We are excited to announce the launch of Levo’s AI Gateway, an end-to-end governance layer for third-party AI usage within enterprises.
Levo’s AI Gateway gives enterprises visibility and control over employee use of third-party AI tools like ChatGPT and Gemini. It helps you discover AI usage, prevent sensitive data from leaving the organization, enforce approved providers, and create audit-ready evidence.
Therefore enabling enterprises to fully embrace third-party AI by removing the security and compliance barriers that slow adoption.
In 2024–2025, surveys indicate that ~92% of Fortune 500 firms already use generative AI in some form.
The reason is simple. Third-party AI delivers immediate productivity gains, faster decisions, stronger customer engagement, and faster execution across software and operations.
But the risk is just as real. 80% of organizations report negative data incidents, and 90% are concerned about shadow AI, with 46% extremely worried.
Some enterprises respond by slowing adoption, restricting tools, or banning usage. That reduces benefits, not risk.
Reducing third-party AI usage is no longer an option. Levo’s AI Gateway offers a sustainable path through governed use, so AI benefits are accelerated while risk is controlled by design.
How Levo's AI Gateway Governs Third-Party AI Usage
Third-party AI is not adopted as a centralized enterprise program. It is adopted as a personal assistant.
Budgets follow the same pattern. They are distributed across departments, not centralized in IT, which makes governance an operating model problem, not a one time tooling decision.
Levo’s AI Gateway provides end to end governance for this reality, so enterprises can enable third-party AI broadly without accepting unmanaged risk.
Discover: Shadow AI Visibility and Tool Inventory
AI usage spreads across functions because teams choose tools that fit their daily work. The result is AI sprawl. In a large enterprise, self reporting cannot keep pace with this adoption. Inventories lag behind reality. Levo discovers third-party AI usage across providers and AI-enabled SaaS tools, and builds an accurate baseline before enforcement begins.
Understand: Identity- and Context-Aware Governance
Visibility alone does not create governance. Leaders need accountability. That requires knowing who used which tool, and in what business context. Levo ties AI usage to identity and context such as team, function, application, environment, and region, so AI activity becomes trackable and governable.
Control: Segmented Policy Enforcement by Function and Region
AI risk is not evenly distributed across the enterprise. Regulated functions and customer-data workflows carry different constraints. A single global policy forces a bad choice. It either restricts everyone or protects no one well.
Levo enables segmented enforcement by function, business unit, and region, so AI is enabled where it is appropriate and constrained where it is not.
Protect: Outbound Data Security for Third-Party AI
Third-party AI becomes more valuable when employees provide context. That context often includes sensitive data. Once that data is sent to an external tool, the enterprise loses control over where it persists and how it is reused. Levo inspects outbound prompts and attachments and applies policy actions so sensitive data never leaves the organization as AI context.
Assure: Inbound Output Safety Controls
Risk is not limited to what employees send. It also includes what the model returns.
Unsafe, inaccurate, or non-compliant outputs can propagate quickly into documents, tickets, and customer communication. Levo applies controls to third-party AI responses before they enter enterprise workflows, reducing downstream reputational and compliance exposure.
Govern Access: Approved Providers and Centralized Credentials
When AI adoption is unmanaged, access becomes fragmented. Teams create accounts, distribute keys, and accumulate shadow spend. Over time, policy turns into guidance rather than control.
Levo enforces approved providers and centralizes credentials, so access becomes standardized, auditable, and enforceable.
Optimize: Spend, Quotas, and Usage Controls
AI adoption scales quickly because it reduces friction in daily work. Costs scale the same way. Without guardrails, spend becomes unpredictable and difficult to allocate across teams.
Levo applies quotas and usage controls to prevent runaway consumption and to make AI spend measurable, predictable, and attributable.
Prove: Audit, Evidence, and Compliance Readiness
Governance must be defensible, not implied. Without a record of usage and enforcement, policy cannot be proven. Levo generates audit-ready logs and compliance artifacts showing who used which tools, when, and under which controls.
Centralize: Provider Credential Management
Third-party AI becomes hard to govern when credentials are distributed across teams. That fragments access and makes enforcement inconsistent. It also makes auditing unreliable.
Levo centralizes provider credentials in the gateway, so employees and internal systems do not need to hold tokens, and access can be enforced by policy.
Extend: Governance Beyond LLMs to AI-Enabled SaaS Tools
Third-party AI is not limited to chat tools and model APIs. It increasingly lives inside AI-enabled SaaS platforms used across the business.
Those tools can trigger outbound actions and data movement, often as part of chained workflows. Levo extends governance to AI-enabled SaaS usage by enforcing approved destinations and outbound action boundaries at the gateway.
Constrain: Agent Tool Actions and Destinations
Agents do not only plan workflows, they take actions by calling external tools on a user’s behalf. Without guardrails, the same tool call can send the right data to the wrong destination, or execute the wrong action with the right intent.
Levo constrains outbound tool use with policy boundaries such as destination allowlists and parameter restrictions, so agent-driven actions remain within approved limits.
What Makes Levo’s AI Gateway Enterprise Grade
Levo’s AI Gateway is built around what enterprises care about most: scaling third-party AI adoption without losing control over data, access, and accountability.
- Programmable guardrails that keep pace with the business (YAML + WASM)
Levo lets enterprises define clear guardrails in YAML, then use WASM when real-world exceptions require logic. For example: allow marketing to use ChatGPT for campaign drafts, but redact customer identifiers if pasted in. Allow engineering to use AI for refactoring, but block secrets and credentials from ever being sent as context.
- Identity- and context-aware enforcement that matches enterprise reality: Levo applies policy based on who is using AI and where it sits in the business. For example: finance can use approved tools for summarization, but cannot send regulated data types. Engineering can use approved coding assistants, while contractors are restricted to a narrower set of tools. EU teams can be constrained to region-appropriate providers, while US internal teams may have broader access.
- Fast rollout without endpoint agents, across every AI entry point: In large enterprises installing and maintaining agents on employee devices is not practical. Levo captures third-party AI usage centrally, so coverage does not depend on device installs or user cooperation. The result is immediate governance across web-based LLM tools and AI-enabled SaaS workflows, without a device by device rollout.
With these provisions, employees keep the speed that makes AI valuable, while the enterprise keeps control over what can be shared and what can be used.
AI Gateway Built for Enterprise Deployment
Levo’s AI Gateway is designed for enterprise deployment without introducing friction into employee workflows or existing systems. It operates centrally, without endpoint agents, and governs third-party AI usage without slowing requests or degrading the user experience, even at high scale.
Unlike Python-based AI gateways that rely on interpreted runtimes and web frameworks, Levo is built on a compiled, systems-grade execution model designed for sustained throughput and predictable latency. This avoids the performance overhead, concurrency limits, and memory pressure that often cause AI gateways to become bottlenecks under real enterprise load.
Crucially, Levo does not export sensitive prompts, responses, or usage data into a vendor cloud for analysis. Inspection and enforcement remain within the customer’s environment, preserving data ownership and regulatory boundaries.
The result is AI governance that scales without introducing latency, encouraging bypass, or forcing tradeoffs between performance and control.
Speak to en engineer today to adopt third-party AI without losing control.
