In just a few days, we define and prototype your AI idea. With real use cases and rapid testing, you get clarity, validation, and a roadmap for execution – including technical feasibility.
Duration: 2 days + Prep & Follow-up
Target group: Product, innovation, and business owners solving real problems with AI.
This multi-day offsite format helps leadership teams build a realistic, organization-specific GenAI strategy. Away from daily operations, we evaluate your market, technology, and structures, and define your most impactful action areas for clear, aligned roadmap with realistic next steps and full organizational buy-in.
Duration: 3-4 days offsite (confidential format)
Target group: Executives, strategy leads, and decision-making teams.
In this strategic workshop, we develop a tailored GenAI ambition for your organization. Together, we define a shared understanding, clear goals, and a realistic vision for the role of AI in your business. It’s the ideal starting point for companies wanting to think ahead before building.
Duration: 1 day + Prep & Wrap-up
Target group: Management, strategic decision-makers, and transformation leads – especially in strategy, innovation, and digitalization.
This compact, benchmark-based assessment helps you evaluate how well your organization is positioned to leverage AI effectively. Together, we analyze the four key dimensions – strategy, processes, technology, and culture – to uncover blind spots, clarify your AI potential, and define actionable next steps.
Duration: 1½ days total (incl. Prep & Wrap-up)
Target group: Executives & decision-makers, especially: C-Level, department heads, digital, strategy & innovation leads, IT and process owners
This workshop lays the groundwork for targeted AI deployment. Together, we analyze core processes in your organization to identify where AI can deliver tangible impact—aligned with your tech and operational reality.
Duration: 3 × ½ day + Prep & Wrap-up
Target group: Management, process owners, business & ops teams, innovation managers. Suited for both entry-level and experienced teams.
In this practical workshop, we’ll build your first AI Agent prototype – tailored to your needs and tech stack. You’ll leave with a functional demo (80%+ ready), built in your own environment and ready for further development.
Duration: 1 day + Prep & Follow-up
Target group: Product and IT teams ready to get hands-on and test their first agent experience.
You bring the use case — we bring the AI expertise. We work together to validate your idea, design a fit-for-purpose solution, and build a functional prototype that fits your tech stack and workflows. Whether it's an internal tool, a client-facing assistant, or a data-heavy automation case — we’ll rapidly iterate with no-code or low-code tools, test feasibility, and deliver a first proof-of-concept.
Relevant for: Innovation teams, IT architects, and domain experts with specific challenges
This strategic hackathon helps leadership teams explore what a truly AI-first version of their company could look like – from structure to culture. Together, we build a future vision, key priorities, and a bold transformation blueprint.
Duration: 3 days offsite – weekends possible
Confidential format.
Target group: Executive boards, founders, and C-suite leaders with innovation mandate.
In this collaborative format, you bring the use case—we bring the AI expertise. Together, we’ll validate the idea, design the solution, and deliver a working prototype tailored to your tech stack. With rapid iterations and no-code tools, you’ll leave with a functional and testable PoC—built for real-world needs
Target group: Innovation Leads, Product Managers, IT Architects, C-Level Teams
Solutions:
Legal & policy document review
Compliance monitoring & alerts
Export control & ESG copilots
Relevant for: Legal, compliance, and ESG leaders in export-heavy, regulated sectors
Solutions:
Anomaly detection from sensors
Monitoring dashboards
Predictive maintenance copilots
Relevant for: Ops, quality, and maintenance teams in manufacturing and engineering firms
Solutions:
AI research agents for customer discovery
Automated sales collateral & pitch generation
CRM task assistants
Relevant for: Any sales team out there
Solutions:
Executive report copilots
Scenario simulation tools
Go-to-market optimization assistants
Relevant for: Strategy, finance, and executive teams driving growth or market entry
Solutions:
AI-assisted onboarding & role-specific training
Internal knowledge base copilots
Document-based learning assistants
Relevant for: HR, L&D, and operations teams in training-intensive or regulated industries
Solutions:
Virtual chat & email assistants
Sentiment and feedback analysis
Multilingual support copilots
Relevant for: Heads of Customer Service, CX & Support, B2B service providers, insurers, utility companies, companies with multilingual customer bases
Challenge:
Large models are compute-heavy and environmentally costly to run in production.
Our Solution:
We distill large models into compact, performant versions using advanced pruning techniques and knowledge distillation on HPC clusters.
Finding:
Our KafkaLM-15B achieved a 37.5% size reduction with over 90% of the teacher model’s performance, enabling faster inference, lower cost, and better carbon efficiency.
Challenge:
Enterprises overspend on AI inference by using the same model for every task, regardless of complexity.
Our Solution:
A smart, prompt-aware router that dynamically selects the optimal model for each task—reducing inference costs by up to 85% while maintaining output quality.
Finding:
Our LLM router achieved over 95% accuracy in model selection, enabling faster, cheaper, and more efficient deployments.
Challenge:
Lack of transparency in AI outputs creates trust and compliance issues, especially in retrieval-augmented generation (RAG) settings.
Our Solution:
We integrate real-time explainability algorithms that detect hallucinations and trace model reasoning paths through external knowledge.
Finding:
We reduced hallucinations in RAG scenarios by up to 95% and provided interpretable outputs aligned with the EU AI Act.
Challenge:
Most open-source LLMs underperform in European languages and require massive compute to fine-tune effectively.
Our Solution:
We train only the most relevant model weights (25%), maintaining performance while reducing compute and memory usage by up to 75%.
Finding:
High-performing, compliant models optimized for production in diverse multilingual settings.Finding: We successfully trained 24-language LLMs using distributed HPC infrastructure while preventing catastrophic forgetting and maintaining benchmark performance.
This multi-day offsite format helps leadership teams build a realistic, organization-specific GenAI strategy. Away from daily operations, we evaluate your market, technology, and structures, and define your most impactful action areas for clear, aligned roadmap with realistic next steps and full organizational buy-in.
Duration: 3-4 days offsite (confidential format)
Target group: Executives, strategy leads, and decision-making teams.
In this strategic workshop, we develop a tailored GenAI ambition for your organization. Together, we define a shared understanding, clear goals, and a realistic vision for the role of AI in your business. It’s the ideal starting point for companies wanting to think ahead before building.
Duration: 1 day + Prep & Wrap-up
Target group: Management, strategic decision-makers, and transformation leads – especially in strategy, innovation, and digitalization.
This compact, benchmark-based assessment helps you evaluate how well your organization is positioned to leverage AI effectively. Together, we analyze the four key dimensions – strategy, processes, technology, and culture – to uncover blind spots, clarify your AI potential, and define actionable next steps.
Duration: 1½ days total (incl. Prep & Wrap-up)
Target group: Executives & decision-makers, especially: C-Level, department heads, digital, strategy & innovation leads, IT and process owners
This workshop lays the groundwork for targeted AI deployment. Together, we analyze core processes in your organization to identify where AI can deliver tangible impact—aligned with your tech and operational reality.
Duration: 3 × ½ day + Prep & Wrap-up
Target group: Management, process owners, business & ops teams, innovation managers. Suited for both entry-level and experienced teams.
In just a few days, we define and prototype your AI idea. With real use cases and rapid testing, you get clarity, validation, and a roadmap for execution – including technical feasibility.
Duration: 2 days + Prep & Follow-up
Target group: Product, innovation, and business owners solving real problems with AI.
In this practical workshop, we’ll build your first AI Agent prototype – tailored to your needs and tech stack. You’ll leave with a functional demo (80%+ ready), built in your own environment and ready for further development.
Duration: 1 day + Prep & Follow-up
Target group: Product and IT teams ready to get hands-on and test their first agent experience.
This strategic hackathon helps leadership teams explore what a truly AI-first version of their company could look like – from structure to culture. Together, we build a future vision, key priorities, and a bold transformation blueprint.
Duration: 3 days offsite – weekends possible
Confidential format.
Target group: Executive boards, founders, and C-suite leaders with innovation mandate.
In this collaborative format, you bring the use case—we bring the AI expertise. Together, we’ll validate the idea, design the solution, and deliver a working prototype tailored to your tech stack. With rapid iterations and no-code tools, you’ll leave with a functional and testable PoC—built for real-world needs
Target group: Innovation Leads, Product Managers, IT Architects, C-Level Teams
You bring the use case — we bring the AI expertise. We work together to validate your idea, design a fit-for-purpose solution, and build a functional prototype that fits your tech stack and workflows. Whether it's an internal tool, a client-facing assistant, or a data-heavy automation case — we’ll rapidly iterate with no-code or low-code tools, test feasibility, and deliver a first proof-of-concept.
Relevant for: Innovation teams, IT architects, and domain experts with specific challenges
Solutions:
Legal & policy document review
Compliance monitoring & alerts
Export control & ESG copilots
Relevant for: Legal, compliance, and ESG leaders in export-heavy, regulated sectors
Solutions:
Anomaly detection from sensors
Monitoring dashboards
Predictive maintenance copilots
Relevant for: Ops, quality, and maintenance teams in manufacturing and engineering firms
Solutions:
AI research agents for customer discovery
Automated sales collateral & pitch generation
CRM task assistants
Relevant for: Any sales team out there
Solutions:
Executive report copilots
Scenario simulation tools
Go-to-market optimization assistants
Relevant for: Strategy, finance, and executive teams driving growth or market entry
Solutions:
AI-assisted onboarding & role-specific training
Internal knowledge base copilots
Document-based learning assistants
Relevant for: HR, L&D, and operations teams in training-intensive or regulated industries
Solutions:
Virtual chat & email assistants
Sentiment and feedback analysis
Multilingual support copilots
Relevant for: Heads of Customer Service, CX & Support, B2B service providers, insurers, utility companies, companies with multilingual customer bases
Challenge:
Large models are compute-heavy and environmentally costly to run in production.
Our Solution:
We distill large models into compact, performant versions using advanced pruning techniques and knowledge distillation on HPC clusters.
Finding:
Our KafkaLM-15B achieved a 37.5% size reduction with over 90% of the teacher model’s performance, enabling faster inference, lower cost, and better carbon efficiency.
Challenge:
Enterprises overspend on AI inference by using the same model for every task, regardless of complexity.
Our Solution:
A smart, prompt-aware router that dynamically selects the optimal model for each task—reducing inference costs by up to 85% while maintaining output quality.
Finding:
Our LLM router achieved over 95% accuracy in model selection, enabling faster, cheaper, and more efficient deployments.
Challenge:
Lack of transparency in AI outputs creates trust and compliance issues, especially in retrieval-augmented generation (RAG) settings.
Our Solution:
We integrate real-time explainability algorithms that detect hallucinations and trace model reasoning paths through external knowledge.
Finding:
We reduced hallucinations in RAG scenarios by up to 95% and provided interpretable outputs aligned with the EU AI Act.
Challenge:
Most open-source LLMs underperform in European languages and require massive compute to fine-tune effectively.
Our Solution:
We train only the most relevant model weights (25%), maintaining performance while reducing compute and memory usage by up to 75%.
Finding:
High-performing, compliant models optimized for production in diverse multilingual settings.Finding: We successfully trained 24-language LLMs using distributed HPC infrastructure while preventing catastrophic forgetting and maintaining benchmark performance.
