Misinformation Guardian Platform
Live risk analysis, evidence scoring, and human escalation for high-stakes content
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The Problem
Creators, teams, and audiences face rapid misinformation spread across posts, videos, and articles. Manual verification cannot scale fast enough, and unstructured moderation often creates inconsistent outcomes.
The Solution
Deploy a layered guardian architecture: intake normalization, multi-signal risk scoring, explainable verdicting, confidence-aware recommendations, and escalation workflows for sensitive domains such as health, elections, and finance.
Overview
A production-grade misinformation defense platform that analyzes live text or URLs, scores manipulation risk, extracts claims, and routes high-risk items to policy-aware human review with full auditability.
Architecture
Components
Input Gateway
networkingReceives URL/text submissions with schema validation, auth, and anti-abuse checks.
Service: Next.js API Gateway / Cloudflare / API Gateway
Content Extractor
computeFetches and normalizes text from URLs or direct user payloads with SSRF safeguards.
Service: Serverless Functions
Misinformation Signal Engine
ai-serviceRuns manipulation heuristics, source checks, claim extraction, and anomaly scoring.
Service: Guardian Rules + LLM Verifier
Risk Fusion Layer
computeAggregates heterogeneous signals into calibrated risk score, verdict, and confidence.
Service: Risk Scoring Service
Policy Router
securityApplies policy bundles and determines auto-pass, warn, block, or human escalation.
Service: OPA / Custom Policy Engine
Guardian Response API
computeReturns explainable analysis payloads, recommendations, and evidence traces.
Service: REST/GraphQL API
Human Review Queue
computeRoutes high-impact cases to analysts with triage SLA and adjudication tooling.
Service: Queue + Review Console
Evidence Store
databaseStores signals, verdict history, source snapshots, and appeal metadata.
Service: PostgreSQL + Object Storage
Decision Ledger
monitoringImmutable audit trail for policy decisions, reviewer actions, and model versions.
Service: Data Warehouse + SIEM
Implementation Steps
Guardian Core MVP
2-3 weeks
Ship deterministic scoring with explainable outputs and basic URL ingestion.
Tasks
- Implement input validation and anti-abuse controls
- Build deterministic signal engine and calibrated risk scoring
- Expose analysis endpoint + dashboard preview
- Store analysis metadata for retrospective tuning
Deliverables
Policy + Escalation Layer
3-4 weeks
Introduce policy routing and high-risk human review workflows.
Tasks
- Define policy bundles per domain (health, election, finance)
- Implement escalation queue with triage SLA
- Add reviewer notes, final disposition, and appeal path
- Create feedback loop for signal tuning
Deliverables
Production Hardening
3 weeks
Scale with observability, evaluation harnesses, and compliance controls.
Tasks
- Add drift monitoring and false-positive/false-negative dashboards
- Run red-team misinformation suites and threshold calibration
- Implement full audit logging and retention policies
- Enable canary release + rollback procedures for policy/model updates
Deliverables
Code Examples
Risk Fusion Pipeline (TypeScript)
Combines weighted signal impacts into a bounded risk score with explainability.
type Signal = { id: string; impact: number }\n\nexport function computeRisk(signals: Signal[]) {\n const baseRisk = 28\n const score = signals.reduce((sum, signal) => sum + signal.impact, baseRisk)\n const bounded = Math.max(0, Math.min(100, score))\n\n return {\n score: bounded,\n verdict: bounded >= 76 ? 'critical' : bounded >= 56 ? 'high' : bounded >= 36 ? 'guarded' : 'low',\n explanation: signals.map((s) => s.id),\n }\n}Policy Routing Example (YAML)
Escalate high-risk health/election content to human review.
policies:\n - id: high_impact_escalation\n when:\n risk_score: '>=56'\n domain: ['health', 'election', 'finance']\n action: 'human_review_required'\n sla: '15m'\n\n - id: guarded_warning\n when:\n risk_score: '>=36'\n action: 'show_warning_with_sources'Cost Estimate
$6,800
per month
$81,600
per year
Assumptions: 300K analyses per month, 5-10% escalation rate to human review, Multi-region deployment with 99.9% availability target
Use Cases
Technologies
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