Representative Engagements

What it looks like when we deliver.

Each engagement below is illustrative of the work we deliver — opening with the business outcome, followed by the technical execution that made it possible. Identifying details are withheld for confidentiality.

Healthcare · Reporting Modernization

From 14 hours to 90 minutes — weekly reporting, reinvented.

A regional health network was burning nearly two full workdays every week stitching together clinical and operational reports across Excel, an aging EMR export, and three siloed line-of-business databases. Leadership was making Monday decisions on Friday's data — and only sometimes.

We delivered a governed Power BI environment fed by Azure Data Factory pipelines and a star-schema SQL Server data warehouse. Row-level security separated clinical, operational, and executive views; refreshes ran on an automated schedule with built-in data-quality alerts so broken upstream feeds surfaced before reports did.

The result wasn't just a faster report cycle. It was a credible single source of truth — finally aligned with the metrics leadership actually wanted to manage to.

Power BI Azure Data Factory SQL Server Row-Level Security DAX
93%
Reporting time saved
1
Source of truth
24/7
Refresh monitoring
Government · Data Consolidation

Seven legacy systems. One source of truth.

A state-level agency was operating across seven disconnected systems — a 1990s AS/400, a Dynamics CRM, a case-management platform, a third-party financial export, an HR API, a document store, and an unholy amount of flat files. Cross-program reporting required three analysts and a week. Audits required prayer.

Nexvora designed and built a unified Azure data platform anchored by Azure SQL and orchestrated through Azure Data Factory. Each source got an idempotent ingestion pipeline with schema validation, error queues, and a metadata-driven framework so adding source eight wouldn't require rebuilding sources one through seven. PII was masked at the bronze layer; transformation logic was version-controlled and CI/CD-deployed.

The agency now runs cross-program reporting in hours instead of days — and crucially, every figure is auditable back to its source row, which is exactly what the inspector general was asking for.

Azure SQL Azure Data Factory Python SSIS CI/CD Data Masking
7→1
Systems consolidated
85%
Report turnaround cut
100%
Audit-traceable
Logistics · Workflow Automation

22 hours a week, quietly given back to the team.

A national logistics operator had six analysts spending two-thirds of their week on the same routine: downloading carrier rates, reconciling invoices against freight bills, exporting daily ops summaries, and emailing them to twelve stakeholders. Smart people, doing work a script could do in seconds, every single day.

We built a Python automation framework with scheduled jobs, structured logging, retry logic, and Teams-based alerting. REST API integrations pulled carrier rates directly; pandas-based reconciliation flagged exceptions instead of forcing humans to find them; Jinja-templated emails went out automatically with the morning's numbers attached. Failures escalated to on-call. Everything was containerized and version-controlled.

The team didn't shrink. The work the team could take on did.

Python pandas REST APIs Docker Azure Functions Teams Webhooks
22hrs
Reclaimed weekly
6
Analysts redeployed
0
Missed sends since launch
Nonprofit · CRM & Donor Intelligence

Donor visibility, finally worth the database.

A $40M-budget nonprofit was running its donor program out of a CRM that had been customized into a corner. Major-gift officers couldn't see giving history without three clicks; retention was measured quarterly because pulling it more often was painful; the development director was managing high-value relationships out of a personal spreadsheet.

We restructured the underlying CRM data model, rebuilt the donor 360 view with the metrics gift officers actually use mid-conversation, and layered in a Power BI retention dashboard pulling directly from the production database. Workflow automation handled stewardship cadence, anniversary acknowledgments, and lapsed-donor outreach without human intervention.

Within two quarters, donor retention moved from 61% to 89% — driven less by the technology than by the fact that gift officers could finally do their jobs the way they'd been trying to all along.

CRM Customization Power BI Workflow Automation Data Model Design SQL
61→89%
Donor retention
3.1×
Engagement signal
$2.4M
Added annual giving
Enterprise Operations · Cloud Migration

Twelve years of on-prem. Migrated. Zero data loss.

A mid-market enterprise had been quietly running on a server room that was older than half its employees. Hardware was past warranty, the DR strategy was "we hope so," and every audit cycle was a fresh exercise in creative explanation. The CIO knew it needed to move. The CFO wanted to know exactly what that meant for the budget.

We delivered a phased Azure migration plan — discovery, dependency mapping, target-state architecture, and a wave-based cutover schedule designed around real business calendars, not engineering convenience. Azure SQL Managed Instance absorbed the SQL Server estate; App Service and AKS hosted the modernized application tier; Blob Storage replaced the aging SAN. Entra ID consolidated identity. Every workload had a rollback plan that was actually tested.

Twelve years of accumulated infrastructure moved in a clean phased cutover with zero unplanned downtime and zero data loss — and the new monthly cloud spend came in 34% under the old hardware + facility + maintenance run-rate.

Azure SQL MI App Service AKS Entra ID Bicep / IaC Azure Monitor
0
Unplanned downtime
34%
Lower run-rate
100%
Audit-ready
Enterprise IT · Infrastructure Automation

From four weeks to four hours.

An enterprise IT team was provisioning new endpoint environments by hand — domain joins, baseline configs, monitoring agents, application payloads, the whole catalog. Every refresh wave took four weeks of two engineers' time, and every refresh wave produced a slightly different fleet than the last one.

We designed a PowerShell automation framework around DSC, deployment orchestration via Azure Arc-enabled servers, and signed module distribution through a private gallery. Idempotent scripts handled identity provisioning, DSC-managed configuration, monitoring registration, and post-deployment health checks. Everything was version-controlled, peer-reviewed, and ran inside an auditable pipeline.

The first end-to-end run of the new framework provisioned 200 machines in under four hours — fully configured, monitored, and identical. The engineers got their lives back, and the fleet finally looked like a fleet.

PowerShell DSC Azure Arc Git + CI/CD Azure Monitor
4wks→4hrs
Deployment time
200
Nodes per run
100%
Config consistency

See yourself in any of these? Let's talk.

Start a conversation → admin@nexvoratechgroup.com