List of OpenAI Codex Customers
OpenAI
1455 3rd St,
San Francisco, 94158, CA,
United States
San Francisco, 94158, CA,
United States
1 669-200-3584
Professional Services
4000
$13.1B
Since 2010, our global team of researchers has been studying OpenAI Codex customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased OpenAI Codex for AI Frameworks and Libraries from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using OpenAI Codex for AI Frameworks and Libraries include: Cisco Systems, a United States based Professional Services organisation with 86200 employees and revenues of $61.50 billion, Github, a United States based Communications organisation with 5595 employees and revenues of $1.00 billion, MIT Department of Electrical Engineering and Computer Science, a United States based Education organisation with 130 employees and revenues of $10.0 million, Superhuman, a United States based Professional Services organisation with 100 employees and revenues of $10.0 million and many others.
Contact us if you need a completed and verified list of companies using OpenAI Codex, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The OpenAI Codex customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Cisco Systems | Professional Services | 86200 | $61.5B | United States | OpenAI | OpenAI Codex | AI Frameworks and Libraries | 2025 | n/a |
In 2025, Cisco Systems engaged as an early design partner to implement OpenAI Codex within its product engineering and design evaluation efforts, establishing enterprise-level exploration of the AI Frameworks and Libraries application class. The engagement was centered in the United States and explicitly targeted software development and product design functions across Cisco's product portfolio, with Cisco Systems evaluating practical usability scenarios for code generation and design-to-code assistance.
OpenAI Codex was exercised for typical AI Frameworks and Libraries capabilities, including programmatic code generation, contextual code completion, and prototype automation to accelerate design and engineering tasks. Cisco evaluated how OpenAI Codex could be configured to support developer workflows, developer assistance in integrated development environments, and design handoff scenarios that translate product concepts into working code artifacts.
Operational coverage focused on engineering and product design teams, using pilot workflows to surface integration points with IDE-assisted authoring, automated code review touchpoints, and CI pipeline handoffs, while shaping requirements for secure and auditable coding assistance. The work emphasized iterative feedback loops between Cisco engineering teams and OpenAI, informing feature set priorities and usability improvements for enterprise engineering workflows.
Governance and rollout activity was organized around usability testing and capability shaping rather than broad production deployment, with Cisco Systems capturing real-world engineering input to influence OpenAI Codex roadmap decisions. The engagement positioned OpenAI Codex, categorized as AI Frameworks and Libraries, as a candidate toolset for Cisco Systems software development and product design activities, with findings intended to inform future integration strategies and product capability evolution.
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Github | Communications | 5595 | $1.0B | United States | OpenAI | OpenAI Codex | AI Frameworks and Libraries | 2021 | n/a |
In 2021, GitHub integrated OpenAI Codex to power GitHub Copilot under the AI Frameworks and Libraries category, deploying AI pair-programming and code-completion capabilities. The partnership targeted developer productivity in the United States and surfaced whole-line and function suggestions directly in IDEs, helping accelerate coding workflows for many software teams.
Implemented functional capabilities included context-aware code completion, whole-line suggestion generation, function-level suggestions, and interactive pair-programming assistance delivered through GitHub Copilot with OpenAI Codex. Integrations focused on IDE editors and developer toolchains, placing AI-generated suggestions into the coding environment and impacting software development teams and workflows across the United States.
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MIT Department of Electrical Engineering and Computer Science | Education | 130 | $10M | United States | OpenAI | OpenAI Codex | AI Frameworks and Libraries | 2021 | n/a |
In 2021, the MIT Department of Electrical Engineering and Computer Science implemented OpenAI Codex as an applied research tool within the AI Frameworks and Libraries category to automate program synthesis for university STEM problems. MIT Department of Electrical Engineering and Computer Science deployed OpenAI Codex to support academic research workflows and to generate executable Python solutions for coursework and study sets.
The implementation emphasized program synthesis and few-shot learning capabilities of OpenAI Codex, using prompt engineering to produce Python code that solves mathematical and programming problems. Functional workstreams included automatic code generation, zero-shot and few-shot evaluation, and creation of labeled problem sets, with the research team validating correctness of generated programs against problem specifications.
Operational coverage was concentrated within an undergraduate research engagement in Cambridge, MA from September 2021 to January 2022, where a researcher curated datasets of course problems and instrumented an evaluation pipeline to assess code outputs. The deployment targeted academic research and coursework problem solving, combining dataset curation, automated code execution, and human verification to determine solution accuracy.
Governance and process work focused on standardized dataset creation and program evaluation protocols to measure model performance, rather than production IT governance. Outcomes reported by the researcher include measured accuracy rates of 70% zero-shot and 80% few-shot across evaluated problems, and subsequent coauthorship on a PNAS publication in August 2022 that documented the program synthesis results.
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Superhuman | Professional Services | 100 | $10M | United States | OpenAI | OpenAI Codex | AI Frameworks and Libraries | 2025 | n/a |
In 2025, Superhuman implemented OpenAI Codex as an AI Frameworks and Libraries capability to accelerate repetitive engineering work such as improving test coverage and fixing integration failures. The deployment is focused on software development and engineering workflows in the United States at Superhuman, a 100 employee professional services firm, and is positioned to shorten small developer task cycles that sit between product and engineering teams.
OpenAI Codex has been configured as a developer assist layer that synthesizes code snippets, generates test scaffolding, and proposes diagnostic fixes for integration failures. The implementation emphasizes lightweight change templates and automated suggestions that enable non-engineers to author small code changes, with all contributions routed into standard code review and merge gates to maintain engineering control and quality.
Operational scope covers engineering and adjacent product teams in the United States, with rollout prioritized on small developer workflows to reduce handoffs between product and engineering. Governance centers on human code review and existing commit review processes, and the initiative has been reported to accelerate small developer workflows and enable faster product delivery while preserving review controls.
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Buyer Intent: Companies Evaluating OpenAI Codex
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating OpenAI Codex. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating OpenAI Codex for AI Frameworks and Libraries include:
- Cusmano Agency, a United States based Insurance organization with 10 Employees
- Brigham Young University, a United States based Education company with 5000 Employees
- Rong Giant Bestment, a South Korea based Professional Services organization with 10 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated |
|---|---|---|---|---|---|---|
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Cusmano Agency | Insurance | 10 | $2M | United States | 2025-10-24 |
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Brigham Young University | Education | 5000 | $1.0B | United States | 2025-10-15 |
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Rong Giant Bestment | Professional Services | 10 | $1M | South Korea | 2025-08-13 |
FAQ - APPS RUN THE WORLD OpenAI Codex Coverage
OpenAI Codex is a AI Frameworks and Libraries solution from OpenAI.
Companies worldwide use OpenAI Codex, from small firms to large enterprises across 21+ industries.
Organizations such as Cisco Systems, Github, MIT Department of Electrical Engineering and Computer Science and Superhuman are recorded users of
OpenAI Codex for AI Frameworks and Libraries.
Companies using OpenAI Codex are most concentrated in Professional Services, Communications and Education, with adoption spanning over 21 industries.
Companies using OpenAI Codex are most concentrated in United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of OpenAI Codex across Americas, EMEA, and APAC.
Companies using OpenAI Codex range from small businesses with 0-100 employees - 25%, to mid-sized firms with 101-1,000 employees - 25%, large organizations with 1,001-10,000 employees - 25%, and global enterprises with 10,000+ employees - 25%.
Customers of OpenAI Codex include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified OpenAI Codex customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of AI Frameworks and Libraries.