GitLab Inc. (NASDAQ: GTLB) will release its second-quarter earnings report after the closing bell on Tuesday, Sept. 1.

Analysts expect the San Francisco-based company to report quarterly earnings of $0.18 per share, down from $0.24 per share in the year-ago period. The consensus estimate for GitLab’s quarterly revenue is $273.36 million, compared to $235.96 million reported last year, according to Benzinga Pro data.

Analyst Revisions

Several analysts have recently adjusted their outlook for GitLab, with most raising price targets while maintaining their existing ratings.

Strategic Developments

On June 10, GitLab expanded its partnership with Alphabet Inc.’s (NASDAQ: GOOGL) Google Cloud. The company launched a fully managed GitLab offering designed for enterprises with strict data sovereignty and compliance requirements.

Shares of GitLab rose 3.7% to close at $46.54 on Monday.

What the Numbers Show

The consensus revenue estimate of $273.36 million implies a year-over-year growth of approximately 15.9% from the prior year’s $235.96 million. This top-line expansion contrasts with an expected decline in per-share earnings, which are forecast to drop 25% from $0.24 to $0.18. This divergence suggests that while revenue is growing, profit per share may be under pressure from increased share count or higher operating costs, as the revenue growth rate does not offset the drop in earnings per share.

GitLab Inc. has released its Dedicated AI Gateway, enabling regulated enterprises to run agentic AI workloads within single-tenant environments. The update addresses data residency concerns by keeping AI-processed data inside existing security boundaries.

Dedicated AI Gateway

The AI Gateway for GitLab Duo Agent Platform is now generally available. It allows customers running sensitive software delivery workloads on GitLab Dedicated to execute the agent platform within their specific region. Users can connect their own models for inference without moving data outside their trusted infrastructure.

This capability targets audited environments where standard multi-tenant AI services may not meet compliance requirements. The gateway ensures agentic workloads follow the same isolation model as the rest of the software development lifecycle.

Secrets Manager Expansion

GitLab Secrets Manager is now in limited availability as a paid add-on billed through GitLab Credits. It securely stores credentials used both inside CI pipelines and by external infrastructure tools like Kubernetes, Terraform, and OpenTofu.

Every secret is scoped to the environment, branch, and protection status of the job requiring it. This unified permission model eliminates the need for separate credential management systems outside the platform.

Security Remediation Automation

Bulk SAST False Positive Detection and Agentic SAST Vulnerability Resolution are now in beta. These features allow security teams to triage thousands of open vulnerabilities in a single action.

The system provides a confidence score for each finding. Confirmed risks receive ready-to-merge fixes, reducing manual coding effort. The tool continues to automatically triage new critical and high-severity findings as they arrive.

Flow Creator Agent

Flow Creator Agent, now generally available, converts plain language descriptions into complete, runnable custom flows. This removes the need for users to learn the Flow Registry schema manually.

Flows generated via Agentic Chat run under scoped service accounts with composite identity. Enabling these flows requires the Maintainer role or higher, ensuring administrative control over automation deployment.

Additional GitLab 19.3 Features

GitLab Credits usage caps are now generally available. Administrators can set monthly ceilings on agentic AI spend at the subscription level or per user via the GraphQL API. This prevents unexpected overages in AI consumption costs.

Restricted visibility for custom agents and flows per GitLab group is also generally available. This makes assets accessible to members across multiple projects within that group, supplementing existing per-project and public visibility options.

What the Numbers Show

The simultaneous release of usage caps alongside new agentic AI features indicates a strategic focus on cost predictability. By allowing granular control over GitLab Credits spend, GitLab addresses a primary barrier to enterprise adoption: unbounded AI inference costs. This suggests the company is prioritizing financial governance tools to accelerate uptake among budget-conscious regulated sectors.