An Azure Logic App that manages capacity based alert rules and automatically increases volume sizes to prevent your Azure NetApp Files volumes from running out of space.

Effectively addressing Resource sizing, Resource Operation Timings, Security Policies, and Discount Recommendations by using cloud-native AI-based intelligent recommendations

Custom Amazon Aurora Auto Scaling solution using AWS Lambda and EventBridge that extends native Aurora auto-scaling capabilities. Automatically provisions reader instances across multiple AZs and instance types during capacity constraints, with intelligent scale-down based on CPU utilization.

Design and implement monitoring and evaluation frameworks. Measure and report on the impact of programs.

This project introduces an innovative parking management system driven by the STM32F401VE microcontroller. Experience efficient, hassle-free parking with real-time monitoring and smart features.

Stores capacity data in a Db and generates capacity charts according to selected data set in selected time range. Overall data preview for better look for company history.

Free & Open Source, Capacity Planning & Management Software, in a Complete Virtual Machine

Early Slip Predictor focused on identifying early indicators of delivery slippage by analysing capacity pressure and task behaviour across work centres. Using simple machine‑learning techniques and clear capacity metrics, the team demonstrated how likely future slip can be predicted early and translated into understandable risk signals.

This project solves the capacity optimization problem in surgical operating rooms.

Workshop capacity management system with waitlist automation

Pulumi component for launching EC2 instances with automatic fallback across instance types and availability zones on capacity errors (InsufficientInstanceCapacity)

SIGNAL delivered SIGNAL (Schedule Intelligence and Guidance for Noticing At‑Risk Lines), a production‑ready data enhancement and alerting engine that turns raw schedule and capacity data into early‑warning signals. The solution enriches datasets with drift metrics, risk scores, behaviour archetypes and plain‑English recommendations, read...

Delivery Risk Classifier explored predictive classification to identify tasks likely to complete late, focusing on understanding the limits of snapshot‑based delivery data and how modelling could still provide early warning signals. The team combined exploratory modelling with clear recommendations on how delivery datasets need to evolve to su...

🌐 Optimize network resources with The Network Godfather, an autonomous engine for efficient resource redistribution and management in 5G networks.

Delivery Confidence Radar built an early‑warning Delivery Confidence Radar that integrates activity and capacity data to surface instability, pressure and likely slippage before dates move. The solution emphasises explainable signals and a clear ‘what’s at risk, why, and where to intervene’ structure suitable for planners and senior lead...