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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.

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 The information is outdated by the time you're done.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

STEP 1 : Configure your analysis agent

In Swiftask, define your study zone parameters: demographics, competition, foot traffic, or sector-specific data.

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.

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.

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

1. Increased precision

Eliminate human errors associated with manual manipulation of complex geospatial data.

2. Real-time insights

Stop making decisions based on days-old data. AI processes information instantly.

3. Multiplied productivity

Free your analysts from repetitive tasks to focus on high-value strategy.

4. Agile deployment

Modify your analysis models without writing a single line of code using the intuitive Swiftask interface.

5. 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

MetricBeforeAfter
Zone processing time2 to 4 hoursLess than 2 minutes
Data updatesWeekly (manual)Continuous (real-time)
Calculation accuracyHuman error riskExact algorithmic calculation
Analysis capacityResource-limitedUnlimited (automation)

Take action with felt

Save valuable time on field studies and accelerate your strategic decision-making.

Never miss a geographical shift with Felt alerts

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