The six-phase OSS action plan
Build sovereign AI one proven phase at a time.
A structured path from a first fine-tuned model to a fully integrated, customer-controlled AI platform. Scroll to travel through each phase.
- Fine-Tuning Proof
- Dataset Factory
- Model Factory
- Private Knowledge / RAG
- Production AI Runtime
- AI-in-a-Box / Sovereign AI
The six phases
Input
- Representative task sample
- Candidate base models
- Target hardware profile
Output
- Fine-tuned adapter
- Benchmark report vs. baseline
- Go / no-go recommendation
Phase 1 of 6 · Roadmap
Fine-Tuning Proof
Prove, on your own hardware and data sample, that an adapted open model can do your task well enough to justify going further.
Technical architecture
Select an open-weight base model, set up a reproducible training environment, fine-tune with LoRA/QLoRA on a curated sample and run local inference against an evaluation set.
Key deliverables
- ▸Base model selection
- ▸Environment setup
- ▸LoRA / QLoRA fine-tuning
- ▸Evaluation datasets
- ▸Benchmarking
- ▸Inference testing
- ▸Model quality assessment
Convergence
Six phases. One AI-in-a-Box ecosystem.
Each phase contributes a component of the final platform: adapted models, governed datasets, a model lifecycle, private knowledge and a production runtime.
Discuss where to start
A Fine-Tuning Proof or a Private Knowledge pilot is a common starting point. We will help you choose.