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Stefan Manja
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01 / selected work

Selected work

Delivery choices, system shape, and outcomes from real internal AI work.

The current case studies come from in-house work at Delta Holding. They cover the workflow, the system decisions behind it and the measured outcomes, without exposing internal material that should stay internal.

Delta Holding

Case 01

Credit-risk decision-support workflow

A credit-risk decision-support workflow built in-house at Delta Holding. Combines public-company risk signals with internal context into recommendations.

Context
B2B credit-risk analysis and limit-setting workflow inside a multi-entity enterprise finance function.
Outcome
Observed workflow outcomes included ~75% faster analysis and report preparation versus the existing RPA-supported process, 4.4/5 analyst-rated quality and 90%+ recommendation acceptance.
  • Python
  • LLM APIs
  • Workflow design
  • Structured decision support
Read the case study →

Delta Holding

Case 02

Self-hosted internal knowledge assistant

A self-hosted internal knowledge assistant built in-house at Delta Holding, with Azure AD access, operator surfaces and usage + cost observability.

Context
Internal enterprise knowledge-access system serving multiple business units, with requirements around access control, quality governance and operational visibility.
Adoption and feedback signal
Used by 300+ unique employees during the first month after launch, with 85%+ positive explicit feedback on thumbs-up/down responses.
  • Flask
  • Docker
  • PostgreSQL
  • pgvector
  • LangChain
  • Azure AD SSO
Read the case study →

Workflow review

If you have a similar internal AI workflow to build or harden, I can review the workflow shape.

A short note on the workflow, users, current stage, and constraints is usually enough to tell whether build or advisory work makes sense.

Send a workflow for review See workflow starting points