LLMOps Foundation for Enterprise AI Platform
Client: Fortune 500 enterprise
The Challenge
Multiple AI applications lacked centralized monitoring, evaluation, and governance, making it difficult to ensure reliability and compliance. Incidents were frequent and deployments were slow due to manual processes.
Our Solution
We established a comprehensive LLMOps foundation with evaluation pipelines, monitoring, versioning, and CI/CD gating for all AI applications. The platform included automated regression testing, prompt/model versioning, and rollback capabilities.
Results
Achieved 99.9% uptime, reduced incidents by 80%, and enabled rapid iteration with confidence in production deployments.
Measurement Period: 6 months post-deployment
Methodology: Platform monitoring and incident tracking
Time-to-Value
Total Duration: 8 weeks
- Kickoff: Week 1
- Architecture Review: Week 2
- Build Complete: Week 6
- Pilot Deployment: Week 7
- Production Rollout: Week 8
Architecture & Scope
Components Deployed
- Evaluation pipeline
- Monitoring dashboard
- Version control system
- CI/CD gates
- Rollback system
Integration Points
- GitHub Actions
- Datadog
- Slack alerts
- All AI applications
Risk & Controls Implemented
Audit Trails
Complete audit logging of all deployments and changes
Permission Models
RBAC for deployment approvals
Evaluation Harnesses
Automated regression testing before deployments
Compliance Controls
SOC 2-aligned controls and auditability
Artifacts
Screenshots
Sample Outputs
Example evaluation report and monitoring dashboard
Interested in Similar Results?
Let's discuss how we can help your organization achieve similar outcomes.