Tarification

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.

Resultat:

Reduce your Mean Time To Resolution (MTTR) and improve your application's user experience.

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.

Les principaux impacts négatifs :

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.

AVANT / APRÈS

Ce qui change avec 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

ÉTAPE 1 : Configure the Fullstory integration

Connect your Fullstory account to Swiftask via our secure connector to sync error events in real-time.

ÉTAPE 2 : Set your alert thresholds

Define which types of JS errors should trigger an automated AI agent intervention.

ÉTAPE 3 : AI-powered enrichment

Swiftask analyzes Fullstory session data to provide a technical summary and suggested fix paths.

ÉTAPE 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.

Connecteur cible : L'agent exécute les bonnes actions dans fullstory selon le contexte de l'événement.
Actions automatisées : Automatic session data extraction, error categorization, prioritization based on user impact, and generation of technical summaries for developers.
Gouvernance native : All data is processed securely while maintaining full traceability of Fullstory sessions.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-fullstory@swiftask.ai ). Vous gardez une visibilité complète sur chaque action et chaque message envoyé.

À retenir : L'agent automatise les décisions répétitives et laisse à vos équipes les actions à forte valeur.

Operational benefits for your team

1. Drastic MTTR reduction

The diagnostic is ready before the developer even starts looking at the ticket.

2. Intelligent prioritization

Focus only on errors with a real impact on your users and your bottom line.

3. Better collaboration

Product and tech teams share identical, precise context on every incident.

4. Technical peace of mind

Automate 24/7 monitoring without the risk of missing a critical error.

5. Automatic documentation

Every error is archived with its resolution history, simplifying technical audits.

Security and data privacy

Swiftask applique des standards de sécurité enterprise pour vos automatisations fullstory.

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.

Pour aller plus loin sur la conformité, consultez la page gouvernance Swiftask et ses détails d'architecture de sécurité.

RÉSULTATS

Measurable impact on technical performance

Métrique	Avant	Après
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

Passez à l'action avec fullstory

Reduce your Mean Time To Resolution (MTTR) and improve your application's user experience.

Analysez vos rage-clicks Fullstory avec l'IA Swiftask

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