Consulting
Expert consulting for Open Source AI adoption. Increase AI maturity, reduce costs, and maintain ownership of your AI code.
Why Open Source with GC.OS?
OS synergies = adoption pathway for small and medium companies ("Mittelstand")
Engagement Opportunities
Where can I use AI? Discovery sessions, workshops, proof-of-concepts
Integration into cutting-edge open source. Community of practice. Upskilling and developer training
Co-development based on business needs. Development integration. Cost reduction through use of international standards. Avoiding "bespoke consultant software"
Why GC.OS?
Neutrality as a mission
You own your own AI components
Staff upskilled and integrated
Transparent software ecosystem
You co-govern and own the software
Tax exempt for non-profit & research
Mid- and long-term benefit profile
AI owned by you
Push to lock-in, support rackets
Subscriptions and technology dependency
AI skills are gatekept by the provider
Hidden software with "surprises"
Assets and jurisdiction in Delaware or Texas
Paid services, fewer tax benefits
Short-term thinking benefit profile
AI "leased" to you
Scoping and Use Case Generation
For organisations exploring adoption of AI
Events, workshops, preparation to generate use cases
Expected outputs, outcomes
White paper on cost/benefit analysis and options
Project report and quick PoC code from study group
Follow-on projects ready for go / no-go decisions
How to get started
• Workshop, study group, preparation, report
• IP open where possible (e.g. open source software)
Typical scoping process
Assisted internal scoping & workshop (1–2 weeks)
Use case preparation for study group (1–3 months)
Data & software infrastructure maturation (1–6 months, internal parallel effort)
Study group event for rapid PoC generation (1 week, intensive)
• Internal proof-of-concept projects, follow-up (6–12 months)
• Supportive activity: mentored internships
• Supportive activity: open source
Staff Integration and Upskilling
For organisations using and adopting AI
Expected outputs, outcomes
Capability state: ability to quickly design and build AI solutions
Solid internal capability to navigate the open source ecosystem
Synergy effects through international community of practice
Staff on secondment to GC.OS to develop open source software and receive mentoring
"Open Source Friday" or block time (e.g. summer)
Internships to attract talented early-career researchers with open source developer background
Develop software and internal use cases → recruitment and retention opportunity
Teaching and seminars
Co-develop and Optimize Software Ecosystems
For organisations regularly deploying AI software
Requires some degree of capability and integration
Gartner (2024-07): Typical LLM project costs range from
• Embed: 150k + 500/month
• Extend: 1M + 10k/month
BUT:
• LLM not always needed! Earlier-generation ML is often OK or better
• Standardized open source components, self-hosting vs subscriptions (SaaS)
Impact can be a factor of 2–10 in upfront or running costs!
• License risks? AI Act and GDPR compliance processes?
• Equivalent open source solutions with much lower license costs?
Prior case:
Multinational using a licensed product instead of a 1:1 equivalent, permissive open source alternative
~500k/year instead of 0/year, discovered on day 1 of license review
Easy company-wide switch
GC.OS is non-profit — results are open domain and tax-deductible as research / public benefit
Ready to get started?
Contact us to discuss how GC.OS can help your organization adopt Open Source AI