Cortical Ventures

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 investor places on each dimension. Totals 100%.

Team-led · 42%

Metrics

Revenue, growth, and unit economics

Market

25%

Size, timing, and competitive landscape

Team

42%

Founder experience and execution ability

Product

28%

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 investor.

Funded / yr

Deals closed in a typical year.

Led / yr

Rounds led in the last 12 months.

Pitches / yr

~1400

Decks reviewed in a typical year.

Acceptance rate

0.57%

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 investor.

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

AI-first specialist investor Early-stage lead or co-lead Operator-led and execution-oriented Production-over-hype conviction US-centric with selective global reach

Investment focus

Industries, themes, and typical ARR expectations.

Industries

Artificial intelligence infrastructureDeveloper tools and data infrastructureRobotics and autonomyDefense and security technologyEnterprise AI softwareHealthcare and safety-focused AI

Investment themes

Physical AI across robotics, autonomy, and defense hardwareThe AI production gap: tools and pipelines that move models into reliable productionCore AI infrastructure including compute, vector databases, agent sandboxes, and data pipelinesEnterprise AI applications embedded into real workflows rather than standalone demosAI for Good in defense, safety, health, and human connectionMission-critical systems operating in regulated or real-world environments

Typical check by stage

Pre Seed$500K-$1M

Seed$1M-$2M

Series A$1M-$3M

Typical ARR by stage

Pre Seedpre-revenue or pilots

Seed$0-$1M

Series A$1M-$5M

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)Lead
Core AI infrastructure (vector database) powering semantic search and AI-native apps, addressing the AI production gap. Cortical led the Series A.
Angel AILead
AI for Good – a safer internet platform for children, aligning with the firm's societal-impact focus. Cortical led the seed round.
Spear AILead
Physical AI/defense tech intersection; operational AI on maritime sensor data. Cortical co-led the seed round with Scare the Bear Capital.
OthersideAI (HyperWrite)Lead
Vertical AI assistant/productivity application with strong user growth. Cortical co-led the $2.8M round with Active Capital.
RupertLead
Enterprise analytics platform that turns insights into actions, an AI-first enterprise software aligning with the firm's focus.
Immerok
Real-time stream-processing infrastructure enabling AI/ML data pipelines, supporting the AI production gap.
NeoCybernetica
Physical AI and autonomous systems for robotics, matching the firm's Physical AI area.
FAL.ai
Serverless 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.
DataroomHQ
Operational metrics automation for SaaS with AI-enabled enterprise workflow, aligning with the firm's focus on production-ready AI.

Key people

Partners who lead investments and shape the thesis.

JA
Jeremy Achin
General Partner
Physical AIAI Production GapAI for Good
IT
Igor Taber
General Partner
Physical AIAI Production GapAI for Good
MO
Mike Obolonskyi
Principal
Physical AIAI infrastructureAI Production Gap
SM
Sheamus McGovern
Venture Partner
AI infrastructureAI Production Gap

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

Similar investors

Firms with overlapping stage and industry focus.

Headline 2.0%

Shared focus

Developer tools and data infrastructure

Andreessen Horowitz 0.9%

4 shared stages