We help government departments and public institutions improve citizen services and internal operations through controlled, auditable AI workflows.
Public-sector AI must improve service delivery without weakening accountability, privacy, or public trust.
We start with a specific service or administrative workflow, establish a measurable baseline, and test a bounded AI-enabled improvement in a controlled environment.
Administrative workflows with a clear baseline, a clear owner, and a measurable service outcome.
Route complaints to the right desk and draft a first response for officer review, with every classification logged.
Scheme information and application status in Hindi and relevant regional languages, with voice where appropriate.
Appointment reminders, scheduling, and completion notifications that cut avoidable visits.
Detect missing documents before submission rather than after rejection.
Surface files approaching a deadline and escalate them to a named officer.
Meeting summaries and file notes that keep decisions traceable across transfers.
Summarise tender documents and flag compliance gaps for human verification.
Turn field reporting into programme-progress dashboards that update without a fortnightly consolidation cycle.
These are design requirements, not policy statements. Each one has an owner and an evidence trail.
AI assists; authorised officers approve consequential actions.
Prompts, sources, decisions, overrides, and approvals are logged.
Data minimisation, role-based access, retention rules, and secure deployment options.
Outputs can be traced to relevant sources, rules, or documents.
Hindi and relevant regional languages, with voice support where appropriate.
Citizens can always reach a human or a conventional service channel.
Accuracy, escalation rates, language performance, and user feedback are measured before scale-up.
Start small, prove it, then scale what works. Durations are indicative and set at proposal stage.
| Engagement | Purpose | Typical duration |
|---|---|---|
| AI Readiness and Workflow Diagnostic | Identify priority use cases, risks, and data readiness. | 3–6 weeks |
| Controlled Pilot | Test one workflow in a sandbox or limited environment. | 8–16 weeks |
| Workflow Implementation | Deploy a production-ready workflow with training and handover. | 4–9 months |
| AI CoE Support | Build internal capability, governance, and a use-case pipeline. | 12–36 months |
| Capacity Building | Train officers and teams on responsible AI workflow design. | 2–10 days |
Tell us which service or administrative process you want to improve. We will respond with a scoped proposal for a bounded diagnostic.
Request a diagnostic proposal