Three disciplines. One team.
Most firms sell you one of these in isolation — an infrastructure vendor, a BI shop, or an "AI strategy" deck. We run all three as a single pipeline, because that's the only way any of them actually holds up in production.
Move off what's fragile, onto what scales
We design Azure environments from the ground up — or migrate you off aging on-prem SQL, SSIS, and SSRS platforms without a disruptive rip-and-replace. This includes hybrid networking (ExpressRoute, VPN) for organizations that need Azure and on-prem to run side by side during a transition.
What's included
- Azure infrastructure & hybrid network design
- Legacy database migration (on-prem SQL Server → Azure SQL)
- Data Lake architecture (hot / cool / archive tiers)
- DevOps pipelines for continuous deployment
What's included
- Azure Data Factory pipelines & orchestration
- Cosmos DB & document-store design
- Event-driven architecture (Event Hubs, Logic Apps, Functions)
- Third-party API integration (Salesforce, Shopify, and similar platforms)
Make your systems talk to each other, reliably
This is the layer most transformations quietly fail on. We build the pipelines and event-driven services that keep CRM, field systems, e-commerce platforms, and internal databases in sync — with a rules engine underneath when regulatory or business logic requires it.
AI as a working help engine, not a pilot project
Once your data is clean and flowing, we build the layer people actually interact with: predictive models, generative design tooling, and dashboards. The goal isn't a research demo — it's a system your team opens every day because it answers real questions faster than they could on their own.
What's included
- Predictive models for forecasting & risk (k-NN, unsupervised learning)
- Generative design tooling built on your own data
- Power BI dashboards tied to a governed data warehouse
- Data mining for pattern discovery across historical records
Not sure which stage you need first?
Most engagements start with a short systems review — we'll tell you honestly whether the bottleneck is infrastructure, data, or the missing insight layer.