Warner
AT&T
Sony
MTC
T-Mobile
Raiffeisenbank
LexisNexis
ORFAI-powered process automation for internal retail operations
Manual reporting and document-heavy internal workflows slowed decisions and consumed high-value staff time.
Identify high-impact AI use cases and launch a production-ready solution within 12 weeks, with fixed scope and a clear delivery date.
Automated reporting workflows and intelligent document classification integrated into the existing stack through API-based architecture.
AWS, Anthropic Claude, Python/FastAPI, SAP-compatible integration and GDPR-ready deployment.
A data protection gap in a third-party interface was identified before launch. The architecture was adjusted before production rollout.
Result figures are directional until customer approval for named publication.
Multilingual AI assistant for member services
A large volume of repeat enquiries overloaded service teams and increased response times.
Build a multilingual conversational AI system that handles standard requests while routing complex legal cases to human specialists.
A multilingual assistant with RAG architecture on top of the internal knowledge base and structured routing between automated and human support.
High compliance requirements, public sector sensitivity and multilingual user needs were part of the delivery constraints from day one.
Bias testing showed weaknesses in edge-case legal answers. Domain-specific tuning was completed before launch.
Result figures are directional until customer approval for named publication.
AI opportunity mapping plus computer-vision quality control
Several AI initiatives existed, but without prioritisation, ROI clarity or a strong decision basis for where to invest next.
An AI audit identified quality control on construction sites as the most valuable first production use case.
A computer-vision-based inspection workflow was designed for field usage, including edge execution where connectivity was unreliable.
Computer vision, edge computing, Azure IoT, Python and offline-capable deployment patterns.
A cloud-only approach would have failed on a significant share of sites. Edge inference and deferred sync made the rollout operationally viable.
Result figures are directional until customer approval for named publication.