Predictive Analytics for Infrastructure, Workloads & Business Processes
Forecasts for systems, costs, utilization, and operational processes
We develop predictive analytics models based on your real data that accurately predict what will happen next in your systems, processes, and cost structures.
From infrastructure and engineering to operations, production, and business analytics. Our models combine ML, time series analysis, heuristic rules, and domain-specific logic — perfectly tailored to your cloud, DevOps, or production environment.
What Predictive Analytics Delivers for You
- Workload and capacity forecasts: predict system load, detect upcoming bottlenecks, plan scaling and resource needs
- Cost forecasting: predict infrastructure and operational costs, detect expensive services and anomalies, recommend cost optimizations
- Failure, outage, and risk predictions: detect signs of instability, unusual error patterns, risky configurations
Automation eliminates these risks completely.
What the Solution Includes
Workload & Capacity Forecasts
We detect patterns in your load peaks, events, and deployments:
- Prediction of system load (CPU, RAM, I/O, Network)
- Detection of upcoming bottlenecks
- Planning of scaling and resource requirements
- Optimization of autoscaling strategies (Kubernetes, Cloud, CI/CD Agents)
- You can avoid bottlenecks before they occur
Cost Forecasting (Cloud, Infrastructure, Workflows)
Our models predict your infrastructure and operational costs:
- AWS/GCP/Azure/Hetzner cost models
- Prediction of expensive services, peaks, and anomalies
- Detection of inefficient deployments or resources
- Recommendations for cost optimization
- You keep budget and scaling under control
Failure, Outage & Risk Predictions
Predictive ML detects signs of instability:
- Upcoming outages or latency spikes
- Unusual error clusters
- Unstable deployments
- Risky configurations
- Security anomalies in logs & events
- Your systems become proactive instead of reactive
Process & Production Forecasts
Ideal for engineering, manufacturing, and internal processes:
- Demand & material forecasts
- Delivery times and bottleneck models
- Production capacities and machine load
- CPQ parameters, weight, material consumption
- Technical specifications based on historical data
- Perfect fit for CPQ/BOM/engineering use cases
Business Metrics & Sales Forecasting
We create models that make KPIs understandable:
- Lead and demand forecasts
- Conversion forecasts
- Risk scoring & prioritization
- Cash flow and cost trends
- Seasonal or market-driven patterns
Deep Integration with Your Systems
Our predictive analytics solutions use data from:
- Kubernetes, CI/CD, GitHub Actions
- Prometheus, Grafana, Loki, ELK, Sentry
- ERP, CRM, and production systems
- Databases, ETL pipelines, warehouses
- Logs, events, telemetry, metrics
- Cloud API data (AWS/GCP/Azure)
- We build models around your real infrastructure and processes — not abstract "AI toys"
How It Works
- 1Data Analysis — We analyze your historical data, metrics, logs, and system behavior.
- 2Model Development — We develop predictive models tailored to your infrastructure and business processes.
- 3Integration — We integrate models with your monitoring, logs, ERP, CRM, and internal systems.
- 4Training & Calibration — We train models on your real data and calibrate for accuracy.
- 5Deployment & Monitoring — We deploy models, create dashboards, and set up alerts for predictions.
Predictive analytics makes teams faster, safer, and less dependent on manual analysis.
Why It Matters
Ideal For
DevOps & SRE Teams
Infrastructure capacity planning, cost forecasting, and risk prediction.
Engineering & Production
Workload forecasting, material demand, and production capacity planning.
Operations & Logistics
Process forecasting, bottleneck detection, and operational risk management.
What You Get
Want to Finally See Risks and Costs in Advance?
We create forecasting models based on your real systems — precise, scalable, and deeply integrated.