Work

Named outcomes, honest labels.

Enterprise engagements are labeled “via” the contracting partner. Founder experience that predates QueUp is marked as such — never claimed as QueUp client work.

Embedded engagement · 16 months · via Akvelon
C#/.NETAzureOpenAIKustoGraphQL

RAG agents for automated task creation — Microsoft internal cloud platform (via Akvelon)

Problem

Engineering teams were manually reviewing completed work to plan follow-up tasks and assignments — slow, inconsistent, and unscalable across a global platform.

What we did

We researched and implemented RAG-based agents on the OpenAI platform, fed by ETL/background jobs that analyzed completed work and generated structured tasks and team assignments automatically. In a second phase we built the data backbone: integrations aggregating operational data over Kusto (KQL), SQL, GraphQL, and HTTP, surfaced through dashboards used by engineering and product leadership.

OutcomeAutomated a manual planning workflow on a global internal platform; QueUp's engineer was promoted to Senior mid-engagement in recognition of technical ownership.
Data platform · Performance Health, via ProfitOptics
C#/.NETAzureSQLETL

1TB ETL migration: data latency cut from ~48 hours to near real-time

Problem

A US healthcare distribution company ran reporting on a legacy ETL pipeline that took roughly two days to surface operational data — decisions were always made on stale numbers.

What we did

We redesigned the pipeline end to end: incremental ingestion, restructured staging, and cloud-native processing on Azure, migrating ~1TB of production data without interrupting reporting for the business.

OutcomeData latency reduced from ~48 hours to near real-time; availability preserved throughout the migration.
Platform handover · Tenderr
.NETAzureReact

Vendor-to-internal platform handover without losing velocity

Problem

Tenderr needed to take a vendor-built platform in-house — with full knowledge transfer, no regression in delivery pace, and a codebase its own team could carry forward.

What we did

We stabilized the system, documented the architecture, restructured the delivery pipeline, and ran a staged handover so the internal team took ownership incrementally rather than in one risky cut-over.

OutcomePlatform fully owned in-house; delivery continued through the transition. [Pending written permission for details.]
AI workflow · IDA (German research institute)
OpenAITextract.NETAzure

AI document workflow for a German research institute

Problem

Researchers were manually extracting structured information from large volumes of documents — repetitive work that consumed skilled staff time.

What we did

We built a document-automation pipeline combining Textract-based extraction with GPT-driven structuring and validation, integrated into the institute's existing workflow.

OutcomeReplaced a manual extraction workflow with an automated pipeline in production use.
Own product · live · fintech
.NETAzureReactReact Native

BaitulMal — donation-tracking fintech, designed, built, and operated by QueUp

Problem

Non-profits struggle to give donors transparent, real-time visibility into where money goes — most tooling is spreadsheets or opaque accounting exports.

What we did

We designed, built, and operate the full platform: .NET/Azure backend, React web app, React Native mobile app, and a white-label donation website offered as an add-on. Same team, same standards our clients get.

OutcomeLive product with real organizations onboarding; proof that we ship end to end with our own money and time.

Want the same shape of outcome?

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