How to use AI for competitive intelligence without drowning in alerts
Let a model do the reading and the first sort, keep people on the decisions, and wire the summaries into Slack, webhooks or an MCP-connected agent.
By ClaudeGPT Si Newsroom, Editorial team
3 min read
Here is how to use AI for competitive intelligence: hand it the reading and the first sort, and keep the judgment for a person. Point an AI monitor such as AyeWatch at the pages and topics that matter, write the rule in plain English, and send the summaries to where your team already works. Below is that setup in five steps, including the API and MCP options a developer will want.
Where AI helps, and where it does not
A model is good at the dull part of the job: re-reading the same pricing pages, changelogs and press rooms, ignoring a restyled header, and writing two sentences about what actually moved. The big platforms use it for the same reason. Crayon's site lists AI news summaries and AI importance scoring, Kompyte advertises AI Daily Summaries, Klue has a Compete Agent, and Visualping puts an important-or-not flag on every change.
A model is bad at deciding what a change means for your roadmap, and it can misread a page. Treat every alert as a pointer to the source, not as the source.
| Task | Let AI do it | Keep a person on it |
|---|---|---|
| Re-reading pages and news | Yes | |
| Skipping cosmetic edits | Yes | Check the first few alerts |
| Summarizing the change | Yes | Open the source before quoting it |
| Deciding the response | Yes | |
| Updating battlecards or the pitch | Yes |
Step 1: pick the sources
For each competitor, start with the pages that change when the business changes: pricing, changelog or release notes, docs, careers and the press page. Add the places where news breaks first, such as the company's LinkedIn company posts, its X account, or a subreddit where your users compare tools. Three to five pages per rival is enough to begin.
Step 2: write the rule like a message to a colleague
Keyword alerts fail because the words you care about appear on every visit. A plain-English rule describes the change itself:
Tell me when plan names, prices or seat limits change.
Skip layout, banner and testimonial edits.
In AyeWatch, you paste the URL, add a rule like this one, and it compares the page by meaning. For topics that span many sites, describe them the same way, for example "new integrations or partnerships announced by Acme".
Step 3: route the alerts
Push notifications and the in-app feed come with every AyeWatch plan. Paid plans add email, Slack, Discord and webhooks, and you choose the channel per topic. A practical split: pricing changes to the sales channel, changelog and docs changes to product, everything else to a daily digest.
Step 4: script it with the API or MCP
Every paid plan includes a REST API to create, list, update and delete topics, and signed webhook events that carry the AI summary, so you can pipe alerts into your own tools. There is also an MCP server at https://ayewatch.ai/api/mcp, so an AI assistant that speaks the Model Context Protocol can create, change or pause monitors for you. Ask it to "watch the release notes at this URL and tell me when a new version ships" and it sets the monitor up.
Pricing starts with a Free Preview and no card, then paid plans from $9 a month as of November 2026.
Step 5: prune every week
After the first week, look at which alerts led to an action. Tighten the rule on any monitor that fired on noise, delete the ones nobody read, and add the source you wished you had been watching. Ten good monitors beat fifty ignored ones.
When to add a full platform
If a sales team needs maintained battlecards and win-loss reporting, a platform like Crayon or Klue is built for that and an alert tool is not. Many teams keep both: the AI monitor tells someone a change happened, and the platform holds the updated card.