Digital Sense

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Overview

$25,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

10 - 49

Employees

2009

Year Founded

ABOUT DIGITAL SENSE

AI That Dares to Innovate

Digital Sense - Research-Oriented, Results-Driven 🎯 We are a dedicated AI firm providing services in Machine Learning, Data Science, and Computer Vision, backed by over ten years of experience and a top-tier team of specialists. At Digital Sense, you can explore a wide range of sectors, including AgriTech, Satellite Imaging, FinTech, Health Care, and Beauty, where our expertise stands out. Reach out to us: 📲 Let’s talk about your project!

Languages Spoken

English

HIGHLIGHTS

$25,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

10 - 49

Employees

2009

Year Founded

Services

Focus

Industries

Clients

Services Provided

50% Custom Web Application Development

40% Machine Learning Model Development

10% Generative AI

About the Team

OUR STORY

Digital Sense specializes in stress-free hiring by providing expert engineering teams that integrate seamlessly with your in-house staff. They offer skilled professionals in Machine Learning, Data Science, Computer Vision, and Image Processing, forming self-managed teams ready to support your projects promptly. These teams typically include roles such as Senior Consultant, Team Leader, R&D Engineer, Scientific Consultant, and various engineering specialists, ensuring tailored, robust solutions. The company emphasizes personalized service by analyzing project goals and technical needs, engaging in detailed discussions to assemble the best team. Confidentiality is maintained through NDA agreements, followed by clear roadmapping and smooth onboarding processes to ensure effective collaboration across diverse industries. Digital Sense empowers clients to harness AI and Machine Learning efficiently through their dedicated teams.

Portfolio

Custom satellite image processing for Satellogic

Unknown

CLIENT: Satellogic is a startup that has secured more than $60 million in funding. It specializes in the design, construction, and operation of a growing fleet of nanosatellites, with offices located in the US, China, Israel, Spain, Argentina, and Uruguay. CHALLENGE: The company faces the challenge of processing vast amounts of image data generated from its custom satellite design. This process must be both highly efficient and precise to ensure clients receive reliable products promptly. SOLUTION: We partner with Satellogic's internal experts to enhance and support their team. Our collaboration spans multiple phases of their proprietary image processing pipeline, from raw images to the final deliverables. Key areas of research and development focus on geometric and radiometric accuracy of images, automated quality assurance, and improving processing efficiency.

R&D to Improve image processing quality for CNES

Unknown

CLIENT: The Centre National D'Études Spatiales (CNES), known as the French National Space Center, operates with a budget of €2.78 billion and employs over 2,350 staff, predominantly engineers. CHALLENGE: CNES manages the development, deployment, and operation of various satellites, including the Pleiades constellation, which consists of two identical high-resolution satellites capable of capturing images at 50 cm for panchromatic and 2 m for multispectral bands. Due to their size, the images are compressed before transmission to Earth, resulting in artifacts that compromise image quality. SOLUTION: We conducted a thorough analysis of the image formation and compression techniques. We introduced a new mathematical model to create a combined denoising and decompression algorithm that effectively eliminates these artifacts. The innovation of our approach garnered attention and was published at the prestigious IEEE ICIP (International Conference on Image Processing) in 2017. A subsequent enhancement utilizing a deep learning method was showcased at CVPR (Computer Vision and Pattern Recognition Conference) in 2018.

AI plant detection for efficient forestry

Unknown

CLIENT: Montes del Plata produces Eucalyptus cellulose pulp and was established in 2009 by two leading global forestry firms: Stora Enso (based in Sweden-Finland with 25,000 employees across over 30 countries and EUR 10.1 billion in revenue in 2019) and Arauco (Chile). CHALLENGE: The company sought an efficient solution for forestry irrigation, as the high mortality rate of young trees during dry months requires them to be watered for successful planting. Although the company possesses irrigation machines, they are operated manually and can only water one row of trees at a time. SOLUTION: Our team created a computer vision module that can be attached to the irrigation machines. This technology detects plants in real time and automatically activates the watering mechanism as the machine moves forward. This innovation allows for the use of multiple independent watering systems, enabling the irrigation of several rows simultaneously, thus conserving time, reducing operational costs, and enhancing the survival rate compared to manual methods.

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