Turn AI Potential into Business Reality.
Consulting, Workflow Design & Tech Evaluation for every stage of your AI journey.
(01)What we do
We support you from idea to production
Whether you need strategic AI insights, a rapid prototype or a full-scale system in production — we support you every step of the way.
Every great AI solution starts with a clear understanding of your processes. We identify the use cases with the biggest impact for your business.
How we work
- In-depth analysis by our AI architects
- Daily rate basis — flexible and transparent
Process & Data Audit
We review your workflows, systems and data to pinpoint where AI will create the most value.
What you get
- Prioritized list of AI use cases with ROI estimates
- Architecture and data-readiness report
- Concrete roadmap for the next 3–12 months
Strategy Workshop
In a focused workshop we develop your AI strategy together with your team.
What you get
- Shared vision & prioritized actions
- Risk and compliance assessment (EU AI Act, GDPR)
- Decision basis for management & stakeholders
We turn your most promising idea into a tangible prototype — test quickly and prove value before you invest in full-scale development.
How we work
- In a 1-week design sprint we bring together idea, UX and engineering:
Design Sprint
A structured week with stakeholders, user interviews and a first clickable prototype.
What you get
- Validated solution concept with real user feedback
- Interactive Figma prototype
- Clear implementation and resource plan
AI Prototyping Sprints
In 2–3 development sprints we build a working POC using your real data.
What you get
- Working prototype with LLM / agent integration
- Transparent evaluation (quality, cost, latency)
- Fact-based go / no-go recommendation
You already have a validated prototype? We turn it into a scalable, production-ready solution — including integration, security and team enablement.
How we work
- End-to-end delivery from architecture setup to go-live
- Integration with your existing systems (ERP, CRM, DMS, data warehouse)
- MLOps and monitoring pipelines
- Team training for day-2 operations
- Iterative releases with clear quality gates
AI systems are not off-the-shelf software — they need continuous monitoring, tuning and adaptation to new models.
How we work
- Continuous monitoring of quality, cost and drift
- Regular model updates and prompt optimization
- SLA-based support with fast response times
- Roadmap upkeep & quarterly evolution
Audit & Strategy
Every great AI solution starts with a clear understanding of your processes. We identify the use cases with the biggest impact for your business.
How we work
- In-depth analysis by our AI architects
- Daily rate basis — flexible and transparent
Process & Data Audit
We review your workflows, systems and data to pinpoint where AI will create the most value.
What you get
- Prioritized list of AI use cases with ROI estimates
- Architecture and data-readiness report
- Concrete roadmap for the next 3–12 months
Strategy Workshop
In a focused workshop we develop your AI strategy together with your team.
What you get
- Shared vision & prioritized actions
- Risk and compliance assessment (EU AI Act, GDPR)
- Decision basis for management & stakeholders
Prototype & POC
We turn your most promising idea into a tangible prototype — test quickly and prove value before you invest in full-scale development.
How we work
- In a 1-week design sprint we bring together idea, UX and engineering:
Design Sprint
A structured week with stakeholders, user interviews and a first clickable prototype.
What you get
- Validated solution concept with real user feedback
- Interactive Figma prototype
- Clear implementation and resource plan
AI Prototyping Sprints
In 2–3 development sprints we build a working POC using your real data.
What you get
- Working prototype with LLM / agent integration
- Transparent evaluation (quality, cost, latency)
- Fact-based go / no-go recommendation
Production rollout
You already have a validated prototype? We turn it into a scalable, production-ready solution — including integration, security and team enablement.
How we work
- End-to-end delivery from architecture setup to go-live
- Integration with your existing systems (ERP, CRM, DMS, data warehouse)
- MLOps and monitoring pipelines
- Team training for day-2 operations
- Iterative releases with clear quality gates
Operations & growth
AI systems are not off-the-shelf software — they need continuous monitoring, tuning and adaptation to new models.
How we work
- Continuous monitoring of quality, cost and drift
- Regular model updates and prompt optimization
- SLA-based support with fast response times
- Roadmap upkeep & quarterly evolution
(02)Why work with us
Great AI solutions deserve great craftsmanship.
We approach every project as if it were our own — applying years of experience, a passion for innovation, and a relentless focus on measurable business value.
Industry experts
Not just theorists — we speak at conferences, publish case studies, and actively shape the AI conversation.
Proven track record
Dozens of production AI projects from PoC to scaled systems. Our code and outcomes speak for themselves.
Senior-level only
10+ years of experience on average per engineer — you get real expertise, not expensive on-the-job learning.
End-to-end expertise
From strategy through data pipelines and LLM integration to UX and operations — all under one roof.
R&D-driven
We continuously evaluate new models, tools and frameworks so you always stay a step ahead.
No long-term commitments
Pause or stop at the end of any sprint — transparent and with no hidden costs.
(03)Our expertise
At the core of our work: AI solutions that hold up in real business operations.
We combine cutting-edge AI technology with agile methods and pragmatic engineering to deliver measurable outcomes.
AI Strategy & Consulting
Use-case discovery
We jointly identify the AI initiatives with the highest business impact — prioritized by ROI, feasibility and risk.
Hypothesis-driven approach
Every use case starts with a clear, measurable hypothesis so we validate ideas early — before heavy investment.
Compliance & EU AI Act
We build in data protection, GDPR and EU AI Act considerations from day one — so your AI is regulatory-proof.
Transparent roadmap
You get a concrete 3-, 6- and 12-month roadmap with clear milestones, owners and success criteria.
LLM & Agent Development
RAG & custom knowledge systems
We build retrieval-augmented systems that make your internal data securely and traceably available to LLMs.
Multi-agent architectures
Specialized agents solving complex tasks together — with clear ownership and eval-driven quality control.
Model-agnostic
We continuously evaluate OpenAI, Anthropic, Google and open-source models to pick the best fit for your use case.
Workflow Automation
Process reengineering
We don't just automate existing workflows — we challenge them and rebuild them AI-native.
Integration with your systems
ERP, CRM, DMS, ticketing, data warehouse — we wire AI logic seamlessly into your existing IT landscape.
Human-in-the-loop
For critical decisions we build in review workflows — the speed of AI, the control of a human.
MLOps & Operations
Monitoring & eval pipelines
Continuous quality, cost and latency measurement — you always know how your AI is performing.
Security by design
Prompt injection, data leakage, access control — we take AI security as seriously as classic app security.
Continuous improvement
Models and prompts are updated regularly so you benefit from every new release advance.
(06)Blog
Insights from our AI studio.
We share what we learn from customer projects, open-source work and continuous research — straight from the trenches, every week.
From Unboxing to private AI brain: Why I Built machine_setup_automation
A Strix Halo or DGX Spark is unpacked in minutes — yet a weekend still passes before the first token is generated. kwisatz reduces local inference server setup to a single YAML file and one command.
August 21, 2026 by Julian Weber
RAG Without Frontier Models: Why Good Retrieval Matters More Than the Biggest LLM
How our advanced RAG setup uses hybrid search, reranking, and local open-weight models—and why it does not need a frontier model.
June 24, 2026 by Manuel Spörer
LLMs Explained Clearly: Training, Model Size, Quantization, and K-Quants
What LLMs really are, how they are trained, which architectural differences matter, and why quantization and K-Quants determine whether local use is even practical.
May 18, 2026 by Manuel Spörer
Ready to build something extraordinary?
Get in touch today and start your AI journey with a partner who delivers outcomes, not slideware.