Bridging the Gap: Using AI to Bring Community Resources to the Frontline

By Jessica DeVries, Lead, AI Evaluation and Program Delivery, Duologue Systems

Not every call for service requires enforcement, as many involve community members facing housing, mental health, addictions, and other complex social challenges. Police services in Ontario have built capacity to respond through specialized teams, referral pathways, and prevention work developed with municipal and community partners, consistent with the province’s broader community safety and well-being framework. However, much of that capacity remains concentrated in specialized units already stretched by high-priority cases.

Meanwhile, frontline members frequently cycle through repetitive calls because the underlying social needs remain unresolved. When officers lack legal grounds for apprehension or enforcement, they require effective tools or immediate referral options to offer individuals before their situations worsen, potentially requiring a major police response at a later time.

Putting Community Resource Knowledge in Frontline Hands

Artificial Intelligence (AI) creates an opportunity to make available specialized community-resource knowledge while also identifying resources beyond those already known to the organization, all within minutes.

Hapi is a Canadian-developed, patent-pending AI-powered resource-navigation technology co-designed with police specifically for frontline use, representing the first application of this type of AI-powered system navigation. Members can identify relevant resource options and decide what to share directly with the community member.

Community members leave with resources they can continue to access, while police services gain anonymous, aggregate visibility into what was requested and shared. Hapi goes one step further by showing which resources prompted an initial action after being shared.

AI Co-designed with Frontline, for Frontline

For AI to be useful at the frontline, it has to fit the realities of the work. Frontline feedback has shaped Hapi’s low-barrier SMS workflow, how resources are handed off to community members, and how the text-based interaction works in practice. Members can text Hapi in their own words without downloading another application, then ask follow-up questions, request different options, or refine the request as the interaction develops. The same SMS channel can also support proactive check-ins and broader communication directly with frontline members, providing another way to share timely information and organizational updates.

Building AI Literacy Where it Matters

Hapi is also designed to support members as they become more familiar with using AI and navigating the community-resource landscape. If a request is broad, Hapi can clarify it rather than requiring the member to frame it perfectly from the outset. A housing request, for example, may involve emergency shelter, transitional housing, or supportive housing, each with different pathways and intake requirements. A community member may also have multiple or intersecting needs, and Hapi can assist by identifying resources or organizations that provide supports through wraparound service models. Through repeated use of Hapi, frontline members build their knowledge of community resources while developing practical AI literacy and learning how to refine requests around the needs of the community member.

Specialized Knowledge, Available Across the Frontline

Specialized community-safety teams develop deep knowledge of local partners and pathways, but personnel regularly move across roles and assignments, affecting where that knowledge sits within an organization.

At the same time, the resource landscape is constantly changing. Funding models shift, programs change, and eligibility requirements evolve making it difficult for even well-versed teams to keep up. While technology does not replace the relationships and expertise developed by specialized teams, it can help make organizational knowledge more consistently available.

Hapi also gives frontline members a way to contribute to what they learn in the field. A food program may close after a funding cut ora drop-in service may suddenly change its hours. Members can report these changes by texting Hapi so information is accurate and up to date for subsequent members. This keeps the resource knowledge grounded in specialized expertise, broader resource discovery, and what frontline members are seeing in practice, making them active contributors.

Turning Frontline Activity Into Insight

Officers may already share non-emergent resource information, but these interactions can be difficult to capture consistently at an organizational level. Hapi enables direct handoff through a QR-coded web link that community members can access immediately or later, including in their preferred language. Without capturing personal identifying information, the link can show whether an initial action, such as a call, was initiated.

At an aggregate level, these interactions can provide further insight into:

the needs frontline members are actually encountering, including patterns across time and location;
the types of supports and resources being sought and shared;
recurring needs or potential gaps in the local service ecosystem; and
whether community members take an initial step after receiving resource information.

This evidence can help inform conversations with municipalities, community organizations, and service providers about emerging needs and how they might be addressed more broadly through collaborative community safety and well-being efforts.

Connect with Duologue Systems

Hapi is currently being used in frontline practice with a regional police service in Ontario, providing an opportunity to understand how members adopt AI in practice while continuing to incorporate specialized community-safety knowledge through co-design. As members become more familiar with when and how to use Hapi, they can also help identify where AI is genuinely useful within existing frontline interactions. Police services interested in exploring Hapi for their own frontline and community-safety work can contact Jessica DeVries at jessica@duologuesystems.ca.

Jessica DeVries is Head of Research and Evaluation at Duologue Systems, where she leads research, evaluation, and governance work supporting responsible AI use in public safety and human services. For over a dozen years, she has provided research and evaluation consulting services to public-sector organizations across Canada to support evidence-based decision-making.

Note: This article represents the view of the author and provides information that may be of value to police professionals. It’s publication does not imply endorsement by the OACP.

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