Taming the Wild West of Enterprise AI with AI Gateways (A FinOps Perspective)

A FinOps Perspective from Asaf Liveanu, CPO at Finout

The enterprise embrace of AI today feels like the Wild West—untamed, fast-moving, and filled with promise… and risk. Generative AI tools, LLM APIs, and experimentation are spreading across companies at record pace. But with that speed comes chaos: engineering teams spinning up OpenAI keys without governance, marketing testing prompts through shadow accounts, and finance teams blindsided by token-based billing spikes they never saw coming.

It’s not just speculation—studies confirm that over 40% of employees use generative AI tools without employer approval, and nearly 90% of enterprise AI consumption happens without formal oversight. This level of decentralization is unsustainable. Enterprises can’t scale AI responsibly if they don’t even know where or how it’s being used.

As the Chief Product Officer at Finout—where we live at the intersection of innovation and cloud cost governance—I see this pattern across industries. That’s why AI Gateways have become a critical component of the modern tech stack.

An AI Gateway is essentially a control plane for AI consumption. Like an API gateway in the microservices era, it routes and manages all LLM and AI API calls in one centralized place. It offers authentication, access control, cost tracking, logging, and model abstraction across providers. In short, it allows enterprises to unlock the potential of AI—without losing visibility, security, or fiscal control.

Without a gateway in place, you’re dealing with:

• 🔐 API key sprawl, where secrets are passed around Slack and GitHub like trading cards.
  
  
• 💸 Uncontrolled spending, with pay-per-token bills escalating overnight.
  
  
• 🔄 Vendor lock-in, where every app is hardcoded to a specific provider.
  
  
• 📉 Zero accountability, because no one knows who used what—or why.

AI gateways offer a remedy. They allow IT, security, and FinOps teams to sleep at night while letting developers build at speed. They’re not roadblocks; they’re onramps—with the right guardrails.

5 Tools Defining the AI Gateway Market

As AI adoption surges, the gateway market is growing fast. Here are five standout platforms making real impact:

1. Databricks AI Gateway

Blending model orchestration with unified data governance, Databricks’ gateway provides deep integration with its enterprise data platform. It supports routing across LLMs, prompt versioning, and centralized permissions via Unity Catalog—ideal for teams already embedded in the Databricks ecosystem.

2. Azure OpenAI + API Management

Microsoft’s AI Gateway is built atop Azure’s powerful API Management layer. Organizations can wrap OpenAI calls with native Azure security, enforce cost center tagging, and monitor usage by app or identity. For enterprises already on Azure, this is a seamless and secure fit.

3. Cloudflare AI Gateway

Built for edge-native deployment, Cloudflare’s gateway emphasizes low latency, global routing, and security. It includes observability features, rate limiting, and cost controls. Its differentiator? Performance at scale—ideal for customer-facing AI apps.

4. Portkey.ai

Portkey takes a developer-first approach. With built-in multi-provider access, prompt caching, and usage analytics, it’s a go-to for startups and product teams looking to avoid vendor lock-in without building everything from scratch.

5. Domino Data Lab AI Gateway

Designed for highly regulated or data-sensitive environments, Domino’s gateway focuses on secure credential vaulting, role-based access, and governed model experimentation. It empowers data science teams to innovate with control.

These tools offer varying strengths—some lean into observability, others into developer UX or compliance—but they all recognize the same truth: AI adoption at scale demands structure.

AI Gateways: The FinOps Linchpin

From a FinOps lens, AI gateways are not just operational tools—they're strategic enablers. GenAI has flipped the script on how organizations consume compute. Unlike infrastructure spend—which is tied to VMs or workloads—AI consumption is ephemeral, often priced by token or request.

That’s where AI gateways deliver unmatched FinOps value:

🔍 Real-Time Cost Visibility

Gateways become the single source of truth for AI usage across teams. They track usage per user, team, model, or endpoint—enabling true cost attribution. Imagine being able to say: “Marketing used 60k tokens on GPT-3.5 this week testing email subject lines.” That’s FinOps gold.

🚦 Cost Controls and Budget Guardrails

Want to cap spend for your customer success team at $2,000/month? Gateways let you do that—enforcing budgets, setting alerts, and throttling usage before budgets are blown. No more end-of-month surprises. You see it. You act on it. Early.

🧰 Governance That Drives Efficiency

Policy enforcement through the gateway ensures smart usage. Want to block the use of GPT-4 for staging environments? Done. Require tagging for every prompt? Easy. Route embedding calls to an open-source model internally before paying $0.01/token externally? Absolutely. These governance levers reduce waste and increase ROI.

📦 Optimization Through Model Abstraction

Gateways enable experimentation: route the same prompt to Claude and GPT-4, compare output quality and cost, then standardize on the most efficient. They empower teams to A/B test with spend in mind—critical for sustainability.

🤝 Engineering + Finance Collaboration

With shared dashboards and cost telemetry, gateways foster real-time collaboration. Instead of waiting for a bill, FinOps teams and engineering leaders work from the same source of insight—solving issues together, proactively.

At Finout, we believe this is how FinOps should work in the AI era: continuously, collaboratively, and close to the point of consumption.

From Chaos to Clarity: Why Every Enterprise Needs an AI Gateway

As someone who bridges the worlds of engineering and FinOps daily, I view AI gateways as a non-negotiable. They don’t slow innovation—they make it sustainable.

In a world where AI is embedded in every product, department, and conversation, an AI gateway acts as your observability and control layer. It allows developers to explore, test, and deploy AI features without wondering if they’re duplicating efforts or incurring surprise charges. It gives FinOps leaders the insight to guide budgets and improve efficiency without chasing mystery invoices.

AI Gateways are the sheriff in the generative AI town. They turn a free-for-all into a fast-moving, well-paved system. With one in place, companies can embrace the future of AI—confident that their costs, data, and innovation remain in harmony.