Tailscale announced Aperture in open alpha, a governance layer that helps organizations adopt AI across both employees and agents. Aperture provides centralized policy controls, audit-ready session histories, and safer handling of provider credentials, so teams can move fast with AI while reducing data leakage and improving compliance posture.
Recent analysis of workplace AI usage found 34.8% of corporate data employees put into AI tools is sensitive, and that source code is the most common category of sensitive data going into AI. Separately, a global study led by the University of Melbourne with KPMG found 48% of all workers reported uploading sensitive company data into public AI tools. Cisco Talos reported 1,100+ publicly exposed Ollama LLM servers, noting it took minutes to identify most of them.
Roll out AI faster while bringing usage into focus
As AI shifts from occasional chat usage to always-on coding assistants and autonomous agents, organizations need guardrails that keep up. Aperture by Tailscale is designed to help teams move from experimentation to production AI workflows with identity-linked policy controls, audit-ready visibility, and centralized provider key custody.
Tailscale already secures connectivity across an organization with access based on identity. Aperture builds on that foundation by extending identity into AI usage, so requests are attributable to a known user or workload identity, with logs and controls that support audit and governance. Aperture’s gateway model also means organizations no longer have to distribute provider API keys to developer machines, containers, and agent runtimes.
Key capabilities include:
- Identity-linked attribution and policy enforcement: Tie AI access and activity to a user or workload identity, so policies and audit trails clearly reflect who initiated each request.
- Quick setup for developers: Deploy Aperture in an existing tailnet and point compatible coding agents at it with a one-line configuration change.
- Centralized API key custody and identity-based usage tracking: Keep provider API keys in Aperture, and associate usage with user or workload identity to reduce key sprawl and improve auditability.
- Full session histories with tool-call visibility: Capture LLM session histories and extract tool calls and related activity for review and investigation.
- Export to security tooling: Export logs and events to a SIEM for monitoring, retention, and compliance workflows.
- Broad provider support and tool compatibility: Route AI traffic to hosted providers and self-hosted model endpoints, and work with coding agents and frameworks that support a configurable base URL.
As organizations move from experimentation to production AI workflows, Aperture provides practical guardrails that make fast adoption easier to manage and harder to regret.
Tailscale is working with partners including Oso, Cerbos, Apollo Research, and Cribl to help customers apply fine-grained authorization and operationalize AI governance using existing security and observability workflows.
“The pressure to adopt AI is forcing organizations to take risks they would never accept elsewhere. Security teams are being asked to approve AI deployments without clear attribution, consistent controls, or audit trails. Tailscale Aperture ties AI usage to identity and provides centralized logging and governance, so companies can adopt AI faster without creating an unmanageable security gap,” said Avery Pennarun, co-founder and CEO of Tailscale.
Customer adoption in private alpha
Early customers are using Aperture during the alpha period and beginning to implement it in production environments, bringing identity-linked governance and audit visibility to AI usage across developer and agent workflows.
Cribl, the data engine for IT and security, has been using Aperture, and is beginning to roll it into production workflows.
“Aperture gives our developers easy access to company-approved AI models and gives us clear visibility into how those models are actually being used,” said Clint Sharp, CEO of Cribl. “We get detailed audit logs out of the box, route them through Cribl Stream, and land them wherever they’re most useful, including Cribl Search. That means our security team gets real observability and control over AI usage without slowing developers down.”
Corelight, a provider of network detection and response (NDR), has been using Aperture to simplify model access and reduce operational overhead for GenAI workflows.
“Aperture provides a single solution to several key sticking points with GenAI workflows. For one, it removes the headache of user API key management; your team just connects to Tailscale and has access to all their models without any other auth flow. It also makes addition of models incredibly easy, allowing your teams to keep up with the newest releases from providers.
Aperture provides a single-pane of glass for metrics with incredible granularity, which provides great data for making decisions on your GenAI spend,” said Louis Gardner, Director, Security Infrastructure & IT at Corelight.
Aperture supports both hosted and self-hosted AI endpoints at launch, including providers such as OpenAI, Anthropic, Google Gemini, Amazon Bedrock, OpenRouter and Vercel, alongside self-hosted endpoints. Aperture works with popular coding agents and agent frameworks where you can configure a custom base URL, including Claude Code, Codex, and Gemini CLI. Aperture is designed for development and production use cases such as governed AI coding assistance, agentic workflows that invoke tools, and AI-enabled automation running in developer environments and CI systems.
Aperture is available starting today in open alpha through waitlist sign-up, followed by a gradual rollout. Customers can request access by joining the waitlist at tailscale.com/aperture.
During the alpha period, Aperture is available at no additional cost across all Tailscale plans, making it easy for teams to evaluate identity-linked AI governance early. Pricing details will be announced as Aperture approaches broader availability.
