List of OpenAI GPT-3 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 GPT-3 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 GPT-3 for Generative AI Platforms 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 GPT-3 for Generative AI Platforms include: Warner Bros. Discovery, a United States based Media organisation with 35000 employees and revenues of $39.32 billion, Quizlet, a United States based Education organisation with 250 employees and revenues of $30.0 million, Willdom, a United States based Professional Services organisation with 192 employees and revenues of $20.0 million, Inworld AI, a United States based Professional Services organisation with 75 employees and revenues of $6.0 million, Waymark, a United States based Professional Services organisation with 40 employees and revenues of $4.0 million and many others.
Contact us if you need a completed and verified list of companies using OpenAI GPT-3, 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.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Computational Neurolinguistics Lab | Healthcare | 15 | $1M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2023 | n/a |
In 2023, Computational Neurolinguistics Lab implemented OpenAI GPT-3 as a core research tool to support in silico analyses of natural language production. The OpenAI GPT-3 deployment was applied to studies of sentence production and second language acquisition, extending comparative experiments previously run with OpenAI GPT-2 and human speech data. The integration followed a lightweight, API-driven architecture typical for Generative AI Platforms, with model access embedded into Python and R analysis pipelines to enable programmatic prompting, batch inference, and scripted feature extraction. Functional capabilities implemented included utterance simulation for stimulus generation, automated model-based comparison workflows, and data preparation routines used for visualization and statistical exploration. Model outputs were combined with multimodal experimental data, specifically EEG recordings collected via Emotiv wireless EEG headsets, and incorporated into the lab's data cleaning and analysis processes. Operational scope covered the lab's research activities and experimental design, with faculty and peers coordinating model use, protocol definition, and dissemination of findings within the Computational Neurolinguistics Lab.
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Eduleaf | Professional Services | 10 | $1M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2022 | n/a |
In 2022, Eduleaf implemented OpenAI GPT-3 as part of its Generative AI Platforms adoption to embed generative models across its machine learning and client delivery workflows. The deployment used OpenAI GPT-3 to power language generation and classification features within a compact professional services engineering organization headquartered in the United States, aligning the application with product development and client outreach functions.
Implementation modules included a software engineer classifier built from GitHub repository signals and code quality features, a resume information extraction pipeline using a custom named entity recognition model combined with rule based extraction, and a personalized recommendation engine that analyzed social media interests. Eduleaf also developed an email generation system leveraging GPT language capabilities with LinkedIn data, a conversational insight bot that retrieved Zoom recordings, produced Whisper based transcriptions, and extracted findings using ChatGPT model prompts, plus image generation experiments using DALL·E and a computer vision MaskRCNN trained on a bespoke dataset for face mask detection.
Integrations explicitly referenced in the implementation included GitHub data sources, LinkedIn data, Facebook and Twitter APIs for social signals, Zoom for call capture, OpenAI Whisper for transcription, ChatGPT for conversational insight extraction, and DALL·E for image generation. Operational coverage centered on the companys machine learning and engineering teams, with models and APIs orchestrated through standard development pipelines appropriate to a 10 person firm, supporting client projects and internal automation workflows.
Governance and delivery were managed using Agile frameworks and Scrum practices, with project tracking through Jira and Trello, and senior machine learning engineering leadership guiding cross functional teams from design through delivery. The narrative reflects a program of prompt engineering, model orchestration, and API driven integration consistent with Generative AI Platforms implementations in small professional services firms.
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FindOurView | Professional Services | 12 | $2M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2021 | n/a |
In 2021, FindOurView integrated OpenAI GPT-3 into its Generative AI Platforms architecture to power SaaS advanced analytics for unstructured ecommerce reviews. The implementation was embedded in a full stack application developed in collaboration with the CTO and CDO, leveraging AWS SageMaker for model training and deployment, Amazon Redshift for secure data warehousing, and a React front end for client interaction.
The project implemented end to end data pipelines for ingestion, deduplication, and retention using SQL and Python, with Langchain APIs used for data manipulation and querying. The solution incorporated Transformers pipeline components from Hugging Face for NLP tasks, Langchain Chains and Agents to orchestrate model-driven workflows, and an AI scheduling module built in SageMaker that applies a FIFO principle to appointment booking.
Integrations explicitly included OpenAI models such as da-vinci alongside OpenAI GPT-3 as part of the Generative AI Platforms footprint, and experimentation with Databricks Dolly_v2. The architecture reused Langchain for API interaction and memory callbacks, Hugging Face Transformers for model pipelines, FastAPI to expose prediction endpoints, Spark cluster ingestion for unified person data, and container deployments to Docker and GCP Kubernetes for portability.
Governance and MLOps practices were formalized using MLflow to manage model artifacts, configurations, and YAML packaging between training and inference pipelines on AWS SageMaker. A model interpretation module was implemented in Python to surface feature contribution scores and what if analysis, and Langchain memory and callback features were incorporated into production chains to support explainability and operational tracing.
The implementation produced a consolidated FindOurView OpenAI GPT-3 Generative AI Platforms capability that delivered a robust solution with reliable and secure storage in Redshift, improved scheduling efficiency through the FIFO agent, and productionizable CV and overstaying risk POCs. The overstaying probability model is planned for future use by the National Targeting Center, and the team documented APIs and MLOps artifacts to support ongoing operationalization.
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Inworld AI | Professional Services | 75 | $6M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2022 | n/a |
In 2022, Inworld AI implemented OpenAI GPT-3 as a foundational component of its Generative AI Platforms deployment to power the company’s AI character capabilities. The implementation targeted the creation of next generation non-playable characters, using natural language inputs to define personality, goals, motivations, manners of speech, memories, and voice so creators can bring NPCs to life in minutes.
OpenAI GPT-3 was integrated as one of approximately 20 machine learning models within Inworld AI’s proprietary technology stack, serving as the primary language generation layer for dialogue and reactive speech. Surrounding modules implemented by Inworld include emotion modeling, memory services, behavior orchestration, and cognition tuning, which together shape contextual responses and longer term character state.
The deployment was embedded into Inworld’s creator and runtime tooling, enabling character design workflows that accept natural language character descriptions and produce dialogue and behavior profiles for game or story engines. Operational ownership rested with product and engineering teams focused on creator tooling and character runtime, and the system was positioned to serve creators building interactive characters for games and narrative experiences.
As a startup with constrained engineering resources, Inworld AI used OpenAI GPT-3 to avoid building base language models from scratch, freeing time and creative energy to invest in differentiated IP that controls emotions, memory, and behaviors. The company described GPT-3 as a foundational model that increased relevance of NPC dialogue and behavior, enabling the team to focus on proprietary features that drive the next generation of AI characters.
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Letterdrop | Professional Services | 28 | $3M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2022 | n/a |
In 2022, Letterdrop implemented OpenAI GPT-3 in a contract engagement based in Frisco, TX between March 2022 and April 2022. The work used the OpenAI GPT-3 application within the Generative AI Platforms category to build fine-tuned sentence rewriting and summarization capabilities for Letterdrop.
The implementation leveraged the OpenAI GPT-3 API and an iterative pattern-exploiting training framework that used cloze prompts and pseudo labeling to produce fine-tuned models. Functional components included prompt engineering, a pseudo-label generation and review loop, an iterative fine-tuning pipeline, and model evaluation and packaging for deployment. The explicit outputs were fine-tuned sentence rewriting models and summarization models tuned against pseudo-labeled and curated cloze-style training data.
Architecture and deployment were API centric, with GPT-3 serving as the hosted model endpoint and an off-platform orchestration layer executing iterative training, pseudo labeling, dataset versioning, and evaluation runs. The operational scope was concentrated on engineering and content processing workflows to support editorial and content generation activities within Letterdrop, consistent with Generative AI Platforms usage patterns.
Governance focused on training data curation and workflow controls, including cloze prompt curation, pseudo-label review gates, staged testing, and model promotion procedures. This created a repeatable fine-tuning and deployment pipeline for OpenAI GPT-3 models at Letterdrop.
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Education | 250 | $30M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2023 | n/a |
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Media | 35000 | $39.3B | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2021 | n/a |
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Professional Services | 40 | $4M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2022 | n/a |
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Professional Services | 192 | $20M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2021 | n/a |
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Professional Services | 40 | $4M | United States | OpenAI | OpenAI GPT-3 | Generative AI Platforms | 2022 | n/a |
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| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD OpenAI GPT-3 Coverage
OpenAI GPT-3 is a Generative AI Platforms solution from OpenAI.
Companies worldwide use OpenAI GPT-3, from small firms to large enterprises across 21+ industries.
Organizations such as Warner Bros. Discovery, Quizlet, Willdom, Inworld AI and Waymark are recorded users of
OpenAI GPT-3 for Generative AI Platforms.
Companies using OpenAI GPT-3 are most concentrated in Media, Education and Professional Services, with adoption spanning over 21 industries.
Companies using OpenAI GPT-3 are most concentrated in United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of OpenAI GPT-3 across Americas, EMEA, and APAC.
Companies using OpenAI GPT-3 range from small businesses with 0-100 employees - 70%, to mid-sized firms with 101-1,000 employees - 20%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 10%.
Customers of OpenAI GPT-3 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 GPT-3 customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Generative AI Platforms.