Cortical Ventures is an AI-first early-stage venture firm focused on production-grade AI systems, core infrastructure, and real-world deployments rather than hype-driven demos. The firm leads pre-seed and seed rounds for deeply technical teams building across physical AI, AI infrastructure, and mission-critical applications in areas like defense, health, safety, and enterprise workflows.
Evaluation weights
How much weight this firm places on each dimension. Totals 100%.
Revenue, growth, and unit economics
Size, timing, and competitive landscape
Founder experience and execution ability
Differentiation and technical quality
- Strong bias toward technical founders over commercial-only teams
- Prefers production evidence over narrative ambition
- More receptive to AI infrastructure and physical AI than consumer AI hype
- Comfortable with frontier and regulated markets if execution quality is exceptional
Pitch difficulty
How hard it is to get a meeting and close funding from this firm.
- Funded / yr
- 2Deals closed in a typical year.
- Led / yr
- 2Rounds led in the last 12 months.
- Pitches / yr
- ~156Decks reviewed in a typical year.
- Acceptance rate
- 1.3%Share of pitches that get funded.
Estimated — public data is not fully disclosed.
Why it's hard
- Strong preference for deeply technical, operator-grade founding teams
- Rejects hype-driven or demo-only AI startups
- Concentrated focus on AI infrastructure, physical AI, and mission-critical applications
- Often seeks to lead rounds, which raises the conviction threshold
Cortical is aggressive at the earliest stages and willing to underwrite meaningful technical risk, but its bar is high on founder quality and production credibility. It is not broad-based or theme-agnostic; companies need to fit a specific AI-first, execution-heavy thesis to win conviction.
Green flags
What drives a yes for this firm.
- Deeply technical, operator-grade founders with strong AI credibility
- Clear path from prototype to production with tangible deployment evidence
- Potential to become foundational infrastructure or a category leader in the AI stack
- Mission-driven use case with real-world urgency, especially in defense, safety, or health
- Proof that the product works beyond a demo via contracts, OSS pull, pilots, or revenue
Red flags
What kills deals and gets a fast no.
- Pitching a flashy AI demo without a credible production roadmap
- Founding team lacks substantive AI or systems depth
- Generic LLM wrapper with weak differentiation or no defensibility
- No evidence of customer pull, deployment, or practical commercialization
- Hype-first storytelling that substitutes for execution details
How to win
Patterns that lead to successful pitches.
- Show technical founder credibility and why this team can ship production AI
- Lead with deployment proof: pilots, contracts, OSS adoption, or early revenue
- Position the company as infrastructure or a deeply embedded workflow/system, not a novelty app
- Demonstrate reliability, security, and real-world readiness in demanding environments
- Frame the opportunity around meaningful impact plus venture-scale market potential
Fund strategy & identity
Who they are and how they operate.
- Lead or co-lead Pre-Seed and Seed rounds in AI-native companies
- Back production-grade AI infrastructure and vertical systems with strong technical moats
- Underwrite technical and go-to-market risk for exceptional operator-founders
- Prefer companies with evidence of deployments, contracts, OSS adoption, or early revenue
- Make selective follow-on investments in later-stage category-defining AI platforms
Firm identity
Investment focus
Industries, themes, and typical ARR expectations.
Industries
Investment themes
Typical check by stage
Typical ARR by stage
Investment thesis
Core beliefs and strategy behind their investing approach.
Cortical Ventures is an AI‑first venture firm that backs founders building production‑grade artificial‑intelligence systems and the infrastructure that powers them. Its thesis revolves around three pillars: Physical AI – embedding intelligence in robotics, autonomy and defense hardware; the AI Production Gap – tools, pipelines and vertical applications that bridge proof‑of‑concept demos to scalable, revenue‑generating products; and AI for Good – applying AI to health, safety, defense and human connection. The firm believes value accrues to teams that can ship reliable AI in real‑world environments and therefore leads early‑stage rounds where its operating expertise can accelerate productization. It actively avoids hype‑driven, demo‑only startups and de‑prioritises non‑technical founders unless paired with deep AI talent. Geographically, Cortical is US‑centric (San Francisco/Boston) but will follow talent and market opportunities globally, especially in Europe. Core belief: operators who can move AI from lab to market create the strongest, defendable businesses.
Decision patterns
How they evaluate and make investment decisions.
Cortical invests when it sees (1) operator‑grade founders with deep technical expertise and a mission‑driven mindset; (2) clear production pathways – evidence of deployments, contracts, OSS adoption or early revenue; and (3) platforms that can become category‑level AI infrastructure. Deal‑breakers include hype‑only or demo‑only AI projects and teams lacking substantive technical depth; non‑technical founders are deprioritized unless paired with strong AI co‑founders. The firm weights team quality and production readiness highest, using market size and traction as secondary validators. Examples include co‑leading Weaviate’s Series A after strong open‑source adoption, leading Spear AI’s seed round backed by a $6 M Navy contract, and backing HyperWrite’s seed extension citing rapid user and revenue growth. While preferring to lead early rounds, Cortical will follow on in later strategic financings when a platform proves critical to the AI stack.
Risk appetite
Cortical adopts a high‑conviction, aggressive stance at the earliest stages, routinely leading or co‑leading pre‑seed and seed rounds. It is comfortable underwriting technical and go‑to‑market risk for operator‑grade founders, even in regulated or frontier domains such as defense. The firm’s typical initial checks range from $500 K to $2 M (occasionally up to $3 M) and it prefers to set terms rather than follow other investors. At later stages it acts more selectively, participating in strategic follow‑on rounds for category‑defining infrastructure companies, reflecting a barbell risk profile – front‑loaded early‑stage exposure with opportunistic later‑stage bets.
Notable investments
Key portfolio companies and why they fit the thesis.
- Weaviate (SeMI Technologies)LeadCore AI infrastructure (vector database) powering semantic search and AI-native apps, addressing the AI production gap. Cortical led the Series A.
- Angel AILeadAI for Good – a safer internet platform for children, aligning with the firm's societal-impact focus. Cortical led the seed round.
- Spear AILeadPhysical AI/defense tech intersection; operational AI on maritime sensor data. Cortical co-led the seed round with Scare the Bear Capital.
- OthersideAI (HyperWrite)LeadVertical AI assistant/productivity application with strong user growth. Cortical co-led the $2.8M round with Active Capital.
- RupertLeadEnterprise analytics platform that turns insights into actions, an AI-first enterprise software aligning with the firm's focus.
- ImmerokReal-time stream-processing infrastructure enabling AI/ML data pipelines, supporting the AI production gap.
- NeoCyberneticaPhysical AI and autonomous systems for robotics, matching the firm's Physical AI area.
- FAL.aiServerless GPU/AI infrastructure for model inference and deployment, addressing the AI production gap.
- Integration.app (Membrane)LLM-powered integrations platform enabling agentic workflows, fitting the AI production gap thesis.
- DataroomHQOperational metrics automation for SaaS with AI-enabled enterprise workflow, aligning with the firm's focus on production-ready AI.
Co-invested with
Other firms in this catalog who've backed the same companies.
No catalog overlap found yet. Co-investors are derived from each firm's notable investments — connections may surface as more firms are added.
Partners
Full firm roster — key partners, partners, and the wider team.
Key partners
Jeremy Achin
General Partner
Cortical Ventures
Jeremy Achin is a General Partner at Cortical Ventures and co-founder of DataRobot, with a background in building applied AI companies.
Igor Taber
General Partner
Cortical Ventures
Igor Taber is a General Partner at Cortical Ventures, an AI-focused early-stage firm, with prior public background connected to DataRobot and Intel Capital.
Mike Obolonskyi
Principal
Cortical Ventures
Mike Obolonskyi is listed in public sources as a Principal at Cortical Ventures focused on AI and robotics. Cortical Ventures describes itself as an AI-focused venture firm interested in areas including AI pipelines, agentic infrastructure, vertical AI-first workflows, AI-driven human engagement, and defense tech.
Sheamus McGovern
Venture Partner
Cortical Ventures
Sheamus McGovern is a Venture Partner at Cortical Ventures and is publicly associated with AI, data science, and AI community-building through ODSC AI. Public sources describe him as founder of ODSC AI and Head of AI at Cortical Ventures.
Public voice
Notable statements and public positions.
- “We create AI impact, not hype.” – Cortical Ventures website
- “Vision without execution is hallucination.” – Jeremy Achin, launch announcement
- “I believe the best companies to invest in operate at the intersection of opportunities to (a) save the world and (b) generate significant returns.” – Jeremy Achin, speaking about Spear AI
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