to BCG (2023), says deep-tech ventures take an average of 25–40% longer between funding stages than other technology firms—and face higher failure risks at each stage. That is a comparison of fundraising intervals, not a forecast of total time to revenue or a prediction for any one company.
Software is often easier or faster to commercialize, but it is not automatically inexpensive, low-risk, or quick to profitability. The practical difference is usually what a company must prove, how long proof may take, and whether its financing can last until the next credible milestone.
What counts as deep-tech—and what does not
Deep-tech is a broad category for ventures built around substantial scientific or engineering advances, including key enabling technologies and strategic sectors. Software startups span just as wide a range of business models, markets, and operating costs. The useful comparison is therefore between common development and financing patterns, not between two fixed types of company.
A software company serving a regulated market or running expensive infrastructure can require substantial capital. A deep-tech venture may secure an early commercial contract and move faster than its technical roadmap initially suggested. Category-level findings describe tendencies; they are not individual-company forecasts.
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How funding needs differ
Deep-tech: finance development before conventional traction
Deep-tech ventures may need external capital through extended periods of technology development and commercialization, before revenue or familiar growth measures can demonstrate progress. The World Bank’s 2021 report describes a shortage of early-stage specialist deep-tech capital and barriers for generalist investors, including limited in-house technical expertise. It also notes that intellectual property can be difficult to value before revenue, while metrics such as revenue growth and customer acquisition cost may not yet be meaningful.
This can create a financing gap: a venture needs money to develop and validate its offering, but has not yet produced the commercial evidence many investors typically assess. Technical uncertainty and intangible assets can make that gap harder to bridge.
Software: potentially faster commercialization, but no universal cost advantage
The OECD says information and communications technology businesses—particularly software companies—are often easier or faster to commercialize and face relatively low demand uncertainty. That tendency can let some software ventures test customer demand and develop commercial traction earlier. It does not establish that every software startup is cheap to build, easy to scale, or fast to reach product-market fit. Product development, hiring, customer acquisition, infrastructure, and expansion can still require significant financing.
Why a single funding target is misleading
The cited sources do not establish a universal funding amount for either category. A useful estimate must reflect the venture’s technical and commercial milestones, development costs, market, and expected time until it can raise again or generate revenue. Comparing two companies by headline dollars alone obscures what each must accomplish before the next financing decision.
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How long between funding rounds?
The clearest quantitative comparison is the OECD’s 2026 report: deep-tech ventures take an average of 25–40% longer between funding stages than other technology firms. The OECD attributes this figure to BCG (2023). It is an average difference in the interval between stages—not an estimate in months or years, a measure of total company lifespan, or a time-to-revenue benchmark.
That longer interval reflects a more difficult path to evidence. A deep-tech company may need to show both that its technology works and that a market wants the resulting product. As the World Bank put it in its 2021 report, “Development timelines for deep tech are less predictable than for other start-ups.” Several components may need to work together before a company can demonstrate the performance, customer traction, or revenue that investors expect.
Software may reach commercial testing sooner, but the sources do not give a like-for-like estimate of total time to revenue for software and deep-tech startups. Nor do they establish a fixed deadline by which either type should raise its next round. Founders should build a timeline from company-specific milestones rather than turn the average interval difference into a calendar forecast.
Where the risks come from
Technical and commercial proof may have to advance together
Deep-tech founders can face a “double unknown”: whether the technology can meet its performance goals and whether customers will adopt the product. A technically successful prototype does not by itself establish product-market fit; early customer interest does not prove that the underlying system can work reliably at commercial scale. When several technical components depend on one another, a delay in one can hold up the broader demonstration.
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Investment evidence may arrive late
Before revenue, deep-tech ventures may have less access to the standard commercial measures investors use to judge progress. Investors may need to evaluate technical milestones, intellectual property, contracts, and other evidence instead. The World Bank’s 2021 analysis says generalist investors can be disadvantaged when they lack the technical expertise to assess those claims, while specialist capital is limited.
Higher reported failure risk is not a company-specific probability
The OECD report says deep-tech ventures face higher failure risks at each funding stage than other technology firms. The cited evidence does not provide a like-for-like failure-rate percentage, so it cannot tell a founder the probability that a particular startup will fail. It does support treating stage-to-stage financing as less predictable, especially when technical validation and commercial evidence are both still outstanding.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which financing approaches may fit?
No financing instrument is right for every startup. The fit depends on eligibility, geography, control and dilution, investor expertise, and the milestone the money must fund.
| Financing approach | Potential role | What to weigh |
|---|---|---|
| Venture capital | Can provide financing alongside investor expertise and networks. | Assess whether the investor understands the technology and can support the venture’s time horizon and evidence needs. |
| Grants and other public support | Can support innovation or development without being the same as conventional equity financing. | Eligibility and availability vary; a grant is not a dependable funding source until awarded. |
| Public participation or public-private co-investment | Governments use these approaches to mobilize patient capital in strategic sectors, according to the OECD’s 2026 report. | Programs are sector- and jurisdiction-dependent; policy examples do not establish that a particular startup can access them. |
| Longer-horizon or evergreen capital | May better match ventures whose development and commercialization milestones take longer. | Confirm the investor’s actual time horizon, terms, and expectations rather than relying on the label. |
| Corporate partnerships | May connect a venture with an industry partner, potential application, or commercial opportunity. | Consider strategic fit, partnership terms, and whether the arrangement supports or constrains the company’s plans. |
| Hybrid capital, venture debt, or venture equity | A 2018 European Commission study recommended financing instruments adapted to deep-tech risk, including these forms. | They have different repayment, dilution, and risk profiles; the study’s recommendation is not a universal prescription. |
These approaches can be combined, but they are not interchangeable. Financing should match the work ahead and the evidence a funder can evaluate—not just the startup’s label.
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- Define the milestone the financing must buy. Specify the technical result, customer validation, contract, or other evidence the company expects to deliver.
- Map dependencies and uncertainty. Identify which technical components must work together and which commercial assumptions still need testing. Include the possibility that one delay affects other milestones.
- Choose investors and instruments for the evidence available. A specialist investor may be better placed to assess technical progress; grants, public co-investment, corporate partnerships, or longer-horizon capital may also be relevant where available and suitable.
- Build the financing timeline around company-specific needs. The 25–40% average difference between deep-tech and other technology funding-stage intervals is context, not a substitute for a development plan or fundraising schedule.
- Check investment readiness as the company develops. The OECD’s incubation report identifies technological readiness, product-market fit, sales history, and management competencies as factors that inform investment readiness.
The key planning question is: what credible technical and commercial evidence can the next round finance, and can the company reach it before its capital runs short?
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