JFrog Says AI Coding Boom Is Driving Demand for Binary Security and Cloud Platform

JFrog (NASDAQ:FROG) Chief Financial Officer Ed Grabscheid said artificial intelligence-driven software development is increasing the volume of binaries moving through software supply chains, creating demand for the company’s software management and security platform.

Speaking at KeyBanc’s Park City conference, Grabscheid described AI coding tools as making code creation less expensive and faster, while making binaries—the compiled software assets that move through the development and deployment process—the more important asset to manage and secure.

“Every organization is becoming this software factory and moving at the speed of machines,” Grabscheid said. “Code is becoming cheap, and the primary asset is the binary.”

He said the emergence of large language models, Model Context Protocol, and skills has added new categories of software assets. JFrog’s Artifactory product manages binaries across the software supply chain, and Grabscheid said machine-generated code is producing an “exponential” increase in the number of binaries customers need to handle.

Quarterly Growth Supported by Cloud, Security and Usage

Grabscheid said JFrog’s second-quarter results included 29% year-over-year total revenue growth and 53% cloud revenue growth. He identified three key drivers: adoption of security products, higher customer usage associated with the rising volume of binaries, and broader use of JFrog’s platform.

Security has become an increasingly important cross-sell opportunity, he said, as customers add products around Artifactory and increase their commitments to JFrog. The company’s Enterprise+ platform customer base grew 39% year over year and represented 59% of revenue, according to Grabscheid.

Usage above customers’ contracted minimum commitments also contributed to revenue, he said. Customers may choose to pay for overages while they assess how much capacity they will need in an AI-driven development environment rather than immediately committing to a larger contract.

Grabscheid said the model gives customers lower per-gigabyte pricing for minimum commitments while allowing flexibility to exceed those commitments. JFrog’s sales team is working to convert excess usage into longer-term commitments, though its incentives are tied to commitments rather than overage revenue, he said.

He pointed to JFrog’s updated cloud growth outlook as evidence that customer commitments are increasing. The company had previously guided for 34% cloud growth at the midpoint and later raised that outlook to 42%, he said. JFrog does not separately quantify the revenue contribution from usage above minimum commitments.

Security Pipeline Gains Attention After Supply-Chain Incidents

Grabscheid said software supply-chain attacks are raising awareness of JFrog’s security offerings, particularly JFrog Curation, which is designed to help organizations control what software packages enter their environments.

He cited the Shai-Hulud open-source security incidents as contributing to increased pipeline since the first event in September 2025. Curation has become a larger part of the company’s security sales mix, he said, after previously accounting for roughly half of security activity.

“Developers and machines want to move quickly,” Grabscheid said. “There is a hesitancy, particularly from the CISO, around what you bring into the organization, and Curation fills the need.”

He said 40% of JFrog’s new customer wins in the quarter included security products. The company sees Curation as easier to sell because it does not require displacement of an existing product, while JFrog Advanced Security generally involves replacing point solutions and can carry longer sales cycles.

According to Grabscheid, large security incidents can accelerate buying decisions because enterprises may access what he described as an “incident budget” to address immediate risks. He said JFrog recorded security-related customer activity in the fourth quarter, first quarter and second quarter following such events.

AI Customers and Hybrid Deployments

Grabscheid also discussed JFrog’s growing presence among AI foundation-model labs. He said the company now serves four of the top five foundational labs, though he did not name the full group. He said the customer base provides a blueprint for JFrog in a newer market category beyond its traditional presence in industries including automotive and financial services.

One recent AI customer win involved a competitive displacement and a hybrid deployment, according to Grabscheid. He said some foundation-model companies initially adopted self-hosted deployments because they operate their own data centers and seek control over their environments. The new customer, however, placed its core deployment in the cloud while extending operations to self-hosted environments at the edge.

Grabscheid said JFrog’s ability to support both cloud and self-hosted environments differentiates it from vendors that focus on only one deployment model.

He also addressed an OpenAI Hugging Face-related incident, saying JFrog responded quickly and transparently and worked with the customer on remediation and patches. Cloud customers were immediately covered, he said, while self-hosted customers need to download updates to receive patches for a vulnerability. Grabscheid said the event also highlighted a potential opportunity to move more customers toward cloud and SaaS deployments.

Managing Internal AI Costs

While AI tools have improved engineering productivity, Grabscheid said their costs have become a distinct budget line for JFrog. The company has shifted from tools such as Copilot and Cursor toward Claude in some cases, he said, adding that both productivity gains and spending have risen substantially.

JFrog has managed the increased spending by reviewing planned research-and-development hiring and using discretionary budgets, while continuing to invest in innovation, Grabscheid said. He said the company is also evaluating model routing, caps on spending for certain organizations, and other methods to optimize AI-related expenditures.

JFrog introduced Boost, a community-focused offering aimed at helping users optimize AI tool usage. Grabscheid said the offering is not being released primarily for monetization because the AI market is changing rapidly. Initially focused on reducing the number of lines generated, Boost has evolved toward directing workloads to appropriate models and supporting orchestration, he said.

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.