Public Sector AI solutions.

Public sector AI solutions for citizen services, case-work triage and document processing. They run on government platforms that every citizen can use, secure by default and transparent enough to audit.

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What makes public sector AI hard.

The public sector AI challenges we design for before any code is written, so the AI holds up with real users, real data and real auditors.

Accountable AI

Every AI recommendation is logged, explainable and reviewed by a caseworker, with documentation that stands up to procurement and audit.

Everyone is the user

Services must work for every citizen, including those on assistive technology and older devices.

Legacy estates

Modernizing decades-old systems in phases, without interrupting services people rely on.

Public sector AI solutions we build

The AI use cases we build for public sector teams, and the software platforms they run on. Each starts from a measurable goal, passes an eval gate before launch and reaches users through a gradual rollout.

The model work comes from our LLM and AI agent development team, tested by QA and AI evaluation. For results in production, browse our AI case studies.

Compliance we plan for

WCAG 2.2 AA
ISO 27001
GDPR

✓Citizen service assistants
✓Case-work triage and summarization
✓Forms and document digitization
✓Citizen-facing service portals
✓Legacy system modernization
✓Case management and workflow tools

Public sector AI development services.

The WAMO Labs services most public sector AI engagements draw on, from LLM integration to the platform around it.

AI integration

Our AI integration services put LLM applications, AI agents and RAG systems into the products and workflows you already run. Measured by evals, guarded in production, with a cost per request you can predict.

Custom web

Custom web application development for fast, AI-ready platforms that scale with traffic, data and your team. Copilots, smart search and clean APIs are part of the architecture, not a bolt-on.

Quality engineering

QA and software testing for business-critical apps: automated tests, performance and reliability work, plus evals and red-teaming that prove your AI features are accurate and safe before users see them.

Questions about public sector AI projects.

Timelines, cost drivers and compliance, answered plainly. More on how we build and evaluate AI in our AI engineering insights.

Which public sector AI use cases do you build?

Public sector AI projects we build include citizen service assistants; case-work triage and summarization; and forms and document digitization. Each one ships with a versioned eval set, guardrails and a gradual rollout, on the platform work listed above.

How long do public sector AI projects take?

Most engagements start with a four-week immersion. By week 3 a first slice is live behind a feature flag for a small share of users, evaluated and instrumented. By week 4 you have a quarter-by-quarter roadmap with named owners. Full timelines depend on scope, integrations and compliance review.

What drives the cost of public sector AI solutions?

Four things: the systems we integrate with (legacy case management and records systems), the compliance scope (WCAG 2.2 AA, ISO 27001 and GDPR), how much evaluation and human review the use case needs, and inference volume, because cost per request compounds with usage. We size all four during the four-week immersion, so you know what it costs to keep going before you commit to a roadmap.

How do you handle compliance and data privacy in public sector AI?

We plan for WCAG 2.2 AA, ISO 27001 and GDPR from the first sprint and decide which data may ever reach a model provider before anything is built. Every AI feature ships with access controls, an audit trail and human review wherever a wrong answer carries real risk.

Building AI in the public sector?

Tell us the AI use case or product you're working on. We respond within one business day, with a real human and a real opinion.

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