How do you protect your data when using AI in Gradient AI?
Here’s what you need to know around the AI risk.
We assess each vendor’s AI risk posture using 26 risk vectors mapped to leading frameworks like OWASP for LLM. This page will show a high-level snapshot of some information for each vendor. For the full, vendor-specific AI risk report, click the image below.
Feature Overview
Each vendor provides a unique set of features, and implements AI in certain ways. Let's see what types of AI features they have to offer:
Gradient AI |
|---|
Supports agent versioning, insights, and citation tracking for transparent, scalable AI agent development—enabling insurers to build complex, real-time decision support tools. |
… see more in full report |
Want to see all AI features?
Pricing Details
Let's dive into the relevant pricing details for accessing AI, as providers vary widely in their pricing models and cost drivers.
Vendor | Description | Gradient AI |
|---|---|---|
Freemium | Offers free tiers | |
Per License | Charges per user, org, or access point | |
Consumption-Based | Pay per taken, API call, inference, etc. | |
Outcome-Based | Pay only when certain results or performance goals are achieved |
Some Quick facts about each vendor
Here are some facts about Gradient AI
Gradient AI |
|---|
Gradient AI specializes in providing advanced machine learning and generative AI solutions tailored for insurance (workers' comp, health, group benefits, and property/casualty) risk assessment and automation. |
Gradient AI offers true consumption-based billing — organizations pay based on API calls, tokens processed, or knowledge base storage/usage. The pricing is aligned with AI/ML inference and data processing volume, not number of users. |
Gradient's AI models are accessed via cloud APIs, with open support for commercial and open-source LLMs, making it easy for carriers and partners to embed AI directly into their digital or legacy insurance workflows. |
If your app pulls in third-party content — like URLs, comments, or files — LLM features can be tricked into leaking private data through indirect prompt injection. Most teams don’t even realize it’s happening.
According to a 2025 Gartner survey,
73%
of enterprises have suffered an AI-related security breach in the last year
$4.8M
average cost per incident — with indirect prompt injection and data leakage via LLMs now among the top attack vectors for financial services and healthcare organizations
In recent incidents, platforms like ChatGPT and Microsoft 365 Copilot were exploited by attackers using hidden prompts and indirect content injection, leading to unintended data exposure
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