Models in Production. Not Just Notebooks.
Deploy, version, monitor, and scale models. Detect drift before users notice. Rollback in seconds. MLOps built for Day Two, not Day One demos.
The Work That Pays
Traditional ML Is Not Dead. It Runs Your P&L.
Fraud scoring. Demand forecasting. Churn prediction. Pricing optimization. These run on structured data and gradient-boosted trees, not LLMs. They hit the bottom line directly and they have for years.
The real unlock is running both in one platform. A single workflow calls an XGBoost model and an LLM in the same pipeline. Same governance. Same observability. Same deployment path. No stitching together separate MLOps and AI stacks.
Demand Forecasting
Structured data. Time series. Runs on XGBoost, not GPT.
Fraud Detection
Millisecond inference. Tabular features. Production since 2015.
Churn Prediction
Retain revenue before it walks. Classification, not generation.
Pricing Optimization
Regression models on real transaction data. Direct margin impact.
The Full Model Lifecycle. Automated.
Training to production to monitoring to retraining. One platform handles it all.
Model Deployment
Single-click deploy. Automatic containerization, scaling, load balancing. REST APIs, batch inference, real-time endpoints. Pick your pattern.
Performance Monitoring
Accuracy, latency, throughput, resource usage - all tracked in real-time. Alerts fire on degradation before users file tickets.
A/B Testing & Canary Deploys
Split traffic across model variants with weighted random, feature-based routing, or multi-armed bandits. Canary deployments auto-progress from 1% to 100% with health-check-driven rollback. Built-in statistical analysis with sequential testing so you can monitor results without inflating false positives.
Auto-Scaling
Scale inference capacity on demand. Handle spikes without manual intervention. Scale down when idle. Pay for what you use.
Drift Detection
Detect data drift and model decay automatically. Get alerts when distributions shift. Retraining recommendations included. Models rot in production - we catch it.
CI/CD Pipelines
Automated testing, validation, and deployment. Quality gates before production. Integrates with your existing DevOps tools. No rip-and-replace.
Models That Stay Healthy in Production
Deployment is the starting line. The real work is keeping models running.
Weeks to Hours
Automated pipelines eliminate manual deployment steps. Standardized operations across teams. Ship models in hours, not sprint cycles.
99.9% Uptime
Automated health checks, failover, rollback. Your models work when you need them. Including at 2am on a Tuesday.
No Black Boxes
Full observability into behavior, performance, and costs. When something changes, you see it. Comprehensive logging and metrics.
Production Models. Day Two Operations.
Our FDEs deploy with your team. We fix what breaks. Fees at risk.