Detect and resolve Fullstory JS errors with AI
Swiftask analyzes JS errors caught by Fullstory. Get contextual diagnostics and speed up your bug resolution process.
Result:
Reduce your Mean Time To Resolution (MTTR) and improve your application's user experience.
AI Agents
fullstory
Connector fullstory · Secure OAuth 2.0
The complexity of manual JS debugging
Identifying a JavaScript error in Fullstory is one thing, but understanding and fixing it is another. Developers waste valuable time switching between tools, reproducing sessions, and isolating the root cause.
Main negative impacts:
Excessive diagnostic time
Each error requires manual session analysis, significantly slowing down your fix cycle.
Developer burnout
Engineering teams are overwhelmed by unqualified alerts, neglecting high-value feature work.
Degraded user experience
Persistent, unpatched errors directly hurt your customer conversion and retention.
Swiftask automates the bridge between Fullstory and your team. As soon as a critical JS error is detected, our AI agent enriches the alert with session context and suggests an immediate fix.
BEFORE / AFTER
What changes with Swiftask
Legacy error management
A JS error occurs. You get an alert, open Fullstory, hunt for the session, try to reproduce the bug, document it manually, and hand off the ticket.
Intelligent workflow with Swiftask
Fullstory detects the error. Swiftask ingests the signal, extracts relevant logs, links the session, and creates a complete ticket with AI-powered root cause analysis.
Activate your fix flow in 4 steps
1
STEP 1 : Configure the Fullstory integration
Connect your Fullstory account to Swiftask via our secure connector to sync error events in real-time.
2
STEP 2 : Set your alert thresholds
Define which types of JS errors should trigger an automated AI agent intervention.
3
STEP 3 : AI-powered enrichment
Swiftask analyzes Fullstory session data to provide a technical summary and suggested fix paths.
4
STEP 4 : Notification and resolution
The enriched alert is sent to your favorite ticketing tool or communication channel.
What your AI agent can do
The agent examines JS stack traces, user interactions leading up to the error, and application state changes.
- Target connector: The agent performs the right actions in fullstory based on event context.
- Automated actions: Automatic session data extraction, error categorization, prioritization based on user impact, and generation of technical summaries for developers.
- Native governance: All data is processed securely while maintaining full traceability of Fullstory sessions.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-fullstory@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Operational benefits for your team
Drastic MTTR reduction
The diagnostic is ready before the developer even starts looking at the ticket.
Intelligent prioritization
Focus only on errors with a real impact on your users and your bottom line.
Better collaboration
Product and tech teams share identical, precise context on every incident.
Technical peace of mind
Automate 24/7 monitoring without the risk of missing a critical error.
Automatic documentation
Every error is archived with its resolution history, simplifying technical audits.
Security and data privacy
Swiftask applies enterprise-grade security standards for your fullstory automations.
- End-to-end encryption: All data from Fullstory is processed securely and encrypted.
- GDPR compliance: Swiftask guarantees compliance with strict data protection standards for your logs.
- Granular control: You decide exactly which session data is accessible to the AI agent.
- Robust infrastructure: Scalable architecture designed to handle high volumes of errors in real-time.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measurable impact on technical performance
| Metric | Before | After |
|---|---|---|
| Manual triage time | 20+ minutes per ticket | Under 2 minutes |
| Diagnostic accuracy | Based on guesswork | Based on real data |
| Resolution rate | Variable by expertise | Consistently faster |
| Monitoring coverage | Partial | Full and automated |
Take action with fullstory
Reduce your Mean Time To Resolution (MTTR) and improve your application's user experience.