What we do.
Five disciplines that complement each other — and make every story land.
01
Business Analysis & Requirements Engineering
Clarity before code.
What we do
- Sharpen problems and goals before solutions are discussed
- Structure requirements — epics, features, user stories, functional specs
- Define acceptance criteria and test strategy, support acceptance
- Translate between business, IT, and data
Typical situations
New platform, migration, legacy replacement, regulatory requirements.
02
Project & Program Management
Structure, cadence, and delivery — matched to context, not to a framework.
What we do
- Structure initiatives, set up roadmap and governance
- Align stakeholders, manage risks actively, secure delivery
- Classic, agile, or hybrid — we pick what works
- Turnaround and replanning in difficult phases
Typical situations
Cross-functional programs, regulatory initiatives, critical phases of an ongoing project.
03
Data-driven Workflows
From raw data to decisions — structured, traceable, reproducible.
What we do
- Connect, harmonize, and transform data sources into robust models
- Specify calculated figures — financial metrics, performance, risk, exposure
- Master reference and master data as confidently as time series, market data, and transaction flows
- Reporting and dashboards that don't just show — they serve as a basis for action
Typical situations
Fund data, calculated portfolio figures, risk and performance metrics, data hub initiatives.
04
Digital Transformation
Question existing processes — don't digitize them one-to-one.
What we do
- Reduce processes to their core — and drop what's only there out of habit
- Automate where it matters most
- Guide the change: tools, processes, and the people working with them
- Keep target pictures lean enough to actually get built
Typical situations
High-frequency manual processes, Excel workarounds, grown point solutions, stalled transformations.
05
AI-supported Processes & MVP Kick-Start
From use case to working solution — in weeks, not months.
What we do
- Identify and quickly validate high-impact AI use cases
- Build prototypes and MVPs — with our proven AI engineering process
- Spec-driven development, CI/CD, production-ready code
- A clear path from idea to live operation
Typical situations
Proof of concept, internal tools, idea-to-MVP.
Engagement models
Three ways to work with us.
Mandate via framework contract or payroller
For financial and insurance clients. Classic BA/RE/PO/PM mandates, embedded in existing procurement processes.
Direct engagement
For SME initiatives. Fixed-price or time-and-materials, clear scope, direct collaboration without intermediaries.
Partner capacity
For software and AI firms. Support in collaborations — business analysis, requirements engineering, product ownership, or program management.