01
Domain experts
Legal, medical, financial — narrow models that out-perform GPT-class on niche tasks.
[ 02 / Services ]
Custom Model Training
Fine-tuning Gemma 4, Llama 3 and proprietary architectures on your data for niche domain mastery.
02
[ Capabilities ]
01
RLHF Implementation
02
LoRA / PEFT Tuning
03
Evaluation Harness
[ Overview ]
Custom Model Training
Off-the-shelf models are good generalists and bad specialists. We fine-tune Gemma 4, Llama 3 and proprietary architectures on your data so the model becomes an expert in your domain — your tone, your taxonomy, your edge cases.
Every engagement starts with a data audit and an evaluation harness, because a model you can't measure is a model you can't trust. We run LoRA / QLoRA / full-parameter tuning, RLHF and DPO depending on the budget and the lift required, then ship the adapter or merged weights into your inference stack.
Result: smaller, faster, cheaper models that beat the frontier on the tasks that actually matter to your business.
[ What you get ]
- Fine-tuned model or LoRA adapter, weights delivered to you
- Reproducible training pipeline (code + configs + dataset cards)
- Eval harness with leaderboard against frontier baselines
- Inference deployment guide (vLLM, TGI, Ollama or managed)
- Cost & latency benchmark vs. closed-source alternatives
[ Where it shines ]
Where it shines
02
Style & voice
Lock the model to your brand voice, refusal behavior and structured outputs.
03
Cost reduction
Replace expensive API calls with a 7B model that wins on your specific workload.
04
On-device & private
Quantized models that run inside your VPC, on a laptop, or at the edge.
[ Tools & stack ]
Gemma 4 · Llama 3 · Mistral · QwenPyTorch · transformers · PEFT · TRLAxolotl · Unsloth · DeepSpeedvLLM · TGI · OllamaWeights & Biases · Langfuse
[ Frequently asked ]
Frequently asked
01How much data do we need?
For LoRA on a strong base model, a few thousand high-quality examples often beats tens of thousands of mediocre ones. We help you build the dataset before we touch a GPU.
02Can the fine-tune be hosted privately?
Yes — your VPC, on-prem or air-gapped. We deliver everything you need to host it without depending on us.
03How do you prevent regressions?
Every training run is gated by an eval harness with task-specific scores and frontier-model baselines.
[ 01 ]
What we deliver
UltraMVP combines deep model expertise with battle-tested production engineering. Every engagement ships measurable outcomes — not just prototypes — built on a stack that includes Claude Code, OpenAI Codex, and custom Gemma 4 fine-tuned adapters.
- RLHF Implementation
- LoRA / PEFT Tuning
- Evaluation Harness
[ 02 ]
How we work
- Step 0101
Discovery and technical audit (1 week)
- Step 0202
Architecture and model selection
- Step 0303
Build, evaluate and harden for production
- Step 0404
Deploy with observability and on-going optimization
Ready for the edge?
Fine-tuning Gemma 4, Llama 3 and proprietary architectures on your data for niche domain mastery.
Book a discovery call→[ MORE SERVICES ]
Services →01
Custom AI Development
End-to-end AI products: agents, copilots, RAG systems, and autonomous workflows built for production.
03
Claude Code & Codex Integration
Leverage the latest Anthropic and OpenAI coding agents to automate complex software lifecycles.
04
Rapid MVP Engineering
From blueprint to production in 4 weeks. High-fidelity AI MVPs built for scale from Day 1.