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Building a competitive intelligence tool? A research platform? A compliance monitoring product? Whatever your application, if it would benefit from real-time web monitoring capabilities, you have two choices: build the AI-powered monitoring infrastructure yourself, or embed it using an API. For most product teams, the build-vs-buy calculus heavily favors embedding. Here's how to do it with the AyeWatch API.
Why Embed Instead of Build?
Building production-grade AI monitoring is a significant undertaking, years of engineering effort to get right, and continuous investment to maintain as the web evolves. The result users expect is demanding: comprehensive coverage, intelligent noise filtering, accurate summaries, and reliable delivery across multiple channels.
The AyeWatch monitoring platform represents exactly that level of investment, battle-tested, continuously improved, and available via API the moment you're ready to build. Embedding it means you get world-class monitoring capabilities immediately, at a fraction of the cost of building from scratch, while we handle the ongoing evolution of the underlying intelligence.
The Embedding Architecture
Embedding web monitoring into your product via the AyeWatch API typically follows this architecture:
- Topic creation on behalf of users: When a user in your application specifies what they want to monitor, your backend calls the AyeWatch API to create a monitoring topic. The topic is created under your AyeWatch account, but represents a user-specific monitoring configuration.
- Webhook delivery to your application: You configure AyeWatch to deliver alerts via webhook to your application's endpoint. All alerts for all your users arrive at this single endpoint, tagged with the topic ID that identifies which user and monitoring configuration triggered the alert.
- Alert routing in your application: Your webhook handler receives the alert, identifies the associated user from the topic metadata, and routes the alert through your application's notification system, whether that's in-app notifications, email, a custom dashboard, or whatever channels your product supports.
- Topic management lifecycle: As users create, modify, and delete their monitoring configurations in your application's UI, your backend makes the corresponding API calls to create, update, and delete AyeWatch topics.
Building the User-Facing Configuration Experience
One of the key design decisions when embedding monitoring is how to present the configuration experience to your users. You can expose the full flexibility of AyeWatch monitoring topics (URL monitoring, topic descriptions, check intervals, sensitivity settings), or you can build a simplified interface tailored to your specific use case.
Many products take the simplified approach: instead of exposing "monitoring topics" as a concept, they present the capability in terms specific to their domain. A competitive intelligence tool might call them "competitor watches." A research platform might call them "literature alerts." A compliance product might call them "regulatory monitors." The AyeWatch API powers all of these, but the user experience is entirely yours to design.
Credit and Quota Management
When embedding AyeWatch monitoring at scale, credit management becomes important. Each monitoring check consumes credits, and your AyeWatch plan determines your monthly credit allocation. When building a multi-tenant application, you'll need to make decisions about how credits are allocated across your users, whether all users share a pool, each user has their own allocation, or credit consumption is unlimited (if you're on an appropriate plan).
The AyeWatch API provides endpoints for querying current credit usage, enabling you to build quota management into your application, preventing individual users from consuming disproportionate shares of your monitoring capacity.
Example: A Competitive Intelligence SaaS
Imagine building a competitive intelligence SaaS for e-commerce brands. Your product lets users add competitor URLs (pricing pages, product listings, promotional pages) and receive alerts when those pages change. The entire monitoring infrastructure is powered by AyeWatch under the hood:
- User adds a competitor URL in your UI → your backend creates an AyeWatch monitoring topic via API
- AyeWatch detects a change → delivers an alert via webhook to your endpoint
- Your application receives the webhook, identifies the user, and creates an in-app notification
- User receives the alert in your product UI, with your branding and your custom context about why this competitor matters
Your users never know AyeWatch exists, they see your product, your brand, and your experience. You get world-class monitoring infrastructure without building it yourself.
Getting Started
API access for embedding monitoring in your product is available on the Pro+ plan at $19/month. For higher-volume embedding use cases and enterprise applications, contact us about enterprise pricing that scales with your product's growth.
The API documentation covers all the endpoints you need to implement the embedding architecture described above, with code examples in multiple languages.
Basically,
Embedding web monitoring capabilities into your product is dramatically faster and more cost-effective than building the infrastructure yourself. The AyeWatch API gives you the full power of AI-powered monitoring as a building block for whatever you're creating.
Start with AyeWatch and ship your monitoring-powered product faster than you thought possible.