Flight Risk Assessment Tool with AWS

Client Background

Overheadintel is a technology company focused on providing advanced insights for drone flight planning. Their goal is to help drone operators understand local hazards such as people, buildings, air activity, and environmental conditions, before and during flight.

Their customers include:

• Drone photography companies.

• Inspection and surveying firms.

• Delivery technology teams.

• Public safety and emergency units.

• Enterprise drone operations teams.

To support these users, they needed a robust, cloud-based system that could collect, clean, and process flight data in real time.

The Problem: Drone Operators Had No Reliable Way to See Risk in Real Time

Before this project, drone operators had:

• Limited visibility of the real risk around a planned flight path.

• Slow or manual risk calculations.

• No automated way to combine air risk and ground risk.

• No system to flag hazards such as population density, restricted zones, or building height.

• No easy way to generate pre-flight or in-flight alerts.

• No cloud pipeline to process large datasets quickly.

Flight decisions were being made with incomplete information, which increased safety risks and compliance issues.

Overheadintel needed:

• Automated data ingestion.

• Cloud pipelines that scale.

• Real-time risk scoring.

• A dynamic map view of hazards.

• A reliable back end that supports different drone use cases.

They partnered with Tenplus to build a complete production system on AWS.

Solution Overview

Tenplus designed the solution using a fully serverless AWS architecture that is fast, scalable, and cost-efficient.

The core technology stack used in the project included:

• AWS Glue for data cleaning and ETL.

• Amazon S3 for data storage.

• AWS Lambda for serverless compute.

• Amazon SageMaker Notebooks for risk models.

• Amazon SNS / emails for alerts and notifications.

• AWS IAM, CloudWatch, and API Gateway for security and monitoring.

Below is a breakdown of how these services worked together.

Data
Analysts

Our in-house data analysts have a hands-on approach to data.

5

45

Companies analyzed

Last year, we were able to help nearly 50 companies.

Process

Step 1: Data Collection and Storage Using Amazon S3

Step 2: Data Cleaning and ETL with AWS Glue

Step 3: Real-Time Compute With AWS Lambda

Step 4: Risk Modelling With SageMaker

Step 5: Real-Time Risk Map Generation

Step 6: Automated Alerts and Reporting

Data designers

Our designers have an extensive background in data analysis.

3

1340

Visualizations made

From presentations to marketing materials and beyond.

23

Ongoing projects

Data changes, but our team stands by your side when you need us.

Results: A Complete Real-Time Risk Assessment System

With Tenplus and AWS, Overheadintel achieved:

• A fully automated, cloud-based flight risk engine.

• Real-time risk scoring for any drone flight path.

• A central data lake powered by S3.

• Scalable ETL with AWS Glue.

• Fast compute with Lambda.

• Strong AI risk modelling with SageMaker.

• A clear, visual map for flight planning.

• Higher safety, lower risk, and better compliance.

The tool helps operators make smarter decisions and reduce hazards before each mission.

⭐⭐⭐⭐⭐

“Working with Tenplus helped us turn a complex idea into a real, working product. Their team built a fast and scalable system on AWS that gives our users the risk insights they need.
The end result is strong, accurate, and ready for growth.”

Head of Engineering, Overheadintel

We’ve helped them

We've partnered with many household brand names to deliver insights and solutions to their problems with big data.

Happy clients

Don't just take our word for it – our clients frequently stay in touch with us and work with us on future projects that require big data insights.

John Bjerrand

I work in agricultural consulting, meaning that we often need to use big and complex datasets to justify expensive investments for our clients. Lilo's consultants helped us see the big picture with their visualization tools and expertise.

Anna Claudio

As the in-house supplier manager, it's sometimes had to understand which manufacturers work best for our needs. Lilo's data analysis helped us identify where we could save and which manufacturers worked the best for us in the long term.

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