AI Buyer Insights:

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Michelin, an e2open customer evaluated Oracle Transportation Management

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Michelin, an e2open customer evaluated Oracle Transportation Management

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

List of OpenAI API Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
DoorDash Professional Services 23700 $10.7B United States OpenAI OpenAI API ML and Data Science Platforms 2024 n/a
In 2024, DoorDash implemented OpenAI API as a core component of its ML and Data Science Platforms adoption to accelerate employee-led innovation and operational automation. The rollout runs alongside enterprise ChatGPT Enterprise usage across technical and non-technical teams, and it is framed by DoorDash’s operator culture where product mindset and rapid experimentation are expected across functions. OpenAI API is being used to deliver a set of capabilities aligned to ML and Data Science Platforms, including enterprise chat and co-pilot functionality, AI-powered search and smarter content delivery, agentic task automation, and workflow augmentation for HR processes. Functional implementations explicitly include synthesis of performance review feedback, automated survey analysis with actionable summaries, workflow generation for manager action plans, and predictive modeling for executive performance, all powered by OpenAI API. The deployment covers both customer-facing and internal systems, with OpenAI APIs powering DoorDash’s customer service platform that handles 3 million chats per month, and supporting internal workflows for review moderation and support. Adoption spans finance, sales, operations, IT, marketing, and People functions, and the People team has enabled non-engineers to build automation, for example a people ops script that automated document uploads. Governance and rollout emphasize access, literacy, and measured adoption, with enterprise license distribution, hackathons, tutorials, and initial metrics focused on adoption and frequency of use. DoorDash integrates AI literacy into its performance framework and relies on HR and IT engineering resources to iterate the stack, while exploring agent capabilities for policy answers, development support, and manager enablement. The articulated aim is augmentation rather than replacement, enabling employees to become technical creators and democratizing workflow automation through OpenAI API.
Model ML Banking and Financial Services 75 $5M United States OpenAI OpenAI API ML and Data Science Platforms 2025 n/a
In 2025, Model ML deployed the OpenAI API as its core platform within the ML and Data Science Platforms category to power purpose-built agents and an application that automates end-to-end research and workflow automation for financial services firms. Model ML implemented OpenAI API driven pipelines using GPT-4.1 and OpenAI o3 family models to enable large-context, reasoning and multimodal capabilities required by investment research and reporting workflows. The implementation centers on two layers, an agent layer and an application layer. At the agent layer Model ML configured GPT-powered agents capable of parsing structured and unstructured financial datasets, understanding schemas, writing code, and orchestrating multi-step workflows. At the application layer Model ML exposed tooling for users to build and manage agents that automate tasks such as data gathering, analysis, slide generation and output publishing, enabling chaining of data ingestion, analysis, and presentation creation into autonomous runs. Model ML integrates the OpenAI Agents SDK and MCP tooling to manage agent loops, tool calling and guardrails, and it connects to data sources commonly used in finance including SharePoint for output publishing, large vendor datasets like Capital IQ, FactSet and Crunchbase, plus CRM systems, email, files and meeting transcripts. The platform is designed to handle terabyte scale datasets and multi-table schemas so agents can retrieve and act on enterprise data across research and investment teams. Operational coverage focuses on research, investment analysis and reporting functions inside financial services firms, with Model ML often acting as a consulting partner early in rollouts to map AI-native operating models and identify high-value workflows for automation. Internally Model ML has adopted an AI-native operating model, using AI-assisted one-on-ones and a flat organization to accelerate product feedback loops, and it shifts toward plugging in OpenAI components rather than maintaining equivalent internal infrastructure. Explicit outcomes called out by Model ML include accelerating tasks that previously took days or weeks into minutes or hours, automating end-to-end processes such as quarterly earnings summaries including slide formatting and SharePoint publication, and delivering thousands of use cases customers can adopt out of the box. The deployment emphasizes workflow orchestration, governance through guardrails and the OpenAI Agents SDK, and enabling firms to remap human roles toward judgment-based activities as agents handle high-volume operational work.
United Kingdom Government Uk Government 450000 $1200.0B United Kingdom OpenAI OpenAI API ML and Data Science Platforms 2025 n/a
In 2025, the UK Government entered a strategic partnership with OpenAI to deploy the OpenAI API as part of its ML and Data Science Platforms adoption across public services and to explore broader private sector use. The memorandum of understanding frames a programmatic approach to embed the OpenAI API into government workflows, infrastructure planning, and technical information exchange to support the UK’s AI Opportunities Action Plan goals. The implementation signal centers on operational AI tooling, notably an OpenAI API powered chatbot on GOV.UK that serves thousands of small businesses and OpenAI technology embedded in Whitehall applications. OpenAI API capabilities are applied in Humphrey, the civil service assistant that relieves administrative burden, and in Consult, a policy workflow tool that automatically sorts public consultation responses and completes tasks that previously took officials weeks in minutes. These deployments reflect category-aligned functions such as natural language understanding, conversational interfaces, and automated text classification under the ML and Data Science Platforms discipline. Integrations are explicitly with GOV.UK information services and Whitehall policy systems, and the partnership contemplates deeper technical information sharing with the UK AI Security Institute to expand a program for model capability awareness and security research. The MOU also includes exploratory work on infrastructure priorities to support UK sovereign capability for advanced AI models, signaling coordination between model providers, government IT estates, and public sector data flows. Governance is structured through the non-binding MOU, which sets collaboration pillars for adoption pilots, infrastructure planning, and technical exchange rather than immediate mandated rollouts. OpenAI confirmed increased UK presence, noting its London office opened in 2023 and a team over 100 staff, which is intended to support implementation, research collaboration, and go-to-market activities in the UK. The UK Government OpenAI API ML and Data Science Platforms relationship is therefore oriented toward staged pilots across civil service and small business services, expanded technical governance, and joint exploration of infrastructure and security programs.
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Buyer Intent: Companies Evaluating OpenAI API

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating OpenAI API. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating OpenAI API for ML and Data Science Platforms include:

  1. Lund University, a Sweden based Education organization with 8800 Employees
  2. Yale University, a United States based Education company with 14800 Employees
  3. Quality First Branding Agency, a United States based Professional Services organization with 10 Employees

Discover Software Buyers actively Evaluating Enterprise Applications

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FAQ - APPS RUN THE WORLD OpenAI API Coverage

OpenAI API is a ML and Data Science Platforms solution from OpenAI.

Companies worldwide use OpenAI API, from small firms to large enterprises across 21+ industries.

Organizations such as United Kingdom Government Uk, DoorDash and Model ML are recorded users of OpenAI API for ML and Data Science Platforms.

Companies using OpenAI API are most concentrated in Government, Professional Services and Banking and Financial Services, with adoption spanning over 21 industries.

Companies using OpenAI API are most concentrated in United Kingdom and United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of OpenAI API across Americas, EMEA, and APAC.

Companies using OpenAI API range from small businesses with 0-100 employees - 33.33%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 66.67%.

Customers of OpenAI API 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 API customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.