Library / Monitoring, Ops & Incidents
Monitoring, Ops & Incidents
Detect funding, layoff, lawsuit, and M&A news for watched companies with Apify, OpenAI
On a schedule, it monitors systems with OpenAI / ChatGPT using Gmail, Google Sheets, Slack, Apify.
What it does
## Detect funding, layoff, lawsuit and M&A news on watched companies with Apify, OpenAI and Slack Watches publisher RSS feeds (and the public GDELT news index when reachable) for the companies and keywords you list, tags business events and headline sentiment, and scores each new article by event type, tone, how many outlets repeat it and how fresh it is. Built for sales trigger-event hunting, PR and comms monitoring, and analysts. ### How it works 1. A daily schedule (or the manual trigger) loads Config; a Monday schedule sends a 7-day report instead. 2. Runs the Apify actor company-news-monitor and downloads the results. 3. Drops incomplete rows and anything already seen in the last 30 days. 4. Score news significance gives a 0-100 rule score; an OpenAI model adds a fit score, verdict and summary. 5. Upserts every row to the News sheet tab. Hot rows go to Slack for approval, warm rows to an email digest. ### Setup steps - [ ] Add an Apify HTTP Header Auth credential (Authorization: Bearer ) on the 3 Apify HTTP nodes. - [ ] Create a Google Sheet with the columns in *Upsert to Google Sheets* and paste its ID into googleSheetId. - [ ] Connect OpenAI, Slack and Gmail; set slackChannelId and digestEmail in Config. - [ ] In Config set actorInput.companies and keywords, timespan (match it to the schedule), priorityEvents (events that should go to Slack), watchSentiment and majorPublishers. Use excludeWords to drop noise such as coupons and sponsored posts. - [ ] Describe your ideal result in aiCriteria, run once manually, then activate. ### Customization - Change the weights in Score news significance. - Needs an Apify account; actor runs use your Apify credits.
The steps
- Daily schedule
- Run manually
- Weekly report schedule
- Config
- Daily run or weekly report?
- Start Apify run
- Wait before polling
- Get run status
- Check run status
- Route by run status
- Stop: Apify run failed
- Fetch dataset items
- Validate and dedupe
- Any new records?
35 steps in total.
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