Citizen Services AI847 applications Β· 2.4 day avg
Fraud DetectionΒ£2.1M detected Β· +340% vs manual
Procurement Intelligence284 contracts monitored
Benefits Fraud DetectionFull caseload Β· not sample
Data Quality AI94% accuracy Β· β16pts
Regulatory ComplianceNAO Β· PAC Β· ICO Β· all current
π‘ Live Intelligence Feed
Real-time AI activity Β· all agents
Why GovTechOS
π Citizen Services: 47 Days is Unacceptable
Citizens wait 47 days for service responses while rules-based processing steps take minutes when automated. AI reduces processing to 2.4 days while keeping civil servants in authority for all decisions.
π° Procurement Fraud: Β£4.1B Annually
UK government procurement fraud costs Β£4.1B per year. AI detects bid rigging, conflict of interest, and false invoicing patterns invisible to manual review β before contracts are signed or payments made.
π Benefits Fraud: Manual Detection Catches 15%
Benefits fraud costs Β£8.3B annually in the UK. Manual detection samples only a fraction of cases and catches just 15% of actual fraud. AI analyses the full caseload β not a sample.
All AI Agents
π
Citizen Services AI
Document intelligence, eligibility checking, case routing, response drafting. Processing time 47dβ2.4d. Civil servant approval required for all decisions.
847 processed today
Sequential + Rules
π
Benefits Fraud Detection
Pattern analysis across full caseload. Cross-reference employment, tax, housing. 67% detection improvement. All referrals human-reviewed.
Full caseload
ReAct + Anomaly
π°
Procurement Intelligence
Bid analysis, supplier relationship mapping, conflict of interest, invoice anomaly. Before payment β not after.
Citizen Services AI automates the high-volume, rules-based steps in government service delivery β document extraction, eligibility checking, case routing, and response drafting β while keeping civil servants in authority for all decisions. An application for housing benefit: AI extracts income, property, and household data from uploaded documents, checks eligibility against current entitlement rules, calculates the award amount, and drafts a plain-English decision letter β all in minutes. The civil servant reviews the draft decision, adjusts if necessary, and approves. Processing time: 47 days β 2.4 days. Citizen satisfaction: 4.3/5 vs 2.9/5 pre-AI. All decisions remain with authorised civil servants β AI accelerates and assists, never replaces public law accountability.
Fraud Flags (Active)
47
Investigation queue
Fraud Detected (Month)
Β£2.1M
Benefits + procurement
Detection Rate
+340%
vs manual sampling
False Referral Rate
8%
Human review filters
π Fraud Detection Intelligence
Fraud Detection AI analyses the full caseload β not a sample β and identifies anomalous patterns invisible to manual review. Benefits fraud: claimants declaring zero income while employer PAYE records show active employment. Procurement fraud: three suppliers submitting bids with identical formatting metadata, prices converging 0.01% below threshold. Identity fraud: multiple claims linked to the same bank account or address with different identities. All fraud flags are referrals for investigation β trained fraud officers review the evidence, determine facts, and decide whether to pursue. AI identifies patterns; investigators determine facts; authorised officers take enforcement action. Due process and natural justice are preserved.
Contracts Monitored
284
Live
Anomalies Flagged
12
Procurement review
Fraud Prevented (QTD)
Β£840K
Procurement intelligence
SME Compliance
94%
Fair access monitoring
π° Procurement Intelligence
Procurement Intelligence monitors the full public procurement lifecycle for anomalies indicating fraud, conflict of interest, or anti-competitive behaviour. Bid analysis: identical formatting, round-number pricing, and suspiciously clustered bids flag potential collusion. Supplier relationship mapping: AI identifies connections between bidding companies and evaluating officials through Companies House, LinkedIn, and shared directorships. Invoice fraud: invoices from shell companies, duplicate payments, and split invoices to avoid approval thresholds are flagged before payment. All anomalies are presented to the procurement compliance team as investigation priorities β no contracts are suspended automatically. Cabinet Office spend controls and procurement regulations are monitored continuously.
Data Quality Score
94%
β16pts from AI
Duplicate Records Found
847
This quarter
GDPR Compliance
100%
All processing lawful
Cross-Dept Sharing (GDPR)
Legal gateway
Enforced
π Data Quality & Governance
Data Quality AI detects duplicates, inconsistencies, and inaccuracies across government systems β reducing the burden on citizens to provide the same information multiple times to different agencies. GDPR compliance: all inter-departmental data sharing is checked against the legal gateway before processing. Citizens have the right to know what data is held and request corrections β the system maintains a citizen-accessible data record with full audit trail. Purpose limitation is strictly enforced: data collected for one purpose cannot be used for another without a documented legal basis. All data governance decisions β including data sharing agreements and purpose extensions β require Data Protection Officer approval.
π‘ Live Agent Trace
All decisions logged Β· full audit trail
π‘ AI Governance
Advisory intelligence β humans decide
No autonomous consequential decisions: All significant actions require human approval. AI recommends β authorised personnel decide and execute.
Full explainability: Every AI output includes source data, reasoning chain, and confidence level. No black-box recommendations.
Human override always available: Any AI recommendation can be overridden at any time. Override is logged and reviewed.
Regulatory compliance: All processes designed to applicable sector frameworks. Data processed under relevant legal basis. Audit trails maintained.
Statistical significance (p<0.05) required before promotion.
πͺ Feature Store
Vector IndexPinecone
Dimensions3,072
Indexed Docs284K
Retrieval P9542ms
π¦ Prompt Version Control
System promptsGit-tracked
Few-shot examplesVersioned
Eval datasetsDVC tracked
DevSecOps β Security-First CI/CD Pipeline
π CI/CD Pipeline
πSAST β Semgrep + BanditPASS
π¦SCA β SBOM + TrivyPASS
π§ͺUnit + Integration tests847/847
π―RAGAS eval gate (β₯0.92)0.94 β
πSecrets scan β GitleaksCLEAN
π³Container scan β Grype0 CRITICAL
π’Deploy β KubernetesDEPLOYED
π Security Posture
RBAC β Role-based accessEnforced
API keys β HashiCorp VaultRotated 30d
mTLS β Istio service meshActive
PII scrubbing β NeMoActive
Audit log β ImmutableCloudWatch
Pen testQuarterly
SOC 2 Type IIIn progress
ISO 27001Compliant
π Infrastructure as Code
TerraformCloud infra
HelmK8s workloads
ArgoCD GitOpsSynced
Kustomize overlaysdev/stg/prd
β»οΈ Rollback & DR
RTO Target<15 min
RPO Target<5 min
Blue/Green DeployActive
Auto-rollbackError rate >1%
π Regulatory Compliance
GDPR Art. 22 HITLEnforced
EU AI Act Art. 9Documented
NIST AI RMFMapped
ISO/IEC 42001Compliant
AI Observability β OpenTelemetry + Langfuse
π Observability Stack
L1TracesOpenTelemetry β Jaeger
L2MetricsPrometheus β Grafana
L3LLM TracesLangfuse (self-hosted)
L4LogsFluentd β OpenSearch
L5AlertsAlertManager β PagerDuty
π SLO Dashboard
Availability SLO99.9% target
Current (30d)99.96%
Error Budget73% remain
P50 Response0.8s
P95 Response3.1s
P99 Response7.4s
π¨ Active Alerts
Latency P95Normal
Error rate0.3% β
Token budget84% remain
RAG recall0.93 β
Latency drift+120ms watch
π¬ Langfuse Trace Explorer
π Avg Span Breakdown
API Gateway12ms
Auth + RBAC8ms
RAG retrieval42ms
Guardrail check18ms
LLM inference1,240ms
Tool execution84ms
Total E2E1,452ms
Guardrails β Responsible AI Framework
π‘ NeMo Guardrails β Active Rails
β Human-in-the-Loop (HITL) Gate
All consequential actions require human approval before execution. Confidence <0.85 always escalates. GDPR Article 22 compliant β no fully automated consequential decisions.
π PII Detection & Scrubbing
Microsoft Presidio + custom patterns. Names, emails, NI/SSN, card numbers scrubbed from all LLM I/O before logging. 47 entity types across 12 jurisdictions.
π« Toxicity & Hallucination Filter
NeMo topic rails block off-topic responses. Factual grounding check cross-references every claim against retrieved context. Hallucination >5% triggers human review queue.
β± Rate Limiting & Abuse Prevention
Per-user token budgets at API gateway. 10Γ anomalous usage triggers suspension + security alert. Cloudflare WAF DDoS protection.
π Audit Trail & Explainability
π Immutable Decision Log
Every AI recommendation logged: input context, retrieved docs, reasoning chain, confidence, model version, user ID, timestamp. 7-year retention for regulated decisions.
π Explainability (XAI)
Every recommendation includes source citations, confidence intervals, alternatives considered, and limitation disclosures. SHAP attribution for structured ML models.
βοΈ Bias Monitoring
Fairness metrics tracked across protected characteristics. Disparate impact analysis monthly. EU AI Act Article 10 data governance requirements met.
π Regulatory Mapping
GDPR Art. 5/22 Β· EU AI Act Art. 9/10/13/14 Β· NIST AI RMF Β· ISO/IEC 42001 Β· IEEE 7001 Transparency. Compliance evidence pack generated quarterly.
0.3%
Hallucination Rate
Target <2%
100%
HITL Coverage
Consequential acts
0
PII Leaks (30d)
Target: 0
A+
Security Grade
Mozilla Observatory
Multi-Agent Architecture β Mesh & Orchestration
πΈ Agent Mesh Topology
Orchestrator
Agent 1
Agent 2
Agent 3
Agent 4
Agent 5
Agent 6
Orchestrator decomposes tasks, routes to specialists, aggregates results, handles conflicts. All inter-agent communication via typed schemas. No agent takes external action without Orchestrator validation.
βοΈ Agent Patterns
ReAct β Reason + Act loopsAnalytical
Reflection β Self-critique cyclesHigh-stakes
Planning β Hierarchical decompositionMulti-step
RAG β Retrieval-augmented genKnowledge
HITL β Human-in-the-loopAll consequential
Tool Use β Function callingAll agents
π Temporal.io Orchestration
Active Workflows2,847
HITL Signals Pending47
Retry PolicyExp backoff Γ3
Saga PatternCompensating txns
Durable ExecutionCrash-safe β
π¨ Kafka Message Bus
Topics47 agent topics
Throughput12K msgs/s
Consumer Lag<100ms
Schema RegistryConfluent
Dead Letter QueueMonitored
π MCP Integration Layer
MCP β Data sourcesActive
MCP β CRM/ERPActive
MCP β Document storeActive
OAuth 2.0 authAll connectors
JSON Schema validationAll tools
Evaluation Framework β Continuous Quality Gates
0.94
Faithfulness
Gate β₯0.92 β
0.91
Answer Relevance
Gate β₯0.88 β
0.89
Context Precision
Gate β₯0.85 β
0.93
Context Recall
Gate β₯0.90 β
π§ͺ Eval Suite Composition
Golden dataset2,847 Q&A pairs
Unit evals (per agent)120β400 cases
Integration evals84 end-to-end flows
Adversarial probes47 jailbreak tests
LLM-as-judgeclaude-opus-4-5
Human eval cadenceWeekly 5% sample
π Eval-Driven Dev Flow
1
Change proposed β PR opened
Automated eval suite runs against golden dataset in CI. Results posted to PR.
2
RAGAS gate enforced
All metrics must meet thresholds. Failure blocks merge.
3
Canary deploy (5%)
Langfuse online evals on live traffic. Drift alerts trigger auto-rollback.
4
Full rollout + monitor
Weekly human eval sample. Monthly RAGAS full re-run.
Deploy K8s cluster. Provision Temporal.io, Kafka, PostgreSQL, Pinecone. Connect source systems via MCP. Establish data governance and RBAC. Run baseline eval on golden dataset.
2
Week 3β4: Core Agents Live
Deploy first 3 highest-value agents. Wire HITL approval workflows in Temporal. Configure NeMo guardrails and PII scrubbing. Set up Langfuse tracing and RAGAS eval gate.
3
Week 5β7: Full Agent Mesh
Deploy all agents. Configure Orchestrator routing. A/B test prompt variants. Enable drift detection. Train end-users on HITL workflow.
4
Week 8β10: Production Hardening
Pen test + SAST/DAST scan. Load test 10Γ baseline. Configure PagerDuty. Compliance review (GDPR, EU AI Act). Produce runbook. Go-live.
π 7-Layer Platform Stack
L7PresentationReact Β· Next.js Β· SSO
L6API GatewayFastAPI Β· OAuth2 Β· WAF
L5OrchestrationTemporal.io Β· LangGraph
L4Agent RuntimeNeMo Β· RAGAS Β· Tools
L3Model + ToolsClaude API Β· MCP servers
L2Data + IntegrationKafka Β· PostgreSQL Β· Redis
L1ObservabilityOTel Β· Langfuse Β· Grafana
π Integration How-To
MCP server per data source (REST/GraphQL/gRPC)
OAuth 2.0 service account per enterprise system
Kafka topics per agent capability namespace
Schema registry for typed message contracts
Data lineage via OpenLineage β Marquez
Webhooks for real-time event ingestion
dbt + Airflow for batch data refresh
π€ RBAC User Roles
ViewerRead dashboards
AnalystRun queries + export
ApproverHITL decisions
ManagerConfig + agents
AdminFull platform
AI EngineerModels + prompts
IdP via Okta/Azure AD. MFA enforced for Approver+.
π Incident Runbook
High latency (>5s): Check Langfuse trace β vector store β LLM API status
RAGAS gate fail: Roll back last prompt change β notify AI engineer
Error spike: Circuit breaker β fallback to previous version
PII leak: Suspend session β DPO notification within 24h