1M business customers use AgentKit to build AI agents in days
Why does speed matter when enterprises roll out AI assistants? For many firms, the promise of intelligent agents has been stalled by lengthy development cycles that stretch into months, draining budgets and eroding momentum. AgentKit claims to flip that script, offering a platform where non‑technical teams can assemble, test and launch agents without the usual overhead.
The company reports that a million business customers have already tapped the tool, turning concepts into usable bots in a matter of days. That rapid turnaround is especially appealing to large‑scale investors and asset managers who need to iterate quickly on complex, multi‑agent workflows. Early adopters such as Carlyle are pointing to measurable gains, noting that the evaluation suite shaved weeks off their internal build process.
If the numbers hold up, the shift from protracted pilots to near‑instant production could reshape how corporations embed AI into daily operations. The following statement from AgentKit’s leadership explains exactly how they’re making that possible.
- We also made enterprise agents practical to build and deploy with AgentKit, making it possible for teams to go from idea to production in days instead of months. Companies like Carlyle are already seeing results: the AgentKit evaluation platform cut development time on Carlyle's multi-agent due diligence framework by over 50% and improved agent accuracy by 30%. - We also advanced our multimodal models to enable richer workflows--from the Image Generation API and Sora 2 for visual and video creation to gpt-realtime and Realtime API to build production voice agents.
Teams across every industry can now work across text, images, video, and audio in one system. (opens in a new window)According to a recent Wharton study(opens in a new window), 75% of enterprises report a positive ROI, and fewer than 5% report a negative return. While there are many studies on this topic, this one reflects what we see on the ground today with our customers: when AI is deployed with the right use case and infrastructure, teams see real results.
- Indeed is using OpenAI APIs in its Invite to Apply feature to drive a 20% increase in applications and a 13% lift in hires. - Lowe's empowers all associates in 1,700+ stores with expert project guidance through Mylow Companion, an in-store app built with OpenAI models. - With OpenAI as the backbone of Fin, their customer service agent, Intercom has accelerated development cycles from quarters to days.
- And starting today, Databricks(opens in a new window) is bringing OpenAI frontier intelligence to where enterprises' data already lives--making it easier to build and run high-quality agents. Beyond internal adoption, we're seeing a second trend: businesses increasingly want to build with OpenAI too. Companies are creating new applications and agentic workflows directly on our platform.
One million businesses now use OpenAI’s platform. Customers range from AMEX and Amgen to Target and Cisco, each paying directly for the service. AgentKit promises to shrink development cycles, letting teams move from concept to production in days rather than months.
Carlyle’s evaluation platform, for example, reportedly cut multi‑agent development time, though the exact magnitude of the gain isn’t quantified. The claim that enterprise agents have become “practical to build and deploy” rests on early adopters’ reports; whether the same efficiency will hold across diverse use cases remains uncertain. Weekly sign‑ups suggest momentum, yet no data are provided on retention or long‑term outcomes.
If the speed advantage translates into measurable business impact, the platform could solidify its position as a fast‑growing enterprise tool. Conversely, without broader performance metrics, the true value proposition stays ambiguous. In short, the numbers are impressive, but the evidence for sustained advantage is still developing.
Further Reading
- OpenAI AgentKit vs Traditional Workflows: The Complete 2025 Guide - Chat Data
- Introducing AgentKit - OpenAI
- 10 Essential OpenAI AgentKit Use Cases in 2025 - Skywork.ai
- OpenAI's AgentKit: The Future of Custom AI Agents - USAI
- 4 Harsh Realities of OpenAI's AgentKit for Enterprises - CloudFactory
Common Questions Answered
How does AgentKit claim to reduce AI agent development time for enterprises?
AgentKit asserts that its platform enables non‑technical teams to assemble, test, and launch AI agents in days rather than months, cutting typical development cycles dramatically. The company highlights that this speed improvement helps preserve budgets and maintain project momentum.
What performance improvements did Carlyle experience using AgentKit's evaluation platform?
Carlyle reported that the AgentKit evaluation platform reduced development time for its multi‑agent due diligence framework by over 50% and boosted agent accuracy by roughly 30%. These gains illustrate the practical benefits of the platform for complex enterprise workflows.
Which multimodal capabilities has AgentKit added to support richer AI workflows?
AgentKit advanced its multimodal models by introducing an Image Generation API and the Sora 2 model for video, enabling agents to handle visual content alongside text. These additions allow enterprises to create more sophisticated, media‑rich agent interactions.
Who are some of the notable business customers that have adopted AgentKit, and how do they pay for the service?
Among the one million business customers are AMEX, Amgen, Target, and Cisco, each of which pays directly for AgentKit’s services. Their adoption demonstrates broad industry interest in accelerating AI agent deployment.