Tarification

Intelligent alerts on your Countly KPIs, powered by AI

Swiftask monitors your Countly data continuously. As soon as a critical KPI hits an abnormal threshold, your AI agent alerts you instantly.

Resultat:

Shift from reactive analysis to proactive vigilance. Protect your business performance without manual monitoring.

Manual KPI monitoring is risky and inefficient

Manually tracking dozens of metrics in Countly is impossible. Teams miss conversion drops or error spikes until it is too late.

Les principaux impacts négatifs :

Delayed anomaly detection: Critical issues remain invisible for hours, directly impacting your revenue or user experience.
Information overload: The sheer volume of dashboards makes reading indicators complex and tedious for decision-makers.
Slow human reaction: The latency between noticing a problem and taking corrective action is far too high.

Swiftask acts as a sentry for your Countly data. It analyzes your KPIs in real-time and triggers contextual alerts as soon as a critical threshold is met.

AVANT / APRÈS

Ce qui change avec Swiftask

Before automation

Your team checks Countly dashboards once a day. A sudden drop in conversion rate in the morning goes unnoticed until the next day's report. You lose a full day of potential revenue.

With Swiftask + Countly

The conversion rate drops below the defined threshold. Swiftask detects the anomaly, analyzes the context, and sends an immediate alert with a summary of probable causes to your communication channel.

Setting up your KPI monitoring in 4 steps

ÉTAPE 1 : Configure the monitoring agent

Create a dedicated agent in Swiftask and connect it to your Countly instance via API or webhook.

ÉTAPE 2 : Define your critical thresholds

Set the KPIs to monitor: conversion rate, active sessions, error rate, or any custom event.

ÉTAPE 3 : Choose the alert channel

Determine where the agent should send the alert: Slack, Microsoft Teams, Email, or a direct action in your CRM.

ÉTAPE 4 : Activate the watch

The agent starts real-time analysis. You only receive notifications when necessary.

Advanced detection capabilities

The agent cross-references Countly data in real-time to distinguish statistical noise from a real business anomaly.

Connecteur cible : L'agent exécute les bonnes actions dans countly selon le contexte de l'événement.
Actions automatisées : Trend analysis, error spike detection, conversion threshold alerts, automated summary reports, triggering of corrective workflows.
Gouvernance native : Configuration is completely no-code and adaptable to your evolving needs.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-countly@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.

Major operational benefits

1. Reduced MTTR

Problem resolution time is drastically reduced thanks to immediate notification.

2. Focus on the essentials

Stop checking dashboards needlessly: the agent only alerts you to critical events.

3. Data-driven decisions

Each alert comes with clear context to facilitate rapid decision-making.

Security and privacy

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

Data encryption: Your Countly data is processed securely and is never shared with third parties.
Granular control: You precisely manage which KPIs are accessible by the AI agent.

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

RÉSULTATS

Impact on your performance

Métrique	Avant	Après
Detection time	24h (daily)	Under 2 minutes (real-time)
Cost of error	High (conversion loss)	Minimized (rapid intervention)

Passez à l'action avec countly

Shift from reactive analysis to proactive vigilance. Protect your business performance without manual monitoring.

Synthétisez vos rapports Countly automatiquement avec l'IA

Cas d'usage suivant.