JFrog NASDAQ: FROG is seeing continued demand from enterprise artificial intelligence activity, with cloud usage benefiting from experimentation around coding agents and model development, Jeff Schreiner, the company’s head of investor relations, said during a conference discussion with analyst Andrew Sherman.
Schreiner said the company began seeing “the spark” of AI-related activity last year, driven by the introduction of experimentation and coding agents inside enterprises. That trend accelerated in the first quarter, he said, as adoption and usage increased year over year.
“It’s not yet necessarily led to the fire” of higher activity flowing into production binaries, Schreiner said. But he added that the experimentation phase has already created significant cloud usage. He also said the AI era is shifting attention away from human interaction with source code and toward binaries as a more critical software asset.
Cloud Growth and Commitments
Sherman noted that JFrog’s cloud revenue grew 50% in the first quarter and has recently been in the 45% to 50% range. Schreiner said some of that growth has come from usage above committed contract levels, while the company guides based only on customer commitments.
Schreiner compared the current AI spending environment to the “Wild West” period of 2020 through 2022, when software budgets were less constrained. He said enterprises are pushing to build AI models and autonomous agents, though he expects spending to eventually normalize.
He said JFrog’s revenue floor is represented by committed customer spending, while the company has also benefited from usage above those commitments. Schreiner said net revenue retention was 116 two quarters ago, 117 last quarter and 118 in the most recent quarter, excluding the benefit of overconsumption.
When Sherman suggested that the company may have line of sight to 120 net revenue retention, Schreiner responded, “We’re hopeful,” adding that it is up to JFrog to convert consumption into higher commitments.
Schreiner said the company has historically been able to work with customers who exceed usage levels and convert them into higher commitments. However, he said the current environment is different because some customers are reluctant to lock in larger contracts while AI usage patterns remain uncertain.
“We’ve ironically found that there has been pushback from customers to signing a commitment,” Schreiner said, adding that customers are often willing to pay higher overage rates during the current experimentation phase.
AI Activity Boosts Binary Growth
Schreiner pointed to JFrog’s recently released State of the Union report, saying binary growth inside Artifactory rose 136% over the past year. He said the growth reflects increased binary creation in the AI era.
He also said AI is changing how customers think about software languages and security coverage. In the past, some customers may have used alternatives that supported only the languages they primarily programmed in. Schreiner said customers are now realizing they can be exposed through languages they do not use heavily.
JFrog’s scale in supporting more than 35 languages is becoming a competitive differentiator, he said. Schreiner said the challenge is not simply supporting 10 or 12 languages, but maintaining performance, security and additional functionality across a much broader platform.
AI-Native Customers and Competitive Position
Schreiner said that as of March 31, JFrog had three of what it considers the top five AI-native companies as customers, though he said the group can vary depending on how companies and models are defined. He said JFrog cannot publicly name those customers.
Those three customers are primarily using Artifactory, similar to enterprise customers, and have not yet adopted JFrog’s security products, Schreiner said. He also said all three are self-hosted.
Schreiner said JFrog hopes to discuss, in general terms, a possible fourth AI lab around its second-quarter earnings. He said that potential customer would be notable because it approached JFrog to work in a hybrid model, which would be the first such case among the AI frontier labs discussed.
Asked about competition, Schreiner said JFrog’s differentiator can be summarized as “scalability.” He said the company has spent nearly two decades focused on binaries, an asset he said is becoming more important as AI shifts software development toward machine-driven creation.
Security Demand and JFrog Curation
Schreiner said security has been a major growth driver, with Sherman noting that it represents 10% of annual recurring revenue. Schreiner said JFrog Curation has benefited from the rising frequency of software supply chain attacks.
He said some buying in the third and fourth quarters of last year was driven by immediate incident-related budgets, with customers moving quickly to deploy Curation. But he said the pattern is no longer dependent on isolated incidents such as Log4j.
“I think this is constant and in front of our customers’ faces,” Schreiner said, adding that the pipeline for Curation continues to show strength.
Schreiner said that before the Shai Hulud incident in the third quarter, the company’s security deployment and pipeline were roughly split between JFrog Advanced Security and JFrog Curation. Since then, he said demand has been more heavily weighted toward Curation.
He also said that, to date, JFrog Curation has not been penetrated. Schreiner said its value is enhanced by being tied to Artifactory as a system of record.
Governance, Skills Registry and Fly
Discussing newer products, Schreiner said governance is “the next big item” for JFrog as enterprises move from training AI agents to governing them as they operate more autonomously. He said JFrog views itself as part of the “governor judge class,” enforcing enterprise policies rather than acting as part of the creator class.
Schreiner said governance is not yet a major component of the company’s 2026 guidance. He said the company is also seeing early proof-of-concept success with its MCP Registry and Skills Registry, which are intended to help track agents, their skills and whether they are behaving as expected.
On Fly, Schreiner said the product was built to help smaller teams starting with agentic workflows plug into Artifactory and help JFrog learn how agentic problems are solved at a smaller scale. He said that experience can then be applied when large enterprise customers look to solve similar problems.
About JFrog NASDAQ: FROG
JFrog is a software company specializing in DevOps solutions designed to streamline the management, distribution and security of software binaries. Its core offering, JFrog Artifactory, serves as a universal artifact repository manager compatible with all major package formats, enabling development teams to store, version and share build artifacts across the software delivery pipeline. The company's platform also includes tools for continuous integration and delivery (CI/CD), security scanning and release automation.
Among JFrog's flagship products are JFrog Xray, a security and compliance scanning service that analyzes artifacts and dependencies for vulnerabilities; JFrog Pipelines, a CI/CD orchestration engine that automates build and release workflows; and JFrog Distribution, which accelerates the secure distribution of software releases to edge nodes and end users.
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