List of OpenAI Function Calling Customers
San Francisco, 94158, CA,
United States
Since 2010, our global team of researchers has been studying OpenAI Function Calling 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 Function Calling for AI Model Deployment and Monitoring 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 Function Calling for AI Model Deployment and Monitoring include: Vercel, a United States based Professional Services organisation with 700 employees and revenues of $80.0 million, Pipedream, a United States based Professional Services organisation with 30 employees and revenues of $5.0 million, Outtake, a United States based Professional Services organisation with 12 employees and revenues of $2.0 million, ReelMind, a United States based Media organisation with 12 employees and revenues of $1.0 million and many others.
Contact us if you need a completed and verified list of companies using OpenAI Function Calling, 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 Function Calling 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!
Apply Filters For Customers
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
Outtake | Professional Services | 12 | $2M | United States | OpenAI | OpenAI Function Calling | AI Model Deployment and Monitoring | 2025 | n/a |
In 2025, Outtake deployed OpenAI Function Calling as part of its AI Model Deployment and Monitoring implementation, embedding agentic AI into enterprise cybersecurity workflows. The deployment focuses on always-on agents that provide 24/7 threat coverage and rapid investigative sequencing for security operations and trust and safety teams.
The implementation is built as a multi-stage pipeline that ingests multimodal signals, applies reasoning, scores findings for severity, and surfaces enforcement decisions. Outtake’s agents run on a model stack led by GPT-4.1, GPT-4o and OpenAI o3, and OpenAI Function Calling is used to compile evidence, draft resolution notices, and orchestrate automated enforcement tasks, with outputs preserved in auditable logs and formatted to meet platform compliance requirements.
Operational coverage includes continuous crawling of surface areas such as app stores, websites, social platforms, and ads to map trustworthy and suspicious entities and detect coordinated abuse across formats. Function calling automates the assembly and submission of case artifacts to platform enforcement interfaces and routes flagged cases into human review queues, while customer-configured whitelists, brand guidelines, intellectual property policies, and enforcement preferences control decisioning logic.
Governance is centered on customer control and human oversight, customers train agents using natural language, retain override authority for edge cases, and provide feedback that updates agent behavior in real time without retraining. Outtake reports reduced takedown timelines from 60 days to hours and avoidance of millions in fraud losses, and internal model evaluations show OpenAI models outperform alternatives for cross-platform reasoning, supporting scaled deployment while maintaining auditable enforcement workflows.
|
|
|
Pipedream | Professional Services | 30 | $5M | United States | OpenAI | OpenAI Function Calling | AI Model Deployment and Monitoring | 2023 | n/a |
In 2023, Pipedream implemented OpenAI Function Calling as an action inside its event driven automation and workflow platform, embedding the OpenAI Function Calling capability into its developer ops tooling. This deployment situates OpenAI Function Calling within Pipedreams AI Model Deployment and Monitoring posture, enabling developers to invoke OpenAI tools directly from workflow triggers and action steps.
The implementation centers on function calling workflows and a library of prebuilt components, configured as first class actions that map LLM outputs to backend actions and service APIs. OpenAI Function Calling is exposed as developer facing modules within Pipedreams platform, with configuration surfaces for request formatting, function schemas, and runtime error handling, supporting automated orchestration of downstream processes.
The rollout is US based and publicly documented on Pipedreams integration pages, with example integrations such as a Rhombus audit record workflow showing ChatGPT using functions to create backend records from events. Documentation and prebuilt components reduced the engineering effort required to wire LLM outputs into backend actions for customers, and the implementation impacts developer teams responsible for integrations, automation, and customer facing backend workflows.
|
|
|
ReelMind | Media | 12 | $1M | United States | OpenAI | OpenAI Function Calling | AI Model Deployment and Monitoring | 2024 | n/a |
In 2024, ReelMind implemented OpenAI Function Calling for AI Model Deployment and Monitoring of its video-generation pipeline. The company published documentation describing a US hosted implementation that orchestrates programmatic workflows to automate video creation and platform actions across its media platform.
ReelMind uses OpenAI Function Calling to invoke internal services to generate videos, fetch metadata, and manage credits. The implementation describes function call schemas that trigger discrete functional modules, including internal video generation APIs, metadata extraction routines, and credit management operations, aligning application logic with API driven orchestration.
The deployment architecture is US hosted and centers on API orchestration, with function calls serving as the control plane between OpenAI and ReelMind internal services. Operational coverage focuses on media and content production workflows and platform level actions, enabling automated end to end video creation and programmatic platform interactions.
Governance and workflow changes emphasize programmatic orchestration, with documented function definitions and invocation patterns used to map business functions such as content generation, metadata enrichment, and credit handling into automated pipelines. OpenAI Function Calling serves as the central orchestration layer for ReelMind OpenAI Function Calling AI Model Deployment and Monitoring of its media production operations.
|
|
|
Vercel | Professional Services | 700 | $80M | United States | OpenAI | OpenAI Function Calling | AI Model Deployment and Monitoring | 2025 | n/a |
In 2025, Vercel integrated OpenAI Function Calling into its AI SDK, using AI Cloud and AI SDK 3.0 to enable Generative UI and streaming React Server Component integrations for front-end AI experiences. This implementation is cataloged within the AI Model Deployment and Monitoring category and is regionally concentrated at Vercel headquarters in the United States, targeting web developer workflows and front-end engineering teams.
Vercel configured OpenAI Function Calling as a first-class runtime capability in AI SDK 3.0, enabling server-side function invocation patterns and streaming server component payloads that surface AI outputs directly into React Server Components. The work emphasizes Generative UI capabilities and includes documentation artifacts and cookbooks that guide component-level wiring, event-driven function calls, and streaming render patterns, with stated outcomes including richer UI components, lower client JS overhead, and faster development for AI native web apps.
Integrations are framed around OpenAI compatible Function Calling, with the SDK exposing developer-facing APIs and runtime hooks optimized for streaming responses into the React Server Component lifecycle. Operational coverage centers on Vercel’s web platform teams and developer experience groups at the US site, and the implementation aligns application-level orchestration with front-end rendering workflows to reduce client side processing and centralize model call orchestration.
Governance and rollout relied on SDK versioning, cookbooks, and documentation to standardize patterns for Generative UI and streaming integrations across projects, prioritizing developer adoption at HQ. The Vercel AI SDK and OpenAI Function Calling combination establishes a repeatable blueprint for embedding AI Model Deployment and Monitoring into front-end engineering practices while preserving developer ergonomics through server streaming and minimal client JavaScript.
|
Buyer Intent: Companies Evaluating OpenAI Function Calling
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
|---|---|---|---|---|---|---|---|---|
| No data found | ||||||||