Amatrol Electrical Machines Learning Systems

The Community Colleges of Spokane has issued a Request for Quote (RFQ) for Amatrol Electrical Machines Learning Systems, targeting multiple jurisdictions including Spokane Valley City, Spokane County, and Spokane City. The procurement seeks to acquire specific electrical machine learning system components, including a DC Generators Learning System, an Alternator/Synchronous Motor Learning System, a Synchroscope, and an Oscilloscope. The solicitation strictly requires new equipment, explicitly prohibiting alternate items, used, or remanufactured equipment. Responses are due by July 14th, 2025, at 4:00 PM PST, with delivery to be made at 3939 N Freya ST, Spokane, WA 99217-6805. The award will be made to the lowest responsible and responsive bidder, with the college reserving the right to make multiple or split awards among different vendors. Vendors must submit a comprehensive response package including signed certifications, detailed quotes for each item, and supporting documentation like a W-9 form. The bid pricing must remain firm for a minimum of 90 days, and all quoted prices should be all-inclusive, covering all associated fees, permits, and licenses.

The RFQ does not explicitly mention specific set-aside designations or restrictions for disadvantaged enterprises. The procurement appears open to qualified vendors capable of providing the specified electrical learning systems. While no incumbent vendors are identified, the solicitation emphasizes that the award is subject to annual budget approvals. No specific budget range or award value is detailed in the available documentation. The procurement process indicates flexibility in vendor selection, with the potential for multiple vendors to be awarded contracts for different components of the electrical machines learning systems. The strict requirements for new equipment and comprehensive documentation suggest a rigorous evaluation process focused on technical capabilities, reliability, and compliance with the specified system requirements. Vendors should be prepared to demonstrate their ability to provide high-quality, new electrical machine learning equipment that meets the precise specifications outlined in the RFQ.