Service · Model adaptation
P5Domain Adaptation Pilot.
Fine-tuning either works for your case or it doesn't. Rather than commit to a production build to find out, the pilot proves it in four to eight weeks — with a measured evaluation harness that shows the gap between the baseline model and the tuned one, on your data, for your task.
Outcomes
What changes when the engagement lands.
Proven lift, measured
You know exactly how much better the tuned model is versus the baseline. Numbers, not vibes.
A hosted pilot endpoint
The tuned model available for your team to use directly during the pilot period.
A reproducible pipeline
The training pipeline documented and reproducible. Ready to run again for production.
Go / no-go clarity
By week eight you know if the production commitment is worth it. Evidence-based decision.
Deliverables
What's in the engagement.
A four- to eight-week fine-tune pilot: dataset preparation, LoRA or QLoRA adaptation of a base model, a measured evaluation harness comparing baseline against tuned, and a hosted pilot endpoint. Answers 'does this actually work for us' before the production commitment.
Prepared dataset
Training and evaluation data prepared to the standard the tuning requires.
Tuned model
LoRA or QLoRA adaptation of the agreed base model. Hosted for pilot use.
Evaluation harness
Measured baseline vs tuned scores against your task. Reproducible, not one-off.
Runbook and recommendation
Documented pipeline. Recommendation on production readiness.
How we deliver
Fixed scope. Named phases. Duration on the cover.
The engagement is priced against the outcome, not open-ended hours. Every phase has a duration, a named deliverable, and a check-out.
Total duration4 to 8 weeks
Sales cycle6 to 10 weeks
- 011 to 2 weeks
Dataset prep
Training and evaluation data prepared, cleaned, and split.
- 022 to 4 weeks
Adaptation
LoRA or QLoRA fine-tune. Iterative training against evaluation harness.
- 031 to 2 weeks
Pilot hosting
Model hosted on pilot endpoint. Team access provided. Usage measured.
Built for
Buyers this engagement fits.
Typical buyer
CTO, Head of AI, Chief Data Officer
Teams whose fine-tune feasibility says yes
P4 said go. This is where you go.
Businesses whose base-model output is close but not quite
The generic model gets 80% of the way. The pilot proves what tuning delivers on the last 20%.
Related services
Where this leads next.
Fine-Tuning Feasibility & Data Readiness
Fine-tune vs RAG vs prompting. Data audit. Base model shortlist. Costed build proposal.
Production Fine-Tune & Deployment
Reproducible pipeline. Multiple adapters. Serving stack. Guardrails. Provenance. Client IP.
Document & Dataset De-identification
Batch de-identify a corpus. Key management. Validation sampling. Safe for analytics, RAG, or training.
Talk to us.
45 minutes on your operation and the engagement you have in mind. No pitch, no deck.
By briefing only
This engagement is scoped one to one.
This engagement requires a delivery team assembled against your specific scope. Every engagement starts with a direct conversation, not an open form. Email us and we'll route it to the right lead.