Edgefinity IoT is an enterprise RFID and real-time tracking platform designed to give organizations greater visibility and control over their operations. The platform connects RFID readers, sensors, and other IoT devices to automatically identify, locate, and monitor assets, inventory, work-in-process, tools, equipment, and personnel.
With configurable workflows, real-time alerts, facility maps, reporting, and a powerful rules engine, Edgefinity IoT turns RFID data into actionable information. Organizations can use the platform to automate inventory tracking, monitor asset movement, improve manufacturing workflows, manage safety and mustering, verify shipments, and create alerts when important events occur.
Hardware-agnostic and available for cloud or on-premise deployment, Edgefinity IoT can scale from a focused RFID application to an enterprise-wide visibility solution spanning multiple facilities and workflows.
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FinOpsly is an AI Cost Governance platform. It brings AI, cloud, data platform and SaaS spend into one attribution, policy and control layer, so enterprises can price a workload before building it, attribute every dollar to an owner, hold spend inside budget under policy, and prove what landed in run-rate.
Your AI invoice is not what your AI costs. One request draws on model tokens, retrieval, warehouse queries, GPU capacity and storage, and only the first shows up on the AI bill. FinOpsly resolves all of it, plus the seats in procurement and the compute in an untagged cloud account, to the same dimensions: owner, team, application, line of business, customer and tenant. An AI initiative's full cost becomes one figure, charged back through one hierarchy in one cycle.
Workforce AI is the tools employees use: seats and per-user token draw across GitHub Copilot, Cursor, ChatGPT Enterprise and Microsoft 365 Copilot. Application AI is the AI your product ships: tokens, compute and data joined into cost-to-serve across OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex AI, SageMaker and Databricks.
PLAN. Price a workload from its architecture before any resource exists, across model APIs, GPU capacity, data platform consumption and storage, with assumptions visible. Compare it across candidate models on your measured usage.
EXPLAIN. Attribute spend to owner, team, application, line of business and business unit across 9+ hierarchy levels. Unified tagging reconciles providers that tag inconsistently, and AI-driven bulk labeling closes large key estates. Unattributed spend is reported in dollars.
ACT. Budgets per project, team and API key, with daily burn-rate monitoring. Anomaly detection with root cause, routed to the owner. Waste detection using FinOpsly's own algorithms and ML models. Commitment planning across AWS, Azure and Google Cloud. Policy-driven parking of idle compute.
PROVE. Chargeback across AI, cloud, data and SaaS in one cycle. Realized savings tracked into run-rate against a no-action baseline. Cost per call, cost per active user, and cost-to-serve per customer and tenant.
proof: 100% attribution of AI spend; chargeback from 12.4 days to under one day across 9+ levels; 26% realized savings in AWS and 17%+ in Azure at a payments client.
Built for CIOs, CTOs and platform leaders accountable for technology spend, FinOps and finance teams running chargeback, and engineering teams who need cost signal before they decide
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PlugXR
PlugXR is a Creative Design Software development platform for spatial computing and immersive augmented reality (AR) applications. It helps creators, designers, and brands enhance customer experience with virtual showrooms, immersive AR product visualization & configuration, and other immersive content for marketing, branding, and other business applications. AR experiences can also be integrated directly into products to enhance the user interface or provide visual aids to users.
It simplifies the process of developing immersive tech applications, including Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), Immersive UI/UX designs, Spatial Computing experiences, and Metaverse applications.
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