Agivant runs a dedicated Azure practice that engineers data platforms, AI, and agents into the Microsoft tools your people already open every day. It starts with one business challenge and lands the answer where the work happens, in Teams, in Outlook, and in Copilot, with results in days and weeks.
Built on Microsoft Azure, with Azure Data Factory, Microsoft Fabric, Azure Synapse Analytics, Azure Data Lake Storage, Azure Machine Learning, Microsoft Foundry, and Copilot Studio, Agivant sizes running cost before anything goes live.
Get Amp’d to move from a Microsoft data estate to agents inside Microsoft 365
An Azure estate earns its keep when the business can ask it something. Amp’d is how Agivant gets there. Bolt scaffolds the agent stack, Forward Deployed Engineers build inside the enterprise’s own Azure tenant, and production grade agents answer through the Copilot surface people already use. Each engagement ships with evaluation and rollback, and every hardened pipeline, semantic definition, and agent pattern becomes a reusable asset the next build starts from. Every build amplifies the next.
Why Azure puts answers where the work already happens
If your identity sits in Entra ID and your work happens in Microsoft 365, the shortest route to AI adoption runs through the tools already on the desk. Answers show up where people work, on a security setup the company already trusts, and nobody has to learn a new application to get them. Microsoft Fabric and Azure Synapse Analytics work from OneLake and Azure Data Lake Storage, so the data stays in one place and stays useful.
What Agivant brings to Azure
Fabric and Synapse at the core
Agivant builds the analytics estate on Microsoft Fabric and Azure Synapse Analytics, and brings in Azure Databricks where a workload calls for it.
Copilot as the front door
Microsoft 365 Copilot and Copilot Studio put every layer of the stack one question away for the business.
Agents managed like employees
Each agent gets an identity in Microsoft Entra ID, so its access is granted, reviewed, and revoked the way a person’s is.
Applications as well as analytics
Agivant rebuilds the manual workflows around the data as working Azure applications.
Cost sized before it lands
Capacity, token budgets, and cost tags are set with the first pipeline, so spend shows up by team from the start.
Featured Azure solutions
Each one starts with a business challenge and lands in the Microsoft tools your organization already runs.
Copilot-ready data foundation
Data foundation
Give Copilot and Foundry something reliable to answer from.
An agent workforce inside Microsoft 365
Agentic operations
Let agents recommend the next best action, then follow through.
Predictive planning on Azure Machine Learning
Forecasting and risk
See demand, churn, and quality drift before they land.
Azure workflow applications
Application engineering
Rebuild the work that still runs on email and spreadsheets.
Key capabilities
• Data pulled from SQL Server, Oracle, SAP, and SaaS applications with Azure Data Factory • Analytics-ready tables shaped in Microsoft Fabric and served from Azure Synapse Analytics • A semantic layer holding business definitions such as recognized revenue and gross margin • Fabric Real-Time Intelligence keeping dashboards minutes behind the business
Built with
Azure Data Factory · Azure Data Lake Storage · Microsoft Fabric · Azure Synapse Analytics
Reported outcomes
up to 60%
faster reporting refresh and up to 35% less duplicated data movement
Data foundation
Give Copilot and Foundry something reliable to answer from.
Key capabilities
• Data pulled from SQL Server, Oracle, SAP, and SaaS applications with Azure Data Factory • Analytics-ready tables shaped in Microsoft Fabric and served from Azure Synapse Analytics • A semantic layer holding business definitions such as recognized revenue and gross margin • Fabric Real-Time Intelligence keeping dashboards minutes behind the business
Built with
Azure Data Factory · Azure Data Lake Storage · Microsoft Fabric · Azure Synapse Analytics
Reported outcomes
up to 60%
faster reporting refresh and up to 35% less duplicated data movement
How the four layers run on Azure
One engineering team carries a use case across all four, so each layer is built knowing what the next one needs.
Data
What Agivant engineers
Pipelines, lakehouse tables, and the semantic layer that gives business terms one meaning.
Built with
Azure Data Factory · Microsoft Fabric · Azure Synapse Analytics · Azure Data Lake Storage
AI/ML
What Agivant engineers
Forecasting, churn, and anomaly detection, retrained as fresh data lands.
Built with
Azure Machine Learning · Microsoft Fabric Data Science
GenAI
What Agivant engineers
Assistants that answer in plain English and show the source and definition behind every answer.
Built with
Microsoft Foundry · Azure OpenAI · Azure AI Search · Microsoft 365 Copilot
Agentic AI
What Agivant engineers
Agents that recommend the next best action and carry it out once a person approves.
Built with
Foundry Agent Service · Copilot Studio · Microsoft AutoGen · Microsoft Entra ID
Keep teams in control while agents work inside Microsoft 365
Every Agivant agent is production grade from day one, observable and always on. Each agent holds its own identity in Microsoft Entra ID, so access is granted, reviewed, and revoked the way it is for people. Routine steps run on their own, and anything carrying money or risk waits for the person who owns the decision.
FinOps, sized before workloads go live
Azure capacity is easy to buy and easy to leave running. Agivant sizes it against real workload patterns and sets token budgets before anything reaches production, so financial accountability, visibility, and cost efficiency are part of the architecture rather than a cleanup exercise two quarters later.
Token budgets per agent and per use case, with prompt caching and batch processing in Azure OpenAI
Provisioned throughput for steady workloads and pay-as-you-go for spiky ones, chosen per use case
Microsoft Cost Management budgets and cost tags showing spend by team and use case
Fabric capacity paused when idle, with Synapse serverless pools for occasional queries
Reported outcomes
up to 65%
lower token spend and up to 30% lower Azure capacity cost
Scale on Azure with identity-first engineering
Agivant connects through native Azure services and the Microsoft 365 surfaces the enterprise already runs, so data, agents, and applications sit inside your own tenant. Forward Deployed Engineers work in focused sprints, and every agent is registered in Microsoft Entra ID before it touches a workflow. This is what an Amp’d enterprise looks like in production.
Working with Agivant on Azure
Start with one business challenge
Something a team owns, with a number the business wants moved.
Design it against your Microsoft estate
Agivant maps the data, the Copilot surface, and the running cost before any build starts.
Ship inside your tenant
Forward Deployed Engineers work in your own Azure tenant, with results in days and weeks.
Carry it into the next one
Pipelines, semantic definitions, and agent patterns become reusable assets the next build starts from.
Proof from production
Gemini Enterprise engagements already running, with outcomes measured in the environment they were built for.
