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Madrona is a multi-stage technology investor rooted in the Pacific Northwest and increasingly active across the U.S., especially from Seattle and Palo Alto. The firm is known for partnering from company formation through scale, with a hands-on model built around board partnership, talent access, go-to-market help, and deep ties to the Amazon/Microsoft ecosystem. Today, Madrona is especially focused on AI-native applications, agentic software, and enabling infrastructure where durable workflow and data advantages can be built.

Evaluation weights

How much weight this investor places on each dimension. Totals 100%.

Team-led · 32%
Metrics
12%

Revenue, growth, and unit economics

Market
31%

Size, timing, and competitive landscape

Team
32%

Founder experience and execution ability

Product
25%

Differentiation and technical quality

  • Favors application-layer and agentic AI over direct foundation model bets
  • Comfortable investing early before perfect alignment if founder insight is strong
  • Prefers measurable customer pull over headline ARR milestones
  • Leans into deals where Madrona can take a board role and materially help operationally

Pitch difficulty

How hard it is to get a meeting and close funding from this investor.

Funded / yr
10

Deals closed in a typical year.

Led / yr
15

Rounds led in the last 12 months.

Pitches / yr
~1000

Decks reviewed in a typical year.

Acceptance rate
1.0%

Share of pitches that get funded.

Estimated — public data is not fully disclosed.

Why it's hard
  • Strong preference for clean metrics and real PMF signals
  • Avoids undifferentiated AI/model-layer companies and fragile market positions
  • Often seeks active involvement, including board seats and deep operating partnership
  • Concentrates heavily in sectors and geographies where it has an edge, especially the PNW and AI-driven software

Madrona is accessible across multiple stages and willing to engage early, but it is highly conviction-driven and filters hard on founder quality, metric clarity, and differentiated AI positioning. Their hands-on style, board orientation, and preference for durable product pull make them selective even when they are risk-on.

Green flags

What drives a yes for this investor.

  • Mission-driven founders with strong founder-problem fit
  • Evidence of real product pull through retention, usage, and expansion metrics
  • AI differentiation at the application or workflow layer rather than undifferentiated model exposure
  • Clean, precise metrics and crisp revenue definitions
  • A clear path to product-market fit or visible compounding momentum toward it

Red flags

What kills deals and gets a fast no.

  • Messy or ambiguous KPIs, especially unclear revenue definitions
  • Pilot-driven revenue with weak conversion, retention, or repeatability
  • AI products that are thin wrappers likely to be displaced by foundation model vendors or hyperscalers
  • Growth that depends on heroic sales effort instead of product demand
  • A weak explanation of why this market and team can build a durable company

How to win

Patterns that lead to successful pitches.

  • Show precise retention, usage, expansion, and unit economics rather than relying on ARR alone
  • Position the company in the application, workflow, or enabling infrastructure layer with clear defensibility
  • Demonstrate authentic founder-problem fit and a mission-driven reason for building now
  • Make clear how Madrona's network in Seattle, enterprise GTM, recruiting, or partnerships can accelerate the business
  • Present evidence of compounding product pull from design partners or early customers

Fund strategy & identity

Who they are and how they operate.

  • Invest from Pre-Seed and Seed through Series A, then re-engage at B/C via Acceleration funds
  • Lead or co-lead selectively at early stage and frequently at Series B/C
  • Concentrate capital in AI-native applications, intelligent software, and selective enabling infrastructure
  • Stay heavily involved post-investment on hiring, GTM, partnerships, and future financings
  • Prioritize markets where Madrona's Seattle network and operating support can materially accelerate outcomes
Firm identity
Pacific Northwest-anchored tech investor with national reach Multi-stage firm investing from formation through B/C and growth inflections Hands-on, board-oriented partner from day one for the long run Deeply connected to Seattle's Microsoft/Amazon talent and customer ecosystem Conviction-driven AI investor focused on practical value capture

Investment focus

Industries, themes, and typical ARR expectations.

Industries
Enterprise softwareApplied AI and intelligent applicationsAI infrastructure and data platformsDeveloper tools and low-code/no-codeBiotech and life sciences softwareConsumer applications and marketplaces
Investment themes
AI-native applications and agentic workflowsInfrastructure and data layers that make AI apps usable and reliableApplied AI in enterprise software and intelligent applicationsLow-code/no-code platformsAI-enabled biotech and life sciences toolsNext-generation consumer and social applicationsWorkflow-embedded products with proprietary data or usage moats
Typical check by stage
Pre Seed$0.5M-$2.5M
Seed$2M-$5M
Series A$5M-$10M
Series B$10M-$20M
Series C$15M-$25M
Growth$15M-$35M
Typical ARR by stage
Pre Seed$0
Seed$0-$500K
Series A$0.5M-$3M
Series B$5M-$20M
Series C$20M-$50M
Growth$50M+

Investment thesis

Core beliefs and strategy behind their investing approach.

Madrona is a multi‑stage, tech‑focused firm anchored in the Pacific Northwest with an expanding West Coast/U.S. footprint. Their core belief is to partner “from day one for the long run,” providing hands‑on company‑building support, board partnership, and deep go‑to‑market and talent networks tied to Seattle’s Microsoft/Amazon ecosystem. Sectorally, Madrona has spent more than a decade championing applied AI and “intelligent applications,” and today concentrates on AI‑native applications and agents, the enabling infrastructure/data layers that remove friction between models and users, low‑code/no‑code, AI‑enabled biotech/life‑sciences intersections, and next‑gen consumer apps. They explicitly emphasize value capture “up the stack” (agentic/application layers) versus competing head‑on with foundation‑model leaders, while selectively backing infrastructure that powers AI apps. Stage and geography: With Fund X (early‑stage) and Acceleration Fund IV (B/C), Madrona invests from formation/pre‑seed and seed/Series A through B/C inflection rounds. The firm remains PNW‑centric while investing nationally; it opened a Palo Alto office (2022) and expects the majority of new capital to continue into the Pacific Northwest, leveraging its “Seattle perspective” and relationships with Amazon and Microsoft. What they avoid: While industry‑agnostic across tech, their public commentary suggests they avoid direct model‑layer battles with OpenAI/Anthropic, preferring domain‑specific apps and enabling layers where durable differentiation can be built.

Decision patterns

How they evaluate and make investment decisions.

What makes them invest: (a) mission‑driven founders who deeply understand why a problem exists; (b) clear signals of product‑market fit (PMF) or the path to it; (c) momentum and clean metrics that prove real demand; and (d) markets where AI‑native differentiation (data/workflow moats, agentic UX) can compound. Madrona emphasizes judgment over rigid ARR thresholds—particularly in applied AI. They explicitly state that investors “have stopped caring” about hitting a specific ARR milestone; instead, they underwrite unit economics, retention/usage cohorts, expansion and trajectory. A $500K‑ARR company with crisp pull‑driven data may be more fundable than a $5‑10M‑ARR company with one‑off pilots. Deal‑breakers: ambiguity and imprecise metrics; unclear revenue definitions; stalled or non‑compounding usage; “heroic” sales masking weak product pull; and category positions likely to be disrupted by hyperscalers or foundation‑model vendors. Timing matters—Madrona will often engage early but delay a check until product, team, and market are sufficiently aligned. When they invest, they typically take active board roles and help on hiring, GTM, partnerships, future financing, and customer access—weighting team and market/traction roughly equally, with a premium on evidence of durable pull and differentiated workflows/data. Typical check sizes and ARR/traction at investment (by stage): - Formation/Pre‑seed/Seed: first checks from hundreds of thousands up to several million (≈$0.5‑$8M). Companies can be pre‑revenue; emphasis is on founder/problem fit, early design partners, crisp hypotheses, and speed of iteration. - Series A: No fixed ARR threshold; examples include ~$500K ARR with crystal‑clear unit economics and strong retention/usage, or ~$1M ARR growing 30% MoM beating larger but slower growth. - Acceleration (B/C): Initial checks around $7‑12M, leading or co‑leading with board seats, at strong PMF and an inflection to scale. Lead/follow and board: Frequently lead/co‑lead at B/C and selectively lead early rounds; typically take a board seat and provide full‑stack operational support.

Risk appetite

Madrona blends disciplined early‑stage partnering with a clear “risk‑on” posture in the current AI/innovation cycle. At formation/seed/A, they engage before perfect alignment, often ideating and testing alongside founders—then wait or proceed based on timing and milestone clarity. They are patient and supportive through volatility (e.g., reinvesting through product rebuilds) and maintain significant reserves. At B/C, the Acceleration Funds lean in at growth inflection, often leading or co‑leading and taking/holding board seats. Practically, they lead or co‑lead many B/C rounds and will lead selective early rounds; they are comfortable being highly active but can also collaborate with existing syndicates. Public guidance in 2025 explicitly frames the macro backdrop as “risk‑on,” with internal conversations encouraging “foot on the gas” execution plans for strong companies. Overall, the firm is conviction‑driven but avoids “tourist” risk—eschewing head‑to‑head model wars—preferring agentic/app‑layer differentiation and enabling infrastructure where they can help unlock customers, talent, and partnerships.

Notable investments

Key portfolio companies and why they fit the thesis.

  • SmartsheetLead
    Seattle‑originated no‑code SaaS platform aligns with Madrona’s PNW and intelligent‑applications thesis; Madrona led the Series A in 2007.
  • RedfinLead
    PNW consumer marketplace/proptech; Madrona was the first institutional backer and led early rounds, fitting the “Day One” strategy.
  • ApptioLead
    Enterprise B2B SaaS from the Seattle region; Madrona co‑led the 2007 Series A, reflecting its focus on cloud‑infrastructure software.
  • RoverLead
    Seattle‑based pet‑care marketplace incubated by Madrona; Madrona led the 2012 Series A, matching its consumer‑marketplace focus.
  • OctoMLLead
    University of Washington spin‑out for ML model optimization; Madrona led the seed round, fitting its AI/ML and intelligent‑applications emphasis.
  • Turi (formerly GraphLab)Lead
    Foundational horizontal ML platform with UW roots; Madrona co‑led the Series A, aligning with its AI infrastructure thesis.
  • SeekOutLead
    Seattle‑area AI‑powered talent platform; Madrona led the Series A, reflecting its applied‑AI and local‑founder focus.
  • Crowd CowLead
    PNW‑based marketplace for premium meat; Madrona led the 2018 Series A, consistent with its consumer‑commerce thesis.
  • The RiveterLead
    Seattle‑based women‑focused co‑working platform; Madrona led the seed round, matching its support for local, mission‑driven founders.

Key people

Partners who lead investments and shape the thesis.

  • MM
    Matt McIlwain
    Managing Director
    Intelligent applicationsCloud infrastructureML/AI
  • SS
    S. Somasegar
    Managing Director
    Developer toolsCloudAI
  • KM
    Karan Mehandru
    Managing Director
    SaaSData infrastructureSecurityCloud computingIntelligent applications
  • TP
    Tim Porter
    Managing Director
    B2B softwareIntelligent applicationsSaaS
  • SS
    Steve Singh
    Managing Director
    Next-gen B2BEnterpriseMachine learning / AIIntelligent applicationsNext-gen cloud infrastructure
  • SJ
    Scott Jacobson
    Managing Director
    MarketplacesConsumer techProptechDigital commerce

Public voice

Notable statements and public positions.

  • “We think a lot of the value is going to be captured in the agentic and application layers.” — Matt McIlwain to GeekWire (on AI investment focus)
  • “Investors have stopped caring whether you hit a specific ARR milestone. They care whether your metrics prove that customers need what you’re building.” — Madrona, “Fundraising in the AI Era”
  • “We are looking to lead rounds, partner with your existing investors and roll up our sleeves as a team to have a positive impact on your company’s trajectory.” — Madrona, Acceleration Fund page