Consulting

Expert consulting for Open Source AI adoption. Increase AI maturity, reduce costs, and maintain ownership of your AI code.

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Why Open Source with GC.OS?

Neutral non-profit with a major track record in open source AI

Keep AI adoption costs low and own your own AI code

Integrate with a rapidly moving open source ecosystem and newest developments

Connect with the international developer community, effective for hiring, retaining, and upskilling staff

OS synergies = adoption pathway for small and medium companies ("Mittelstand")

Engagement Opportunities

Scoping Activities

Where can I use AI? Discovery sessions, workshops, proof-of-concepts

Staff Integration

Integration into cutting-edge open source. Community of practice. Upskilling and developer training

Software Ecosystem

Co-development based on business needs. Development integration. Cost reduction through use of international standards. Avoiding "bespoke consultant software"

Why GC.OS?

GC.OS & Open Source AI

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

Commercial AI Providers

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

Where can we use AI with positive impact?

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)

Common follow-ons

• 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

Getting integrated with open source development. Upskilling on business-relevant skills and components

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

Framework: Open Source Fellows

Staff on secondment to GC.OS to develop open source software and receive mentoring

"Open Source Friday" or block time (e.g. summer)

Framework: Mentored Internships

Internships to attract talented early-career researchers with open source developer background

Develop software and internal use cases → recruitment and retention opportunity

Supportive activity

Teaching and seminars

Co-develop and Optimize Software Ecosystems

For organisations regularly deploying AI software

Requires some degree of capability and integration

Optimizing and plug-and-playifying component portfolios with open source. Move to standardized open source component libraries; create, develop. License and regulatory compliance processes, templating

Example 1: Cost–Impact Trade-offs

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!

Example 2: License Review and Regulatory Reporting

• 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?

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