Our History

Deasil's principals and core team have worked together since the 1990s. We have been innovating since the beginning of the many eras of modern digital transformation, contributing to the early years of Disney.com, to Research and Development and animation at the highly disruptive Napster, and a handful of Universal and Sony subsidiaries. We spent our early days on the bleeding edge, in the open green fields of new media and disruptive technology. As a result, our veins have equal parts infrastructure and software. We built our own distributed services and expanded our bare-metal data center presence more than a decade before they called it a cloud, not to sell cloud services but to solve nearly impossible matrix problems presented by an unrelenting surge in demand for digital transformation, mobile, and data solutions.

Supporting the Entertainment Industry

Headquartered in the heart of the entertainment industry in the early 2000s, we became a key innovator for some of the biggest stars looking to harness the booming internet, many of which included U2, Black Eyed Peas, No Doubt, Nine Inch Nails, and Beyoncé. Suddenly, we faced the challenge of accommodating the data and communication demands of a global fan base flocking to the internet to interact with their favorite artists and brands. Google was just getting started, along with socials MySpace and Facebook. From massive international data processing for Disney to pre-Youtube live video streaming, the team gained experience developing technologies in demand across industries.

Enhancing the Major Platforms

While individual artists and brands were looking to innovate online in the early 2000s, content providers such as Sony, Universal, Electronic Arts, Warner Brothers, and NBC were expanding their in-house development capabilities. As a result, they needed experienced platform architects as they transformed themselves from content providers to content platforms. Our team developed NBC.com's first software framework, powering its content platform and unifying internal resources and development operations. In addition, we developed many imaginative applications atop NBC's platform, including the first web applications implementing real-time synchronization with broadcast events.

Handling Enterprise Data

With a mature and growing skillset, the team translated its early success with high-traffic, big data, distributed computing, and platform development to solve problems for many traditionally data-heavy enterprises, including logistics, automotive, retail, and manufacturing. Our clients expanded from L.A. and Silicon Valley to the midwest as more conventional industries sought to harness digital transformation into contemporary technologies at the internet's scale.

For example, Deasil developed several solutions for a logistics client looking to expand their capabilities beyond the archaic systems available at the time; this led to additional projects for a top automaker looking to provide deeper access to their extensive parts catalog to tens of thousands of independent service centers. In addition, a national retailer engaged us to build a unique private-cloud, highly-available retail management system in use by thousands of locations nationwide, designed explicitly for rapid scaling over seasonal sales rushes, along with special features for the franchise and independent operator management, a custom predicate language for complex coupon development, multi-tier loyalty points system, and highly complex sales reporting, comparisons, and forecasting.

From video content platforms to retail management, our first decade of projects firmly established our mastery of distributed computing, moving, storing, and presenting data in all its forms. In the following decade, our toolset and experience with data communication, extraction, transformation, and management grew deeper.

The Language of Machines

Artificial Intelligence and Machine Learning are captivating popular media these days, mainly due to the last decade of advances in infrastructure and automation. While many ideas and algorithms have existed for nearly a century, they were challenging to develop, refine and implement, primarily due to the complex and costly infrastructure and environments needed to experiment, create and automate.

In 2010 the team began refining our infrastructure management systems, leading to several solutions that fit the needs of our data science clients in academia and, later, the energy industry, including advanced custom data science environments and our own GPULab and D4L data platforms. From traditional ETL and data warehousing to inference and generative AI, we are ready with the skills and toolset to solve your business' next move.