
Government agencies depend on field staff to understand what is happening across their communities, from property inspections and infrastructure assessments to resident complaints; but an observation made in the field is only the beginning. Staff must document what they find, connect it to existing records, determine what needs to happen next, and ensure the right people follow through. When these steps rely on paper forms, disconnected systems, or manual handoffs, even routine work can become difficult to manage.
At the 2026 Forerunner Summit, Forerunner’s VP of Product, Chris Schilling, demonstrated how agencies can close these gaps by connecting fieldwork with the systems and information that support day-to-day operations. Using the OODA loop — observe, orient, decide, and act — as a framework, he illustrated how a more connected approach can help teams move from an initial observation to a completed task, with less administrative friction along the way.
Consider an inspector arriving at a property to investigate a complaint. To understand the situation, they may need to review previous inspections, check permit history, consult local requirements, and document what they see. If that information is scattered across spreadsheets, emails, paper files, and separate applications, gathering the necessary context can take as much effort as the inspection itself.
This is a challenge the Puerto Rico Planning Board faced before adopting Forerunner. Staff relied on paper forms, cameras, spreadsheets, emails, and manually organized photographs to document inspections. After seeing the benefits of using Forerunner for floodplain management, the board expanded the platform to code enforcement, where it now supports dozens of field staff each day. The result has been better documentation, less paperwork, and greater visibility into ongoing work.
Schilling demonstrated how Forerunner brings that context directly into the field. An inspector can open a property record and review its history, including previous inspections, permits, cases, and mailings, before documenting a new finding. If the inspector is working in an area with unreliable connectivity, saved map areas allow them to continue working offline rather than interrupting the inspection.
AI can further reduce the effort involved in turning observations into usable records. During the demonstration, Schilling showed how AI can help populate inspection forms from photographs and answer spoken questions about local ordinances. Instead of documenting everything from scratch or waiting until they return to the office, staff can capture information in context and create more complete records as they work.
Once an inspection is documented, the next challenge is determining what the information means and what to do about it. An inspector may need to establish whether a property has a history of violations, a manager may need to understand which corrective actions are coming due, or a staff member may need guidance on how local rules apply to a particular situation. Answering these questions often requires searching multiple systems and piecing together information from different sources.
Schilling demonstrated how Forerunner’s AI Assistant can help staff find answers using plain-language questions. A user might ask for records associated with an address, the number of stormwater corrective actions due that month, or guidance on removing a storm-damaged tree. Rather than manually searching through individual records, the Assistant provides a summary with links to the underlying information.
The distinction is important: an answer is most useful when staff can understand where it came from and verify it before acting. Agencies can add their own ordinances, policies, and internal guidance so the AI Assistant can reference local requirements alongside relevant records. Staff can then review the supporting information and apply their own judgment.
Schilling also showed how dashboards can help teams see patterns that are harder to identify when information is spread across systems. By bringing together data such as inspection activity, fleet performance, water quality metrics, and MS4 annual reporting, dashboards give staff and managers a clearer view of activity across programs. Whether they are reviewing an individual case or monitoring broader operations, teams can use that context to make more informed decisions about what needs attention.
Identifying a problem and deciding how to address it are only part of the process. Agencies also need a reliable way to turn those decisions into work, whether that means scheduling an inspection, issuing a notice, or assigning a follow-up task. Without clear workflows, these next steps can depend on staff remembering what needs to happen and manually passing information between systems.
Schilling illustrated how Forerunner can connect these steps through configurable forms and automated workflows. AI can help staff build inspection forms without starting from scratch, while the platform's workflow tools can link information submitted by residents to the work that follows.
For example, a complaint submitted through a public portal can create a code enforcement case and initiate the next steps, such as queuing an inspection and preparing a notice of violation. If an inspector identifies a violation that requires additional attention, an automation can assign a high-priority reinspection based on that condition. Instead of relying on someone to manually coordinate each handoff, the workflow helps ensure the appropriate next step is triggered.
These processes can also work alongside the systems agencies already use. Schilling explained how data collected in Forerunner can sync back to an agency's GIS system, while notices can be generated from templates and sent by standard or certified mail. The goal is not to replace every existing tool, but to reduce the manual work required to move information between them and keep a case progressing toward resolution.
The session also offered a glimpse of how this process could become even more seamless. With Forerunner’s Live Mode, staff can speak with the AI Assistant while it views a scene through their phone’s camera and fills out an inspection form in real time. The interaction brings observation and documentation closer together, reducing the need to switch between looking at a site and entering information into a form.
Schilling took this a step further with a prototype using smart glasses. During a simulated fire standpipe inspection, the AI Assistant captured details about the system, including clearance, labeling, moisture, and surface condition. It also captured and attached a photograph without requiring the inspector to interact directly with a form.
These demonstrations offered a picture of fieldwork in which technology supports the inspection without becoming the focus of it. Staff can concentrate on what they are seeing and assessing, while AI helps capture those observations and connect them to the records needed for follow-up.
Across the demonstration, Schilling returned to a central challenge for government agencies: information is only useful when it can move with the work. An observation needs to become a reliable record; that record needs to inform a decision, and the decision needs to lead to action.
The OODA loop provides a useful way to understand how these stages reinforce one another. When field observations are captured in context, staff can find the information they need to assess a situation. When decisions are connected to configurable workflows, the next steps become easier to coordinate. When results are documented, they provide a stronger foundation for future decisions.
By connecting these stages while working alongside existing government systems, agencies can reduce administrative friction, improve visibility into their operations, and give staff more time to focus on the work that matters to their communities.
