Government Cloud
AI pipelines for
Government & Public Sector
Route constituent requests to the right department the first time, screen benefits eligibility across every program, and catch non-compliant procurement clauses before they become problems.
Constituent Case Intelligent Routing
The Problem
Government agencies handle thousands of constituent requests weekly across dozens of program areas. Cases are manually triaged by intake staff who may not know which department handles which issue. Cases bounce between departments — constituents wait weeks for routing before anyone works the actual issue.
Why not DIY?
Identifying the correct program area from a free-text constituent description, determining required documentation, and routing by both program AND urgency requires multiple LLM stages plus ConditionalFlowControl with compound branching. In Apex, that routing logic becomes unmaintainable as programs change.
Pipeline Stages
FlowMason Components
Realistic Outcomes
| Metric | Before | After |
|---|---|---|
| Routing accuracy | 60% | 94% |
| Time to first action | 5 days | Same day |
| Case bounce rate | Baseline | -70% |
Illustrative based on observed patterns. Your results depend on your data and implementation.
Benefits Eligibility Screening
The Problem
Eligibility workers manually review applications against program criteria for multiple benefit programs. Each determination takes 45–90 minutes. Workers must stay current on changing eligibility rules across 10–20 programs. Errors cause improper payments or eligible constituents being wrongly denied.
Why not DIY?
Checking eligibility across 10–20 programs in parallel — without hitting governor limits — is exactly what ForEach with async fan-out is built for. In serial Apex, checking 15 programs for 500 applications per day hits CPU limits before lunch.
Pipeline Stages
FlowMason Components
Realistic Outcomes
| Metric | Before | After |
|---|---|---|
| Determination time | 60 min | 8 min |
| Worker review required | 100% | 30% |
| Error rate | Baseline | -45% |
Illustrative based on observed patterns. Your results depend on your data and implementation.
Contract & Procurement Analysis
The Problem
Procurement officers manually review vendor contracts for compliance with standard terms, identify non-standard clauses, and check against approved vendor lists and budget authorities. A single contract review takes 2–4 hours. Backlogs delay projects. Non-compliant terms slip through under time pressure.
Why not DIY?
Extracting all clauses from a contract PDF (DocumentProvider), checking each against a policy library (two LLM stages), merging the results (CombinerNode), and routing by risk level (ConditionalFlowControl) is four separate orchestration concerns. FlowMason composes all four in a single JSON pipeline definition.
Pipeline Stages
FlowMason Components
Realistic Outcomes
| Metric | Before | After |
|---|---|---|
| Review time | 3 hours | 25 min |
| Non-standard clause detection | Inconsistent | 100% flagged |
| Officer capacity | Baseline | 3× contracts reviewed |
Illustrative based on observed patterns. Your results depend on your data and implementation.
Chat with your Government data.
Beyond the pipeline patterns above, FlowMason ships a chat surface admins drop on any Lightning page. Government users type plain-English questions; FlowMason generates SOQL, validates through the 8-gate sanitiser, runs under FLS, returns rows. Read-only by default.
Try asking:
- › "list permits stuck in review > 14 days"
- › "show me FOIA requests opened this month"
- › "which case workers have caseload over 40?"
FLS-aware. Allowlist-governed. Permset-gated. No data leaves the org.
Ready to build Government pipelines?
Tell us your use case. We'll show you exactly which pipeline pattern fits.
Talk to us about Government & Public Sector