WASHINGTON — Inadev, a provider of cloud-based services for federal agencies, said it won a multi-year, $33 million prime contract award from the U.S. Department of Health and Human Services to enhance software applications for the HHS Office of the Assistant Secretary for Health, including a a “no-code” replacement for the Commissioned Corps Personnel and Payroll system.
The Codeless Architecture Configuration contract will support an effort to modernize and migrate OASH’s core collaborative IT services, which are essential to its missions and projects across geographically distributed centers, the McLean, Virginia-based company said in a statement. The scope of work includes implementation of a no-code platform from New York-based software company Unqork in a federal cloud environment, and engineering of a Commissioned Corps Integrated Personal and Payroll System for HHS and OASH, it said.
“Inadev is a huge proponent of low-code/no-code systems, having leveraged our own proprietary platform—CEEBIT—for enterprise-wide federal agencies and commercial clients,” said Co-Founder and CTO Vikrant Binjrajka, in the statement. “Whether we’re harnessing CEEBIT or Unqork’s platform, this partnership illustrates our unyielding commitment to advancing technology innovation—faster and more efficiently.”
No-code is a software development approach that requires few, if any, programming skills to quickly build an application, according to news and data site TechTarget. This allows line of federal employees with institutional knowledge and an understanding of the requirements for an app, but lack knowledge of programming languages, to create software applications such as a form or website, or add functionality to an existing site or app.
The company was recently selected by U.S. Citizenship and Immigration Services for a task order on the Fraud Investigation National Security Coordinated Heuristics analytics contract and will supply open-source Artificial Intelligence and Machine Learning products and services to automate the detection and identification of fraud.
