Intent to Sole Source enroll ml, inc Software

The University of Montana's Department of Admissions is pursuing a sole source procurement for enroll ml, inc's machine learning-driven software platform, designed to convert student engagement behaviors into real-time, actionable intelligence for enrollment leadership and admissions counselors. The solicitation (Event Number UOM-SolSour-2025-0320) was released on March 24, 2025, with proposals due by April 7, 2025, at 2:00 PM MDT. The procurement falls under commodity codes 0910 (Computing Equipment & Software - Software) and 0911 (Computing Equipment & Software - Software as a Service). Potential vendors who believe they can provide equivalent products or services must submit a written "REQUEST TO CHALLENGE" to Jody Parrow at jody.parrow@umontana.edu by the proposal deadline. The procurement will follow a non-competitive proposal process, indicating a specific intent to contract directly with enroll ml, inc. Payment terms are structured as 0% 0, Net 30, with transactions conducted in US Dollars. The software platform's key objectives include transforming student engagement data into strategic enrollment intelligence, providing real-time insights for admissions counselors.

The solicitation does not explicitly outline specific set-aside designations or restrictions on responding organizations. No incumbent vendors or current contractors are mentioned in the available documentation. The procurement appears to be focused on acquiring a specialized software solution with unique capabilities that justify a sole source selection. While specific award values or budget ranges are not disclosed, the procurement is for a technology platform intended to enhance university enrollment strategies. The intent to sole source suggests that enroll ml, inc possesses proprietary technology or capabilities that are not readily available from alternative vendors. The procurement process includes a challenge mechanism that allows other potential vendors to demonstrate equivalent capabilities, though the ultimate selection appears to favor enroll ml, inc. The technology will likely need to integrate with existing university admissions infrastructure and data systems, though specific integration requirements are not detailed in the provided documentation.