Santa Fe staff outline citywide asset‑management rollout, select OpenGov and plan AI risk tool

Taylor Jurgens, an engineer with the City of Santa Fe water division, told the Public Works and Utilities Committee on Jan. 6 that the city has selected OpenGov as its asset‑management software vendor and has finalized the scope of work with the firm. Jurgens said the OpenGov contract is in review and staff expects implementation to take about six to nine months once the contract is placed.

The asset program covers the water division’s infrastructure and will be rolled out across public utilities, wastewater and the city’s bus depot division (BDD), Jurgens said. “Really, add all this up, and we have roughly a billion dollars in assets excluding BDD,” he said. He described features the city expects to use from OpenGov, including work‑order management, life‑cycle cost analysis, capital improvement planning, GIS integration and a mobile app for field crews.

Jurgens also described plans to procure a second tool — described in the presentation as a machine‑learning model (referred to in the presentation as VOTA AI) — to support the city’s priority line‑replacement program. “It uses our historic break data along with several other factors to identify the highest risk mains we have in our system so that we can use that data, prioritize, and decide where we’re going to replace and rehab mains next,” he said. The model will produce remaining useful‑life projections and risk rankings that staff can use to target inspections or replacement projects.

Regina (public‑works staff) said public works will adopt a related work‑order system (Cartograph) and build a GIS layer for sidewalks, crosswalks and trails that the Bicycle and Pedestrian Advisory Committee (BPAC) resolution required. She told the committee that public works received $1,000,000 in one‑time funding in the current fiscal year for sidewalks and has brought on a project manager; Bike Santa Fe provided a study to help prioritize repairs. “We’ll be tying into the GIS and the work‑order system, so it’s all starting to come together,” she said.

Committee members pressed staff on several implementation points. Councilor Michael Garcia asked how the AI model works and which other cities have used it; Jurgens said vendors had shown case studies from Las Vegas and a large Arizona city and described a validation approach in which municipalities withhold historical data to test predictions. Councilor Lee Garcia and others asked how the model accounts for local conditions that drive breaks, including freezing temperatures, soil corrosivity and pipe materials; Jurgens said age is only one factor and the model incorporates soil maps, proximity to railways and other data sources.

Staff described training and user involvement as part of the rollout. Jurgens said OpenGov will provide training during implementation, including sandbox testing and post‑go‑live support; public‑works and utilities field crews, managers and other staff will be involved in designing work‑order pages and the data that crews will enter.

Staff did not present a final contract for committee approval on Jan. 6. Jurgens said the draft contract is under review and that staff hopes to bring the contract forward for approval within about a month. No formal votes on the OpenGov purchase or the AI tool occurred at the meeting.

Why it matters: the city aims to use software and analytics to manage a large, aging inventory of water and public‑works assets, target limited replacement dollars and improve transparency about priorities and performance. Committee members encouraged staff to publish the risk factors and priority lists so the public can see how projects are ranked.

What remains to be decided or clarified: the OpenGov contract must still be executed, the VOTA AI procurement is planned but not yet finalized, and staff said some data limitations remain — particularly regarding local freeze‑related break patterns — that may affect predictive accuracy.