Product Development & Delivery
From idea to increment — deliver iteratively, hand over cleanly.
Discuss Your Project
Ergebnisse im Detail
Delivers a usable product increment in each iteration — testable, deployable, and stakeholder-ready.
Enthält- Working code with tests
- Acceptance criteria per feature
- Release notes & changelog
Gives stakeholders transparent insight into project status and enables data-driven steering decisions.
Enthält- Velocity metrics & burndown charts
- Risk & impediment tracker
- Sprint review protocols
Enables seamless continued development and integration by internal teams or external partners.
Enthält- API documentation (OpenAPI/Swagger)
- Architecture Decision Record (ADR)
- Code documentation & developer guide
Ensures a smooth transition to ongoing operations — with clear processes and escalation paths.
Enthält- Operational processes & monitoring setup
- Incident response & escalation paths
- SLA definitions & maintenance cycles
Minimizes risk during the transition to operations through a guided hypercare phase and clear handover criteria.
Enthält- Handover checklist & acceptance protocol
- Knowledge transfer sessions
- Hypercare plan (4–8 weeks)
Unser Vorgehen
- Product vision & business requirements
- Stakeholder requirements & priorities
- Technical framework conditions & infrastructure
- Sprint backlog + milestone plan
- Prioritized sprint backlog
- Design specs & acceptance criteria
- Feedback from previous sprints
- Production-ready increments + sprint reports
- Increments from sprint delivery
- Acceptance criteria & test cases
- Performance & security requirements
- Validated software + technical documentation
- Final product increment
- Operational requirements & SLAs
- Operations team & contacts
- Operations handbook + handover protocol
Typische Szenarien
AI Product from PoC to Production
Transition of a validated AI prototype into a production-ready system with sprint delivery.
Production-ready system + operations handbook
Iterative Development of a Decision System
Sprint-based development of an AI-powered recommendation system with incremental releases.
Working increments + stakeholder transparency
Operations Handover for Enterprise AI
Structured handover of an ML system to the internal operations team with documentation and runbook.
Operations handbook + hypercare phase