customer Story

How Safari AI Improved Model Accuracy and Reduced Time to Delivery by 50% with V7

Safari AI
Using computer vision to automate the measurement of physical operations for enterprises using their own IP camera network
Company Industry
Software & Internet
Use Case
Video Analytics
Company Size
11-50 employees
New York, USA
"We are leveraging V7’s model-assisted labeling in our workflows, which helps us decrease the cost per image labeled and cuts in half the time to delivery."
Images labeled/week
Annotated data type
Image and video
Favorite feature
ML-assisted labeling

The Challenge

Safari AI is a company that specializes in providing end-to-end computer vision solutions for large enterprises, automating the measurement of physical operations. The company works with customers across various industries, such as retail, real estate, restaurants, logistics, and more. Their main challenge is to ensure the highest degree of accuracy for their vision AI solutions while delivering them in a timely manner.

To meet the demands of their customers, Safari AI needed a robust ML training data platform to annotate data and train accurate models at scale.

The Solution

Safari AI partnered with V7 to expedite ground truth creation and enhance their ML model performance. By utilizing V7's labeling workforce and advanced platform features like custom workflows and model-assisted labeling, Safari AI achieved a significant reduction in annotation costs and delivery time, which was cut in half. Leveraging V7's on-demand workforce, Safari AI also improved their operational efficiency with minimal overhead.

We’ve had experience working with other labeling partners where the annotation instructions were handled poorly, and V7’s workforce has done a great job of following the instructions, which significantly sped up our labeling process.
Adrian Levitt
Head of Ops & Finance
Meet the team

About Safari AI

Safari AI is a computer vision company automating the measurement of physical operations for enterprise companies.

Founded in 2018 as a curb space availability monitoring company, Safari AI pivoted towards its current mission in 2022. Now, they help large organizations across industries such as retail, logistics, or real estate replace manual, physical or non-existent data collection of mission-critical processes with end-to-end computer vision solutions.

Safari AI's wide variety of use cases includes pedestrian counts, vehicle classification, staff detection, and more.

Training data needs

On-demand high-quality labeling and model training with V7

Safari AI uses customers' existing cameras or their own equipment to capture images and videos, which they label to build object detection models. These models are then deployed on the client's cameras, providing valuable insights, such as store visitor count or peak parking occupancy times.

To build accurate models, Safari AI deals with large amounts of data, sometimes tens of thousands of images, all of which require accurate labeling. Some models require ongoing data inputs to improve their quality over time.

Safari AI uses V7 to outsource the entire image labeling process to V7’s labeling partners. After importing the data to the platform, providing instructions, and setting up the workflows, V7’s labelers annotate all the images with bounding boxes or polygons. Then, Safari AI's machine learning engineers can use them to train and retrain their models.

Why V7

Using ML-assisted labeling workflows to cut down time to delivery in half

Safari AI needed an end-to-end training data platform to annotate data and train models at scale quickly. The company's standard project completion timeline is just one month, making it crucial for them to have a trusted labeling partner and a reliable platform like V7 to deliver quality vision AI solutions promptly.

Since Safari AI's labeling needs depend on the number of clients, business types, and seasonality, maintaining an in-house labeling workforce would strain resources. Additionally, the team faces challenges in annotating their data due to varying weather conditions, camera angles, and shadows. V7 solves these problems by providing on-demand, high-quality labeling services and custom model-assisted workflows. 

Safari AI now leverages V7's labeling workforce and model-assisted labeling, and they can label more than 10,000 images per week, achieving higher model accuracy faster.

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V7 and our labeling partners play a very important role in the development of our products. We currently use V7 for image and soon potentially also video annotation. We train models off of that and deploy those models on our customers’ cameras and give them the data that they want.
Adrian Levitt
Head of Ops & Finance

Towards faster and more cost-effective model training

Safari AI has been able to scale their operations significantly with the help of V7's intuitive platform and professional labeling services. This has allowed them to build computer vision solutions for their clients faster and more cost-effectively, while maintaining high levels of quality and accuracy.

By cutting down delivery times in half, Safari AI can take on more projects without having to hire additional staff or increase management overhead. According to Adrian Levitt, Head of Operations, "V7 and our labeling partners play a very important role in the development of our products, helping us deal with the surges and lulls of customer pipelines. Thanks to V7, we have a workforce and platform on-demand that can meet our seasonal and sales-driven needs."

Thanks to V7's model-assisted labeling workflows, Safari AI has been able to annotate data faster, improve the quality of their labeled data through a more comprehensive review process, and lower the cost per project.

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