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AI-Based Weather Forecasting & Microclimate Models

Build AI-powered weather forecasting and microclimate modelling platforms. PySquad delivers high-accuracy predictions using ML, satellite data, and sensor networks.

Built around your operation
  • Agriculture and agri-tech companies
  • Renewable energy operators and planners
  • Logistics and supply chain teams
The business case

What changes for your business.

Expected outcomes from the solution.

Explore the approach

Highly accurate hyper-local weather forecasts

Improved planning and operational efficiency

Early detection of extreme weather conditions

Scalable forecasting systems for multiple regions

Results depend on scope, integrations and adoption.

The operating context

A clearer view of the whole operation.

Accurate weather forecasting is critical for industries like agriculture, energy, logistics, and urban planning. However, standard forecasts often lack the resolution and precision needed for localized decision-making, especially in environments where microclimates vary significantly.

Where friction builds

Generic forecasts fail at local accuracy

Most organizations depend on broad weather APIs that do not capture local variations. This leads to inaccurate planning, missed risks, and inefficient operations. Without microclimate insights, teams cannot respond effectively to changing environmental conditions.

Current approach
  • Using generic weather APIs for all locations
  • Manual interpretation of weather data
  • Ignoring microclimate variations
  • Limited integration with operational systems
Operational impact
  • Inaccurate forecasts at local levels
  • Poor operational planning and decision-making
  • Missed early warnings for extreme weather
  • Reduced efficiency in climate-sensitive operations
Inside the solution

The capabilities behind the operation.

Review the functional scope, then discuss the requirements specific to your team.

Microclimate modelling

Generate hyper-local forecasts using geospatial clustering techniques

Multi-source data integration

Combine satellite, IoT, radar, and historical climate datasets

AI forecasting models

Predict temperature, wind, rainfall, and other parameters with ML

Geospatial visualization

Display weather layers, heatmaps, and localized insights

Continuous model retraining

Improve accuracy over time with updated data

Alerts and APIs

Provide real-time alerts and integration for operational systems

From requirements to implementation

Grounded in the way your team works.

How we work
  1. 01

    Collect and integrate environmental and sensor data

  2. 02

    Design geospatial and machine learning models

  3. 03

    Build forecasting engines and visualization tools

  4. 04

    Continuously optimize models for accuracy and scale

Our approach

We build AI-powered forecasting platforms that combine multiple data sources and machine learning models to generate accurate, hyper-local predictions. Our systems are designed to adapt continuously and provide actionable insights.

Make an informed decision

Is this the right fit?

The right solution starts with the right operating requirements.

Check the fit with us

Designed for

  • Agriculture and agri-tech companies
  • Renewable energy operators and planners
  • Logistics and supply chain teams
  • Smart city and urban planning organizations
  • Businesses needing hyper-local weather insights

May not be suitable for

  • Businesses relying only on basic weather updates
  • Teams without location-specific forecasting needs
  • Projects not using environmental or climate data
  • Organizations not requiring predictive insights

Trusted by clients worldwide

BDO
Marinapy
Vanilla Steel
INT Express
InnovationM
Telco Holdings International
Inglasco International
Upex Electrical UK
Lux Logic Lighting
CM3 Engineering
Finest Travel Africa
CareNav
XA Global Trade Advisors
Predictores.ai
iTech Consulting
Net Informatica
TextureAI UK
Lux Via
EEN Consulting
Intelgrity Ltd
OTEK Consulting
AI-O AI
The Hillock Hotels & Banquets
See it on your workflows

Walk through the solution with your operation in mind.

Discuss your requirements
Before you decide

Questions worth asking.

Ask something else
What datasets do you use for forecasting?

Satellite imagery, radar feeds, weather APIs, IoT sensors, and climate archives.

How accurate are the models?

Accuracy improves with local data, continuous training, and domain tuning.

Can this be used for farming or renewable energy?

Yes. We tailor models for agriculture, solar, wind, and logistics.

Do you support alerts for extreme weather?

Yes. Alerts can be triggered for wind, storms, rainfall, heat, and more.

Can forecasts be accessed via API?

Yes. We provide API endpoints for apps, dashboards, and external systems.

Start with your requirements

Let’s define your next step.

Tell us what needs to work better, the systems you use, and the scope you have in mind.

Discuss your requirementsShare your requirements through our enquiry form.

A little closer, wherever you are

Big world.
Close partnership.

Good work travels. We bring product engineering, AI and Odoo ERP to the conversation, and make room for your way of working.

01 / BaseAhmedabadIndia, remote
02 / ApproachOne shared planDiscovery to delivery
03 / ConnectionBuilt around youAgreed meeting rhythm