Mapping Deep Tech ecosystems to guide Intel's Deep Tech bets

4

ECOSYSTEMS BENCHMARKED

5

YEARS OF ECOSYSTEM PERFORMANCE TRENDS

15+

SUB-SECTORS MAPPED

Challenge: Locating the next Deep Tech bet

Intel’s Deep Tech accelerator program had built proven traction in key markets and was preparing to expand. With sites under consideration on both sides of the Atlantic, leadership needed a defensible answer to a high-stakes question: where do you build the next program, and what makes one Deep Tech ecosystem a better bet than another?

Intuition pointed in obvious directions: Boston for Life Sciences, New York for scale, London for talent depth. But Intel's leadership wanted empirical clarity down to the zip codes, not received wisdom. The team needed to compare different areas of Boston, NYC, and the London–Cambridge corridor on the metrics that actually matter to a Deep Tech program: ecosystem growth, founder quality, sub-sector funding density, accelerator competition.

Solution: Data-driven Deep Tech ecosystem benchmarking

Startup Genome conducted a structured four-step assessment to inform Intel’s location decision. We benchmarked Boston, New York, Cambridge, and London across global ecosystem performance, differentiated each city's Deep Tech vs. broader tech profile, and drilled into sub-sector performance in the verticals most relevant to Intel: Semiconductors, Quantum Computing, AI & Big Data, and Enterprise Software.

The analysis combined five years worth of ecosystem data, including startup creation, attrition funnels, venture funding performance, and accelerator-vs.-output density ratios to surface a single comparable view across the four ecosystems. We also mapped sub-sector concentrations within each city so Intel could pinpoint exactly where to plant a program. Not just which city, but which corner of it.

Highlights

4

Ecosystems Benchmarked

15+

Sub-Sectors Mapped

80+

Funding Metrics Analyzed

QUOTE

Marc Penzel, Founder & President, Startup Genome

Corporate accelerators often succeed or fail on location, talent depth, and sub-sector fit. We brought Intel a data-grounded view of four very different Deep Tech ecosystems so the team could quickly move from intuition to a defensible call on where to build next.

Heartbeat of the project:

Location Analysis

Ecosystem Lifecycle Model

Positioned each ecosystem within the Startup Genome Lifecycle Model to compare maturity profiles across Boston, NYC, Cambridge, and London.

Voice of the Entrepreneur Insights

Captured Deep Tech founder maturity signals — round sizes, attrition funnels, time between rounds — to surface where serious Deep Tech founders cluster.

Startup DNA Assessment

Profiled each ecosystem's tech vs. Deep Tech composition and the sub-sector mix that fit Intel's strategic priorities.

Global Benchmarking & Sub-Sector Strengths

Compared the four ecosystems across 15+ sub-sectors and five years of funding data, surfacing where Life Sciences, Quantum, AI, and Semiconductor startups cluster.

Best Practice Recommendations

Delivered comprehensive recommendations that informed Intel’s location decision strategy

Assessment results:

Examples of uncovered insights

Cambridge's Deep Tech success paradox

Despite being the smallest of the four ecosystems by raw startup count, Cambridge posted the highest attrition-funnel success rates and the fastest year-over-year growth in startup creation. The success funnel, built from round-by-round funding data, revealed Cambridge as a high-quality, low-volume Deep Tech bet.

Sub-sector dollars cluster sharply

Life Sciences and Quantum Computing funding concentrated in Boston, while Fintech captured the largest share of dollars in NYC and London. The pattern emerged from analyzing dollar amounts invested by sub-sector across all four ecosystems over five years, making each city's strategic specialism legible at a glance.

Accelerator competition runs counter to size

Boston, NYC, and London each had between 9.6 and 11 startups available per accelerator program per year. Cambridge, the smallest ecosystem, had the most intense competition for applicants, a counter-intuitive finding from cross-referencing accelerator counts with annual startup-output figures.

Key Takeaways

Deep Tech rewards quality over volume

Headline startup counts favor the largest cities, but Deep Tech accelerators succeed or fail on funnel quality, round sizes, attrition rates, founder maturity. Smaller ecosystems like Cambridge can outperform on the metrics that actually matter to a hardware or Life Sciences program.

Sub-sector geography beats headline numbers

Aggregate ecosystem rankings flatten the differences that matter to a corporate accelerator. Funding-by-sub-sector and startup-by-sub-sector views surface where Life Sciences, Quantum, AI, or Semiconductors actually cluster and where they don't. Strategic location decisions live at this level.

Corporate programs need their own benchmark

Generalist ecosystem rankings can't determine where corporations should put their next specialized startup programs. That decision needs metrics built for the questions: funnel quality in your sub-sectors, accelerator-to-startup ratios, and where the founders you want to recruit already live.

Curious how these insights could apply to your ecosystem?

Every success starts with a deep understanding of local context and a commitment to measurable outcomes. Let’s explore how we can collaborate on a similar project.