alongside

alongside labs

Developing responsible AI solutions alongside the people and organizations closest to the point of need.

A cluster of orange satellite dishes crowded onto a rooftop tower, pine branches in front, pale sky above.

We begin with the need, then ask what AI now makes possible, and what it can make accessible at a cost and scale previously out of reach.

Bring us a field need

alongside labs: building AI for social good, together with those closest to the problems

Organizations, frontline teams, and communities closest to society's most urgent challenges often understand exactly where existing services fall short and what better support could make possible. What they lack is rarely insight or commitment, but the technical imagination and capacity, implementation support and funding required to turn that knowledge into responsible, working AI systems that can expand reach and impact. alongside labs brings these conditions together. We start from recurring field problems and partner with you to co-design, build, deploy, and evaluate AI-enabled solutions in real-world settings, then adapt and scale what proves effective.

Where AI can be used in your mission

Support people directly

AI-enabled services that expand access to trusted information, guidance, and support across an individual journey.

Strengthen frontline delivery

AI-enabled systems that help frontline teams interpret information, coordinate services, and extend the reach of their work.

What becomes possible in practice.

A point of need that calls for labs

We look for the intersection of four conditions: a consequential need, a clear role for AI, the foundations for responsible deployment, and a credible path into everyday use. Where these conditions align, discovery ends and co-design begins.

Field need
A recurring and consequential problem, grounded in lived experience and frontline practice, that limits an important outcome. We begin with the need itself, particularly where existing approaches are falling short, rather than with a technology looking for somewhere to be used.
AI fit
A clearly defined task where current AI capabilities could make an approach meaningfully more effective, accessible, responsive, or scalable. The advantage over existing tools must be specific enough to test and significant enough to justify introducing AI.
Readiness
The data, infrastructure, delivery channels, organizational capacity, and safeguards required to test and deploy a solution responsibly. This means understanding whether it can work within the technical, operational, regulatory, and social realities of the setting.
Adoption
A credible path from prototype into sustained everyday practice, shaped around the people who will use, manage, and be affected by it. Trust, usability, local ownership, human oversight, and long-term maintenance are treated as part of the solution itself.

From point of need to proof of concept.

We listen across leadership, frontline teams, existing data, and the people affected, and define the need before anyone talks about tools. The output is a shared need statement, not an AI brief.

Communities and frontline teams are design partners, not research subjects. Together we map the whole journey, decide what must stay human, and set the language, consent, safeguards, and measures of success.

We configure or develop the components, content, integrations, human escalation, and monitoring the intervention needs. Context-specific parts stay visible instead of disappearing inside a generic product.

The intervention enters a defined setting with prepared staff, clear support routes, and stop conditions. Early deployment is deliberately bounded so the team can learn before expanding.

We assess technical performance, user experience, journey completion, and service outcomes, with evidence rigorous enough to trust and timely enough to improve the work.

If the work earns continuation, we identify what can be replicated, what must stay contextual, and which partner should carry the next phase. New context, new validation.

Two technicians stand at the top of a mobile tower above a city.

A field need needs more than one kind of partner.

For organizations

Bring a recurring need your team understands deeply, especially one where existing services, tools, or staffing models repeatedly fall short. You do not need to arrive with a technical solution.

Bring us a recurring field need

For funders

Support the work between a promising need and a responsible, evidence-producing intervention: discovery, co-design, implementation, evaluation, reusable infrastructure, and the path beyond a pilot.

Explore a labs funding partnership

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