Pricing

Anticipate performance with AirOps predictive analytics

Swiftask connects your data to AirOps to generate predictive models. Turn weak signals into informed strategic decisions, instantly.

Result:

Shift from reactive analysis to proactive strategy. Forecast market trends with high precision.

Untapped data is holding back your growth

Most companies accumulate massive volumes of data without extracting predictive value. Without the right tools, forecasts remain intuitive or based on outdated spreadsheets, preventing real market anticipation.

Main negative impacts:

Decision-making based on the past: Your strategies rely on historical reports that do not reflect future dynamics, limiting your agility.
Isolated data silos: Hidden value in your databases remains inaccessible to operational teams due to a lack of modeling tools.
High cost of data science: Developing custom predictive models requires rare and expensive technical resources, slowing down innovation.

Swiftask and AirOps democratize predictive analytics. Create intelligent workflows that analyze your data, detect patterns, and generate actionable forecasts, all without writing a single line of code.

BEFORE / AFTER

What changes with Swiftask

Traditional approach

Your team manually exports data to Excel, attempts to build complex regression models, and spends days interpreting results that are often disconnected from operational reality.

Predictive power with Swiftask + AirOps

Swiftask automates data flow to AirOps. The AI analyzes variables in real-time, generates precise projections, and injects these insights directly into your business tools.

Deploying your predictive models in 4 steps

STEP 1 : Centralizing data flows

Connect your data sources to Swiftask. The agent prepares and cleans key variables for analysis.

STEP 2 : Configuring the AirOps engine

Integrate AirOps via Swiftask to define the type of desired prediction (sales, churn, trend).

STEP 3 : Training and modeling

The agent runs models on your historical data to identify predictive correlations.

STEP 4 : Activating insights

Receive actionable predictions directly in your dashboards or communication tools.

Advanced modeling capabilities

The Swiftask agent evaluates variable relevance, adjusts model weights, and detects anomalies in incoming data.

Target connector: The agent performs the right actions in airops based on event context.
Automated actions: Revenue forecasting, proactive churn detection, dynamic customer segmentation, inventory optimization. Seamless integration of results into Swiftask workflows.
Native governance: You maintain full control over model parameters, allowing for rapid adaptation to market shifts.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-airops@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 advantages of AI analysis

1. Increased precision

Reduce uncertainty with models trained on your real-world data.

2. Business autonomy

Your operational teams create their own forecasts without relying on the Data team.

3. Decision agility

React to market changes before your competitors thanks to detected weak signals.

4. Maximized ROI

Optimize resource allocation based on reliable projections.

5. Seamless integration

AirOps fits naturally into your existing Swiftask ecosystem.

Commitment to security and compliance

Swiftask applies enterprise-grade security standards for your airops automations.

Data encryption: Your data is protected throughout the transfer cycle between Swiftask and AirOps.
Strict governance: Control who accesses predictive models and generated results.
GDPR compliance: The architecture adheres to the highest privacy standards.
Full traceability: Every prediction is documented to ensure model explainability.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your key performance indicators

Metric	Before	After
Forecast precision	Based on intuition (±25%)	AI-driven (±5%)
Modeling time	Several weeks	A few hours
Analysis cost	High (consultants/data team)
Data exploitation	Partial and isolated	Full and centralized

Take action with airops

Shift from reactive analysis to proactive strategy. Forecast market trends with high precision.

Ensure data integrity with automated validation via AirOps

Next use case