Streamline your geographic zone analysis with Felt and AI
Swiftask integrates with Felt to turn your maps into intelligent analysis tools. Identify opportunities and risks without manual effort.
Result:
Save valuable time on field studies and accelerate your strategic decision-making.
AI Agents
felt
Connector felt · Secure OAuth 2.0
Manual map analysis limits your responsiveness
Analyzing geographic zones on traditional tools is often a slow and disconnected process. Your teams spend hours layering data, extracting trends, and writing reports, while market opportunities slip away.
Main negative impacts:
Excessive analysis time
Processing geospatial data requires constant manual input, delaying the production of critical insights.
Data silos
Felt maps remain isolated from other business tools, preventing effective cross-analysis with your customer or financial data.
Lack of scalability
Analyzing 10 zones is feasible, but analyzing 1000 becomes an unbearable operational bottleneck for your teams.
Swiftask automates your zone analysis in Felt. Our AI agent processes your geographic data in real-time, identifies key patterns, and alerts you immediately about high-potential zones.
BEFORE / AFTER
What changes with Swiftask
Traditional approach
You manually import data into Felt, spend hours manipulating layers, then write a summary in an external document. The information is outdated by the time you're done.
The Swiftask + Felt ecosystem
As soon as data changes in Felt or your database, Swiftask recalculates zone metrics, updates your annotations, and notifies you of relevant changes.
Automate your zone studies in 4 steps
1
STEP 1 : Configure your analysis agent
In Swiftask, define your study zone parameters: demographics, competition, foot traffic, or sector-specific data.
2
STEP 2 : Link your Felt map
Connect Swiftask to your Felt project. The agent accesses the necessary data layers to perform its calculations in real-time.
3
STEP 3 : Define performance indicators
Set alert thresholds: for example, if the number of points of interest in a zone exceeds a certain figure, the agent notifies you.
4
STEP 4 : Visualize and act
View generated insights directly in Swiftask or receive automated notifications as soon as an opportunity is detected.
Advanced analysis capabilities for Felt
The agent analyzes density, proximity, and temporal evolution of geographic data stored in Felt.
- Target connector: The agent performs the right actions in felt based on event context.
- Automated actions: Automatic extraction of zone metrics. Dynamic updating of map annotations. Intelligent alerts based on data changes. Correlation between geospatial data and external business metrics.
- Native governance: All analyses are logged in Swiftask to track the evolution of your zones over time.
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.
Why choose smart analysis
Increased precision
Eliminate human errors associated with manual manipulation of complex geospatial data.
Real-time insights
Stop making decisions based on days-old data. AI processes information instantly.
Multiplied productivity
Free your analysts from repetitive tasks to focus on high-value strategy.
Agile deployment
Modify your analysis models without writing a single line of code using the intuitive Swiftask interface.
Seamless collaboration
Share AI-generated conclusions directly with your teams via integrated communication tools.
Commitment to security and compliance
Swiftask applies enterprise-grade security standards for your felt automations.
- Secure integration: The connection between Swiftask and Felt uses restricted and secure API access.
- Data privacy: Your geospatial data remains under your exclusive control within your workspace.
- Decision traceability: Every analysis produced by the agent is documented to ensure full transparency.
- Robust infrastructure: Scalable architecture designed to process large data volumes without compromising security.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measurable operational performance
| Metric | Before | After |
|---|---|---|
| Zone processing time | 2 to 4 hours | Less than 2 minutes |
| Data updates | Weekly (manual) | Continuous (real-time) |
| Calculation accuracy | Human error risk | Exact algorithmic calculation |
| Analysis capacity | Resource-limited | Unlimited (automation) |
Take action with felt
Save valuable time on field studies and accelerate your strategic decision-making.