Vedi Systems
Vedi Systems helps you modernize data platforms on Azure Fabric and Synapse, activate analytics with Power BI and Azure AI, and ship event-driven applications with strong security and DevOps.
Productized offerings derived from our core Azure capabilities. Each engagement includes architecture, security baseline, CI/CD, documentation, and enablement.
Stand up a production-ready Fabric Lakehouse with medallion layers, governed zones, and a first analytics use-case.
Migrate legacy DW to Synapse or Fabric Warehouse with performance-tuned ELT and orchestration.
APIM + Service Bus/Event Hubs + Logic Apps/Functions to enable real-time integrations.
Power BI semantic model, KPI scorecards, and curated dashboards aligned to business outcomes.
A targeted Copilot using your data to summarize events, answer questions, and propose actions.
Fabric Lakehouse + Power BI to unify events and reduce reporting time.
Synapse + ML forecasting improved inventory planning.
APIM + Service Bus + Functions for event-driven integration.
Vedi Systems designs and delivers Azure-based data platforms and event-driven applications. We specialize in Azure Fabric & Synapse Lakehouse architectures, integrations with APIM/Service Bus/Event Hubs/Logic Apps/Functions, and pragmatic Data & AI solutions that create measurable business value.
Book a discovery call to scope outcomes, timelines, and success metrics. We’ll propose a plan and a right-sized start.
Effective 2025
We collect only the information needed to respond to inquiries and deliver services (e.g., name, email, phone, company). We do not sell personal data.
Data is processed to provide proposals, statements of work, contracts, and support. We use industry-standard security controls (RBAC, encryption, least privilege, secret management).
Retention is limited to the duration of the engagement or as required by law. You may request access, correction, or deletion by contacting pvedi@vedisystems.com.
Third-party processors (e.g., Microsoft Azure, GitHub, billing providers) are used where appropriate under data-processing agreements.