Found 63 results across all entity types
Passive hybrid energy storage systems are simple and efficient but lack flexibility in splitting power between batteries and supercapacitors during transient EV loads. Hybrid energy storage systems need real-time power-splitting decisions; poor control can reduce battery life, waste energy, and hurt system responsiveness. Reduces battery stress, power fluctuation, and harmonic distortion in EV hybrid energy storage systems while maintaining performance across changing driving conditions.
Campaign Management groups 1 use cases in real-estate around AI Agent Performance Benchmarking general source 1. Query: "Agent Performance Benchmarking" AI implementation real-estate
This application area focuses on automating the creation, maintenance, and governance of software Bills of Materials (BOMs) across the manufacturing software supply chain, including AI components. It continuously discovers and catalogs software packages, services, models, datasets, licenses, and vulnerabilities used in SaaS tools and internal applications. By maintaining a live, accurate inventory of all components, versions, and dependencies, it replaces static, manual BOMs that quickly become incomplete and outdated. For manufacturers, this matters because software and AI have become critical infrastructure, but visibility into what is actually in use is often poor. Robust BOM management improves security posture, supports regulatory and customer audits, reduces supply chain and vendor-lock risks, and accelerates change management (upgrades, deprecations, and incident response). AI is used to automatically detect components, infer relationships and dependencies, normalize metadata across disparate systems, and flag potential risks, enabling scalable governance of complex software and AI supply chains.
Intelligent Traffic Management refers to systems that monitor, analyze, and control urban traffic flows in real time using integrated data from signals, sensors, cameras, and connected vehicles. Instead of operating traffic lights and road infrastructure on fixed schedules or manual interventions, these platforms continuously optimize signal timing, lane usage, incident response, and routing recommendations based on current and predicted conditions. This application matters because growing urbanization is driving chronic congestion, increased travel times, higher emissions, and more accidents, while building new roads is expensive, slow, and often politically difficult. By extracting more capacity and safety from existing infrastructure, intelligent traffic management helps governments reduce delays, improve road safety, and lower environmental impact. AI is used to forecast traffic patterns, detect incidents automatically, and dynamically adjust controls, enabling cities to achieve better mobility outcomes without massive capital projects.
AI-supported decision tools and dashboards for managing parking demand, visitor traffic, pricing strategies, occupancy, and vehicle throughput in congested urban destinations to improve stakeholder planning and reduce adverse traffic impacts.
Intelligent energy optimization for chemical processing, distillation, and reactor operations
This AI solution focuses on using data-driven systems to plan, staff, and manage the total workforce—permanent, contingent, and gig—so that headcount, skills, and labor spend stay aligned with business demand. It encompasses strategic workforce planning (forecasting future talent and skills needs), operational workforce management (scheduling, time and attendance, staffing levels), and HR process automation for core tasks like screening, scheduling, and responding to employee queries. AI is applied to continuously forecast talent demand and supply, detect skill gaps, optimize schedules, and automate routine HR workflows. By replacing spreadsheet-based planning and manual administration with predictive models and optimization engines, organizations can make faster, more accurate decisions about hiring, upskilling, redeployment, and contingent labor use. This leads to better capacity utilization, lower labor costs, improved compliance, and a more consistent employee and customer experience, especially in dynamic, service-heavy environments and for small to mid-sized businesses without large HR teams.
Reinforcement learning and AI for HVAC optimization, building energy efficiency, and smart building management.
Intelligent home energy management and automation systems
AI-driven planning for renewable energy grid interconnection
Reduces grid dependence, improves local energy self-sufficiency, and coordinates EV charging with on-site storage under operational constraints. Manual inspection in radioactive zones is slow, risky, and prone to human error. Manages the variability of solar and wind generation without sacrificing grid stability or reliability.
This application area focuses on transforming how IT operations teams monitor, detect, and resolve incidents across complex, hybrid and multi‑cloud infrastructures. Instead of relying on manual log review, static thresholds, and reactive firefighting, these systems automatically ingest and correlate data from monitoring tools, logs, metrics, events, and IT service management platforms to identify issues early, cut alert noise, and pinpoint root causes. By applying pattern recognition and predictive analytics, the tools surface the most important incidents, predict emerging failures, and trigger or recommend remediation actions. This reduces downtime, shortens mean time to detect (MTTD) and mean time to resolve (MTTR), and allows smaller teams to manage larger, more complex environments with greater reliability and better digital user experience.
AI-driven management and optimization of distributed energy resources including solar, storage, and demand response integration.
Intelligent management and optimization of community solar programs
It addresses the problem of power grid congestion due to the increasing use of renewable energy sources, which can lead to inefficiencies and higher operational costs. Grid operators need better ways to handle congestion on transmission or distribution networks, where power flows can exceed safe limits and create reliability and cost issues. Manual inspection in radioactive environments is slow, risky, and prone to human error.
Banking, trading, risk management, fraud detection
Guest experience and revenue management
IT operations and service management
Other
IT Operations
Other
Other
Other
Other
Frontend
Analytics Platform
Company: AQR Capital Management
Sabre hospitality derived pricing management appears in 1 scoped applications and is modeled as a canonical company.
SynXis derived rate management integrations appears in 1 scoped applications and is modeled as a canonical company.
Manual portfolio revenue management appears in 1 scoped applications and is modeled as a canonical company.
ServiceNow Enterprise Service Management appears in 1 scoped applications and is modeled as a canonical company.
Collective management organizations appears in 1 scoped applications and is modeled as a canonical company.
Third-party bid management tools appears in 1 scoped applications and is modeled as a canonical company.
Telecom workforce management platforms appears in 1 scoped applications and is modeled as a canonical company.
commercial parking revenue-management platforms appears in 1 scoped applications and is modeled as a canonical company.
Atlassian Jira Service Management for HR appears in 1 scoped applications and is modeled as a canonical company.
Jira Service Management appears in 1 scoped applications and is modeled as a canonical company.
Atlassian Jira Service Management appears in 2 scoped applications and is modeled as a canonical company.
Contract lifecycle management platforms with AI appears in 1 scoped applications and is modeled as a canonical company.
Lease management software vendors appears in 1 scoped applications and is modeled as a canonical company.
Oracle Transportation Management appears in 1 scoped applications and is modeled as a canonical company.
Quality management system vendors appears in 1 scoped applications and is modeled as a canonical company.