JuliaHub Due Diligence

Run due diligence on JuliaHub: check compliance and get alerts when suppliers or ownership change.

United States · owned by Independent (United States) · juliahub.com · 10 vendors

JuliaHub (formerly Julia Computing) is an AI-native software company that provides platforms for engineers to model, simulate, and deploy complex physical systems. Its flagship products include Dyad, an AI agent for physics-based modeling and simulation, and the JuliaHub cloud platform for high-performance scientific computing. The company was founded by the co-creators of the Julia programming language and serves customers in aerospace, pharmaceuticals, automotive, and other engineering-intensive industries.

Resilience scores

Technology vendors

Services catalogue

1 service in catalogue across 1 category; runs on 10 sub-vendors.

Insights

Last updated 2026-10-19 · revision 2

10 direct vendors, 157 subvendors

Direct vendors by controlling owner country (sample)

Subvendors by controlling owner country (sample)

Migration Readiness: 9/10

Assessed by AI based on technology stack characteristics (cloud-native vs legacy, containerization, microservices), regulatory environment, data residency requirements, financial stability, and vendor lock-in risks. The score ranges from 0-10, where higher scores indicate better readiness for technology migration.

JuliaHub exhibits very high migration readiness, primarily due to its highly modern and cloud-native technology stack. The company already operates on Amazon Web Services (AWS) and extensively uses containerization technologies like Kubernetes and Docker, which are foundational for flexible and portable deployments. Their internal tech stack and key technologies, including the Julia programming language, SciML, and HPC capabilities, are well-suited for cloud environments and microservices architectures. A significant advantage is the absence of specific data residency requirements, which greatly simplifies potential migration strategies by removing a common and complex constraint. Financially, the company's strong venture capital backing provides the necessary resources to fund and execute any significant migration efforts. While the vendor relationships indicate a 'Medium' vendor lock-in risk with 10 vendors, the overall cloud-native architecture and lack of data residency restrictions suggest that any vendor-related migration challenges would be manageable. The company's proactive approach to regulatory compliance (NIS2 awareness, SOC 2 framework) also means that processes are likely in place to ensure compliance during a migration, rather than hindering it.

Compliance

9 in-scope frameworks identified; showing 3.

CMMC — No public evidence

The company works with U.S. defense contractors and government bodies like DARPA and the Air Force. Handling Controlled Unclassified Information (CUI) within these contracts would require Cybersecurity Maturity Model Certification (CMMC).

ITAR — No public evidence

JuliaHub serves the aerospace and defense sectors and offers an 'air-gapped' solution, suggesting it may handle data subject to the International Traffic in Arms Regulations, which control the export of defense-related articles and services.

GDPR (source) — Evidence found

As a global platform available to users worldwide, JuliaHub likely processes the personal data of individuals in the European Union/European Economic Area, making it subject to the General Data Protection Regulation.

Evidence: https://juliahub.com/legal/privacy-policy, https://help.juliahub.com/juliahub/v6.3/Deck.pdf

Financials

Three-year financials

Financial Resilience Score: 7/10

JuliaHub demonstrates solid financial resilience primarily driven by its strong recent capital position. The company closed a $65M Series B in April 2026 led by Dorilton Ventures, bringing total disclosed funding to approximately $106.6M (or $127M per Tracxn's tally). This provides multi-year runway for a company with roughly 100-110 employees, mitigating near-term liquidity risk. The investor base is high-quality and diversified, including Dorilton Ventures, General Catalyst, Menlo Ventures, AE Ventures, HighSage Ventures, and Founder Collective. However, the company operates in a highly competitive space dominated by well-capitalized incumbents like MathWorks, Siemens (post-Altair), Dassault Systèmes, and Synopsys/Ansys. Revenue estimates from third-party vendors vary wildly from $4M to $50M, suggesting the business is still at modest scale relative to its ambitions. Blended gross margins are likely lower than pure SaaS peers because the product bundles cloud compute with software. As a private company, JuliaHub does not disclose audited financials, making external credit analysis difficult. The ecosystem risk tied to the Julia programming language (smaller than MATLAB/Python communities) and the need for agentic AI assurance in regulated verticals (aerospace, pharma, government) create execution risk. On balance, the strong funding position and diversified product monetization across subscriptions, usage-based compute, domain apps, and services support a moderately strong resilience score.

Key strengths: $65M Series B raised April 2026 led by Dorilton Ventures providing multi-year runway, Total disclosed funding of $106.6M-$127M across 8 rounds from 11 investors, Marquee enterprise reference customers in pharma, aerospace, automotive, and defense, Diversified product monetization across software subscriptions, usage-based compute, domain apps (Dyad, Pumas), and professional services, Vertical integration from language runtime through cloud execution to domain applications, High-quality investor base including General Catalyst, Menlo Ventures, Founder Collective

Risk factors: Formidable incumbents: MathWorks (MATLAB/Simulink), Siemens (post-Altair), Dassault Systèmes, Synopsys/Ansys, Mixed gross-margin profile due to bundled cloud compute with software, Ecosystem risk around Julia language being smaller than MATLAB and Python ecosystems, Agentic AI assurance requirements in aerospace, pharma and government gate production revenue, No public audited financials makes external credit or counterparty analysis difficult, Third-party revenue estimates vary by order of magnitude ($4M to $50M), suggesting opacity

Revenue by geography

Revenue by product/service

Workforce by country

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