Plenty of ideas, but no solid business case for AI in the company.
Pilot projects stall and never make it into production.
Uncertainty around data protection, compliance and the EU AI Act.
We put AI where it creates value: in your core processes. Instead of isolated pilots, we identify use-cases with a clear business case, build prototypes in weeks rather than months and move them into production in a controlled way, including governance, data protection and training. From generative assistants and AI agents to classic machine learning.
Production AI with measurable ROI, safely integrated, not an island solution.
We identify use-cases with real leverage, assess feasibility and business case, and prioritise your roadmap.
Assistants for knowledge, documents and customer service, securely connected to your systems via RAG pipelines.
Agents take on scoped tasks in service, sales and back office, with clear guardrails and escalation paths.
From concept to a testable prototype in a few weeks, with real data and feedback from your teams.
Monitoring, evaluation and versioning keep AI solutions maintainable and traceable.
Risk classification, documentation and processes for compliant AI use.
Policies, contracts and project knowledge are scattered. A RAG assistant answers questions with sources, permission-aware and inside your environment.
Incoming requests and receipts are sorted manually. AI classifies, extracts data and creates records in the target system, with a human in the loop for edge cases.
Recurring service requests tie up the team. An agent answers standard cases, escalates cleanly to staff and documents every step.
We understand your business, data and goals and define measurable success criteria.
We design the solution: system landscape, data model, integration and roadmap.
Iterative delivery in short cycles, with continuous quality assurance.
Safe rollout, team enablement and reliable support after launch.
The compact entry point: we analyse your starting point and goals and deliver a roadmap, architecture sketch and effort indication.
Delivery with a clear scope: iterative, with regular reviews, quality assurance and go-live support.
After go-live: support, maintenance and continuous development as a plannable agreement.
Knowledge search, document processing and service assistance usually deliver measurable value fast, because data and processes already exist.
Yes. We rely on architectures that keep your data in your environment and set up access on a least-privilege basis.
No. We build solutions your IT can operate and hand over the know-how in a structured way.
That depends on the use-case. After the assessment you get a clear effort indication before you commit.
We are vendor-neutral and choose by requirements, data protection and cost, from Azure OpenAI to Anthropic, including European options.
Before the start we define metrics such as handling time, automation rate or answer quality and evaluate against them.