Samba Safety automates workflows on AWS, cutting delivery time by 70% | Firemind
Case study

Samba Safety automates workflows on AWS, cutting delivery time by 70%

Industry: Retail

About

Samba Safety helps reduce driver risk and promote safer communities through data-driven insights. Their software supports automotive and shipping industries by maintaining low-risk driver profiles to prevent accidents and damage.

Challenge

Samba Safety’s data science team built powerful models to enhance driver risk analysis, but their workflow relied heavily on manual processes. Scripts for data preprocessing, model training, tuning, and validation had to be run manually whenever new data arrived, with no automated versioning or hosting for inference. 

This manual model promotion process was time-consuming, labor-intensive, and slowed innovation. Samba needed an automated solution that replicated their manual workflow, integrated with their existing external code repository, and supported continuous delivery for both training and inference. 

Solution

Firemind designed two ML pipelines using AWS: one for model training and another for inference. The training pipeline ran Samba’s custom preprocessing and training scripts, deploying the resulting model to Amazon SageMaker for both batch and real-time inference. The inference pipeline handled prediction requests separately, ensuring flexibility and scalability. 

AWS Step Functions, SageMaker Processing, and AWS Lambda were used to replicate Samba’s manual workflow while adding full automation for training, tuning, deployment, and inference workloads. AWS CodeStar was integrated with Samba’s existing code repository to trigger automated pipelines whenever code updates were committed. 

Services used

  1. AWS Step Functions
  2. AWS Lambda
  3. AWS CodeStar

Results

  • 70% reduction in time to delivery

  • Faster turnaround times for model deployment

  • Improved accuracy in model outputs

  • Fully automated ML workflow

  • Scalable infrastructure supporting continuous delivery

By automating our data science models and integrating them into their software development lifecycle, we have been able to achieve a new level of efficiency and accuracy in our services. This has enabled us to stay ahead of the competition and deliver innovative solutions to clients.

Patrick KembleCTO, Samba Safety

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