Opulentech
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All Case Studies
Enterprise AI Safety & Governance 12 Weeks 5 AI Specialists

TrustWise AI Governance

Designed and built an enterprise-grade LLM governance pipeline that monitors RAG outputs, enforces data privacy filters, and scores model alignment prior to user response delivery.

Outcome Metrics
< 120ms
Real-time Guardrail Latency
94.2%
Hallucination Reduction
1.2M+
Compliance Audits Logged
0
Security Incidents

1. Executive Summary

Enterprise AI risk evaluation engine providing real-time compliance checks, hallucination scoring, and vector retrieval validation.

2. Business Problem

Enterprise clients required strict compliance and zero PII leakage before deploying autonomous AI agents in production.

3. Technical Constraints

System had to integrate with existing third-party APIs while maintaining sub-100ms response times. Zero downtime requirements during migration. TypeScript strict mode enforced throughout.

4. Our Solution

Engineered a low-latency security proxy combining Pinecone vector filtering, semantic guardrails, and automated audit logging.

5. System Architecture & Data Pipeline

TrustWise AI Governance — Technical Architecture

01. Presentation

Enterprise App Interface

frontend
02. Ingress & Auth

TrustWise Proxy Gateway

api
03. Execution Engine

Semantic Guardrail Logic

logic

RAG Evaluation Engine

ai
04. Persistence Layer

Pinecone Vector Store

vectordb

Audit Trail Storage

storage
Hover over any architectural system node above to inspect dynamic details.

6. Technology Stack

PythonFastAPIOpenAI APIPineconeLangChainDockerAWS

7. Engineering Deliverables

Secured LLM queries against prompt injection & PII exfiltration
Built real-time analytics dashboard monitoring token costs and confidence scores
Created containerized microservices ready for AWS Elastic Kubernetes deployment

8. Lessons Learned

01.Early API contract definition prevents downstream integration failures.
02.TypeScript strict mode pays dividends during scaling phases.
03.Architecture documentation reduces onboarding time by 60%.
04.Separating read and write paths simplifies scaling decisions.

9. Future Roadmap Opportunities

Extend to mobile applications with React Native
Introduce GraphQL subscriptions for real-time dashboard updates
Add automated regression testing CI pipeline
Multi-region deployment for reduced global latency

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