# ML Model Deployments

URL: https://qualixsolutions.com/services/ml-model-deployments/

We take your trained ML models from prototype to production-grade deployment with monitoring, versioning, and infrastructure that holds under real traffic.

Models that run in production not just in notebooks.

#### Why this matters

- 85%: of machine learning models never make it to production. The gap between a working notebook and a deployed, reliable system is where most ML investments die.
- 60%: of AI projects lacking AI-ready data will be abandoned through 2026. The failure is almost never the model - it's data pipelines, governance, and quality.
- 80.3%: of enterprise AI projects fail to deliver intended business value. A third are abandoned before ever reaching production.

#### What you get

- Model Assessment & Production Readiness Audit
- Data Pipeline Engineering
- Model Serving & API Layer
- Infrastructure & Scaling
- Monitoring, Drift Detection & Retraining Pipelines
- CI/CD for ML (MLOps)

Service brief: 6-14 weeks. Good for CTOs, ML/AI Leads, Founders with trained models that need to ship

#### How we deliver this

1. Discovery workshop: We sit with you, map your workflows, users, and constraints. You leave with a scoped brief — not a proposal full of assumptions.
2. Architecture & Design: System design and UX decisions made before a line of production code.
3. Build: Sprint-based delivery with demos every cycle and one accountable lead.
4. Ship: Deployment to your infrastructure with docs and a clean handover.
5. Stabilize: 30 days of post-launch stabilization while real usage settles in.

#### FAQs

Q: We already have a trained model. Can you just deploy it?

Yes - that's exactly what this service is for. We take your existing model, assess its production readiness, build the infrastructure around it, and deploy it with proper serving, monitoring, and versioning. Most of our clients come to us with a model that works in a notebook but has never handled real traffic. We close that gap.