Tarification

Automate spatial data cleaning in Felt

Swiftask connects your AI agents to Felt to normalize, correct, and prepare your geographic data in record time.

Resultat:

Eliminate geolocation errors and prepare your maps faster.

Manual spatial data cleaning is a bottleneck

Processing large geographic files in Felt requires extreme precision. Formatting errors, missing coordinates, or overlapping polygons slow down your projects significantly.

Les principaux impacts négatifs :

Geographic accuracy errors: Poorly cleaned data leads to critical misinterpretations in your final maps.
Time wasted on prep: Your teams spend 80% of their time formatting files instead of analyzing cartographic results.
Non-reproducible processes: Without automation, every data update becomes a complex technical challenge prone to new errors.

Swiftask automates data cleaning before integration into Felt. Your AI agents detect anomalies and fix formats instantly.

AVANT / APRÈS

Ce qui change avec Swiftask

Manual data management

You download a file, identify errors one by one, fix formats in a spreadsheet, then attempt to import into Felt. If an error persists, you start over.

Swiftask automated workflow

As soon as data arrives, your AI agent validates it, cleans coordinates, harmonizes attributes, and sends it clean and ready to use into your Felt project.

Geospatial preparation: 4 key steps

ÉTAPE 1 : Define quality rules

Configure your Swiftask agent with the formatting standards required for your spatial data.

ÉTAPE 2 : Connect to Felt

Link your agent to your Felt account via our secure connector for seamless synchronization.

ÉTAPE 3 : Automate cleaning

The agent analyzes each data entry and applies necessary corrections automatically.

ÉTAPE 4 : Instant visualization

Your cleaned data appears instantly in Felt, ready for your analysis and presentations.

Intelligent processing capabilities

The agent checks coordinate system consistency, geometry validity, and the integrity of associated attribute data.

Connecteur cible : L'agent exécute les bonnes actions dans felt selon le contexte de l'événement.
Actions automatisées : Normalize GeoJSON/KML formats. Automatic correction of outlier coordinates. Merge and remove spatial duplicates. Dynamic layer updates in Felt.
Gouvernance native : Every cleaning operation is documented in the Swiftask audit log for full transparency.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

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

Why automate with Swiftask

1. Increased precision

Drastically reduce human errors with strict validation rules.

2. Operational speed

Turn hours of manual work into seconds of automated processing.

3. Scalable projects

Manage growing volumes of geographic data without increasing your workload.

4. Data compliance

Ensure consistent and documented quality for all your map layers.

5. Focus on analysis

Free up time for strategic analysis rather than technical data entry.

Security and reliability

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

Data encryption: Your spatial data is processed in a secure, encrypted environment.
Source integrity: Swiftask ensures source data remains unchanged during the cleaning process.
Full control: You validate the cleaning rules applied by the agent at all times.
Complete traceability: Detailed history of every modification made to your datasets.

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

RÉSULTATS

Impact on your productivity

Métrique	Avant	Après
Preparation time	Hours per dataset	Real-time
Error rate	High (manual)	Near zero (automated)
Volume processed	Limited by human	Unlimited
Map updates	Heavy process	Instant

Passez à l'action avec felt

Eliminate geolocation errors and prepare your maps faster.

Optimisez vos zones de chalandise via Felt et l'IA

Cas d'usage suivant.