Update Felt layers automatically with AI agents
Swiftask links your data sources to Felt. Your maps stay current, reflecting the latest field changes or data updates, without any manual input.
Result:
Save significant time on map maintenance and ensure peak accuracy for your teams.
AI Agents
felt
Connector felt · Secure OAuth 2.0
Manual Felt layer updates kill your productivity
Keeping maps updated in Felt often requires constant human intervention. As soon as new data arrives, it must be extracted, formatted, and updated in the corresponding layer. This repetitive process exposes your projects to errors and unacceptable processing delays.
Main negative impacts:
Critical data lag
The time gap between data collection and visualization on Felt reduces the relevance of your decision-making.
Operational overload
Your experts spend more time manipulating files than analyzing the essential geospatial insights.
Human error risks
Repetitive manual entry increases the likelihood of typos or formatting errors, undermining map reliability.
Swiftask automates your Felt data lifecycle. Your AI agent detects new info, processes it, and updates your layers instantly when changes occur.
BEFORE / AFTER
What changes with Swiftask
Traditional manual process
A technician receives new data. They must convert it, open Felt, delete the old layer, upload the new one, and reconfigure styles. It's slow, tedious, and frustrating.
Automation with Swiftask
As soon as data is available in your database, Swiftask processes it and updates the Felt layer via API. The map updates continuously without anyone lifting a finger.
Deploy your Felt automation in 4 steps
1
STEP 1 : Agent definition
Configure an agent in Swiftask dedicated to monitoring your geospatial data sources.
2
STEP 2 : Felt connector setup
Integrate your Felt credentials to allow Swiftask to interact directly with your maps and layers.
3
STEP 3 : Trigger configuration
Define the update conditions: time intervals, arrival of a new file, or changes in an external database.
4
STEP 4 : Workflow activation
Launch the agent and monitor the automatic real-time synchronization from the Swiftask dashboard.
Advanced features for your Felt maps
The agent analyzes format, projection, and data integrity before every update to ensure perfect compatibility with Felt.
- Target connector: The agent performs the right actions in felt based on event context.
- Automated actions: Incremental updates of existing layers. Automated replacement of datasets. Automatic cleaning and formatting of source data. Error notifications for corrupted data.
- Native governance: All updates are logged, enabling immediate rollback if necessary.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-felt@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.
Strategic benefits for your projects
Real-time data
Your maps always reflect the most recent state of your field activities.
Increased productivity
Total removal of manual layer update tasks.
Data reliability
Automatic standardization of import processes, eliminating human errors.
Full scalability
Manage hundreds of layers without increasing manual workload.
Full control
Centralized tracking of every update via the Swiftask interface.
Security and governance
Swiftask applies enterprise-grade security standards for your felt automations.
- Secure authentication: Swiftask uses secure tokens to interact with your Felt account without exposing your main credentials.
- Access management: Precisely control which agents can modify which layers in your workspace.
- Audit logs: Every update is logged, ensuring full transparency on your maps' evolution.
- Compliance: Your data remains private and is processed according to the strictest security standards.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measured operational performance
| Metric | Before | After |
|---|---|---|
| Update time | 30-60 min (manual) | Seconds (auto) |
| Error rate | High (human input) | Near zero |
| Updates per day | Limited by humans | Unlimited |
| Deployment time | Weeks (scripting) | Minutes (no-code) |
Take action with felt
Save significant time on map maintenance and ensure peak accuracy for your teams.