Protect AI pricing in 2025: A complete breakdown & key considerations

As more and more businesses jump into using AI, they’re also discovering a whole new world of security risks. Platforms like Protect AI are built to secure AI models from top to bottom, but figuring out what you’re actually buying, and how much it’s going to cost, can be a bit of a headache.

Many of the big players in the AI space have an enterprise-first, "contact us for a demo" pricing model. It’s a common approach, but it often leaves teams like yours in the dark. You’re left wondering about the potential cost, how long it’ll take to get started, and what you’re really getting for your money.

This guide is here to clear things up. We’re going to break down the Protect AI platform, its features, and its pricing model using all the publicly available information we could find. We’ll also explore what this all means for your team and highlight some things to think about when you’re choosing any new AI tool.

What is Protect AI?

Protect AI is a security platform built specifically for artificial intelligence (AI) and machine learning (ML) systems. The main idea is to help companies see, understand, and manage security risks across the entire lifecycle of their AI projects. Think of it less as a tool for people using off-the-shelf AI and more as a security toolkit for the teams actually building and deploying it.

The platform is made up of a few different products that work together to secure everything from the third-party models you download to the custom apps you build yourself. It’s all built on a few core pillars:

• Guardian: For scanning and securing your AI models.

• Recon: For stress-testing your AI applications with red teaming.

• Layer: For monitoring and protecting your LLMs while they’re running.

• Radar: For getting a bird’s-eye view of your overall AI security.

Protect AI is really geared toward enterprise-level security and ML teams who are deep in the trenches, building or fine-tuning their own AI systems and need a serious framework to keep everything locked down.

A deep dive into the features that influence Protect AI pricing

Before we talk numbers, it helps to understand what the platform actually does. Protect AI is broken down into a few key products, each handling a different part of the AI development and deployment puzzle.

Guardian: Proactive model security and scanning

Guardian basically acts as a bouncer for any AI models your team wants to use. It automatically scans models from public sources (like Hugging Face) and your own private models to check for vulnerabilities, malicious code, or other sketchy stuff.

Let’s say your data science team gets excited about a new open-source model they want to try. Before that model gets anywhere near your company’s data, Guardian gives it a full scan to make sure it hasn’t been messed with. It’s all about stopping a potential supply chain attack before it even gets a chance to start.

Recon: Automated AI red teaming and application testing

Think of Recon as an automated penetration testing tool that’s been trained to think like a hacker trying to break your AI. It hammers your AI applications with tests for things that traditional security tools would probably miss, like prompt injections, jailbreaks, and data leaks.

Before you roll out that new customer-facing chatbot, you’d unleash Recon on it to simulate all sorts of attacks. This helps you find and patch up weaknesses that could be exploited, so you can be sure your app is solid before it ever talks to a real customer.

Layer: Real-time runtime monitoring and control

Layer is your on-the-ground defense for live AI applications. It sits in front of your large language models and keeps an eye on the prompts and responses flowing back and forth in real-time, ready to block threats as they pop up.

So if someone tries to trick your AI into coughing up sensitive company info, Layer would spot the malicious pattern, block the prompt and the potentially dangerous response, and stop a data breach right then and there.

Radar: Centralized AI security posture management

Radar is the command center for your entire AI security setup. It gives you a complete "AI Bill of Materials" (AI BOM) and a high-level dashboard so security leaders can get a clear picture of all their AI assets and any associated risks.

A Chief Information Security Officer (CISO) could use Radar to get a quick snapshot of the risk level for every AI app in the company, track vulnerabilities, and make sure everything is sticking to the company’s security policies.

This video explores the security challenges in AI that traditional security tools might miss, directly relevant to understanding the value proposition behind Protect AI pricing.

Understanding Protect AI pricing

Alright, let’s get to the question you’re probably here for. Based on all the information on their website, their AWS Marketplace listing, and other review sites, Protect AI does not have public, tiered pricing.

Instead, Protect AI operates on a custom enterprise pricing model. You won’t find a pricing page with different plans and features listed. To get a quote, you have to get in touch with their sales team for a consultation to build a custom plan that fits your company’s specific needs.

What the "contact for pricing" model means for you

This isn’t an unusual approach in the enterprise software world, but it has some real implications you should know about before you dive in.

• You can’t see the price: Without a public price list, you can’t easily compare costs or even make a rough budget without getting on the phone with a salesperson. This makes the initial research and planning phases a lot harder.

• It’s going to take a while: This model is set up for a consultative sale. You should expect to have multiple calls, watch demos, and go through a needs assessment before you even get a number. This can really slow down the whole process of buying and implementing a tool.

• It’s probably not cheap: A "contact us" button is usually a sign that a solution is built for large companies with big budgets. It’s generally not a great fit for smaller teams or businesses looking for a straightforward solution they can start using today.

• Costs can be unpredictable: Enterprise pricing is often tied to custom metrics, like how many models you scan, apps you monitor, or API calls you make. This can make it tricky to forecast your spending as your AI use grows, which can lead to some unpleasant budget surprises later on.

Feature	Custom/Enterprise Pricing (Protect AI)	Transparent/Tiered Pricing (eesel AI)
Transparency	Low --- You have to talk to sales for any price info.	High --- Public pricing page with clear plans.
Onboarding Speed	Slow --- Could take weeks or months.	Fast --- Self-serve setup in minutes.
Budget Predictability	Low --- Custom metrics can be hard to forecast.	High --- Fixed monthly or annual costs.
Ideal Customer	Large enterprises with complex needs.	SMBs and mid-market teams looking for value and speed.

Key considerations when choosing an AI platform

The price tag is just one piece of the puzzle. The true cost and your overall experience depend on a lot more than a simple feature list. Here are a few important things to think about when you’re looking at any AI tool, whether it’s for security or customer support.

Implementation complexity and total cost

Deep security platforms like Protect AI are definitely powerful, but they often require specialized security expertise and a good chunk of engineering resources to get them integrated and running smoothly. This is a hidden cost, both in time and people, and it can mean waiting a lot longer to see a real return on your investment.

Not all AI tools have to be that complicated, though. For example, some customer support platforms like eesel AI are designed to be completely self-serve. With one-click integrations for helpdesks like Zendesk and Freshdesk, teams can connect their tools and get started in minutes, not months, without having to rope in the engineering team. This approach is all about getting you value right away.

The eesel AI platform showing how easy it is to connect to various helpdesks and knowledge sources, which is a factor to consider beyond just Protect AI pricing.

The importance of testing

Deploying any new AI system without testing it first is a gamble. How can you be sure it will work the way you expect when it’s live? For a security tool, a mistake could be a disaster. For a support tool, it could lead to a terrible customer experience that hurts your brand.

It’s always a good idea to look for platforms that give you a sandbox environment where you can test things out safely. eesel AI, for example, provides a powerful simulation mode that lets you test your AI agent on thousands of your own past support tickets. You can see exactly how it would have replied, get solid forecasts on its resolution rates, and tweak its behavior before it ever interacts with a single customer. This kind of risk-free approach is a huge help for building trust in your AI and making sure your launch goes smoothly.

A screenshot of the eesel AI simulation mode, a feature that offers a risk-free testing environment, contrasting with the considerations needed for Protect AI pricing.

Securing customer interactions

Securing the AI model itself is obviously important (and that’s Protect AI’s focus), but it’s just as critical to control what your AI says and does when it’s talking to customers. An AI can be technically secure but still give out wrong information, go off-brand, or just create a frustrating experience for users.

This is a different kind of "AI security" that’s more about governance and quality control. Platforms like eesel AI tackle this by letting you set up scoped knowledge. This means the AI will only pull answers from approved places, like your help center, Confluence, or other internal documents. You can also customize the AI’s personality and what it’s allowed to do, making sure every single interaction is helpful, on-brand, and safe.

An image of eesel AI's customization settings, showing how teams can control AI behavior, an important consideration beyond Protect AI pricing.

A holistic view of AI security, value, and pricing

Protect AI offers a powerful, heavy-duty platform for securing the entire AI/ML lifecycle. But its custom pricing and the likely complexity of setting it up make it a better fit for large organizations with dedicated security and engineering teams who have the time and resources for a long procurement and implementation process.

When you’re looking at any AI platform, it’s so important to look beyond just the features. Think about the total cost of ownership, how fast you can get up and running, and whether the pricing is transparent. The best tool isn’t always the one that solves your problem on paper, but the one that fits your team’s budget, resources, and timeline.

Looking for an AI tool that’s built differently?

While Protect AI focuses on securing your backend models, eesel AI is designed to securely automate and improve your customer-facing support.

We believe in a different approach:

• Transparent & predictable pricing: Our plans are public, with no hidden fees. What you see is what you get.

• Go live in minutes: You can set everything up on your own with our truly self-serve platform. No mandatory demos or sales calls needed.

• Test with confidence: Use our simulation mode to check performance and get your team on board before you launch.

• Unify your knowledge: Instantly connect to your helpdesk, Google Docs, Slack, and more to give your AI all the context it needs.

Ready for an AI platform that’s powerful, secure, and actually easy to use? Start your free trial of eesel AI today.