Understanding AI Summaries
Learn how OpsBrief's AI extracts important events from your team's messages.
How AI Detection Works
1. Message Collection
OpsBrief reads messages from your connected channels via secure API connections.
2. AI Analysis
Our AI model analyzes message content, context, and patterns to identify potential events.
3. Event Classification
Detected events are classified by type (Release, Incident, etc.) and assigned severity levels.
4. Confidence Scoring
Each event gets a confidence score. Only high-confidence events appear in your digest.
What the AI Looks For
The AI is trained to recognize patterns that indicate business-critical events:
- Action verbs: "deployed", "released", "launched", "fixed"
- Version numbers: v1.2.3, 2.0.0, etc.
- Urgency indicators: "incident", "outage", "urgent", severity labels
- Announcement patterns: "announcing", "excited to share", "now available"
- Custom keywords: Your team-specific terminology
Accuracy & Limitations
High Accuracy
Clear, structured messages with explicit keywords
Example: "'v2.3.1 deployed to production successfully'"
Medium Accuracy
Informal announcements with context
Example: "'finally shipped the new checkout flow 🎉'"
May Miss
Highly contextual or coded language
Example: "'the thing we discussed is done' (no context)"
Improving Detection Accuracy
Use clear language in announcements
'Released v2.3' is better than 'pushed the thing'. The AI works better with explicit language.
Add custom keywords
If your team uses unique terminology, add it to your settings. See our custom keywords guide.
Choose the right channels
Monitor channels where structured announcements happen, not casual chat.
Match event types to channels
Enable 'Incidents' only on #incidents, not on #general. Context helps accuracy.
Privacy & Security
Your Data is Protected
- Messages are processed in real-time and not stored permanently
- Only extracted events are saved, not raw message content
- Your data is never used to train our AI models
Learn more about our security practices.