LLM Fine-Tuning

LLM fine-tuning services & human feedback that align your models.

LLM fine-tuning services done right: RLHF, SFT, prompt engineering and expert evaluation — with STEM and domain specialists on the hard prompts, so your model learns what good actually looks like. We supply the human feedback that turns a capable base model into a reliable, fine-tuned product.

Book a pilot All services

Why fine-tuning

Turn a capable base model into a reliable product

Base models are broadly capable but rarely production-ready. LLM fine-tuning aligns them to your task, tone and safety bar using human data — RLHF preference rankings, SFT demonstrations and targeted evaluation. Graveiens brings a STEM and domain SME bench to the fine-tuning work most data vendors cannot staff, and pairs it with LLM evaluation and data annotation services so every iteration is measured, not guessed.

Scope a fine-tuning pilot

What we do

LLM fine-tuning services: from preference data to fine-tuned models

We supply the human judgment that turns a capable base model into a reliable product — ranking, demonstrating, prompting and stress-testing across domains and languages.

RLHF & Preference Data

Pairwise & ranked comparisons
Reward-model training data
Helpfulness, harmlessness, honesty
Multi-turn dialogue rating

Supervised Fine-Tuning (SFT)

High-quality demonstrations
Instruction-response pairs
Domain & task-specific data
Style and format control

Prompt Engineering

Prompt design & optimization
Chain-of-thought curation
Template & system-prompt libraries
Few-shot example sets

Red-teaming & Safety

Adversarial prompt discovery
Jailbreak & misuse testing
Toxicity & bias probing
Policy-aligned labeling

STEM & Domain Trainers

Math, science & code review
Medical, legal & finance SMEs
Curriculum-grade validation
Reasoning-quality grading

Fine-Tuning & Optimization

Dataset curation & cleaning
Pipeline & tooling support
Python, TensorFlow, PyTorch
Evaluation-driven iteration

See evaluation

How it looks

Preference feedback in practice

RLHF

Rank, compare, improve

Trained raters and domain experts compare and rank model responses against your rubric, producing the preference data your reward model needs — with quality controls to keep labels consistent throughout the LLM fine-tuning loop.

Talk to us

Why Graveiens

Why teams choose Graveiens for LLM fine-tuning

Compliance-first delivery and a pay-on-approval model that de-risks every engagement.

Real subject-matter depth

A STEM SME bench inherited from our education business — rare for a data vendor.

Multilingual feedback

RLHF and SFT data across 25+ languages, not just English.

Consistent quality

Rubric-based grading with calibration and four-stage QA.

Pay on approval

Invoiced only for approved deliverables.

FAQ

Questions, answered

What does LLM fine-tuning with Graveiens involve?

We provide the human data for LLM fine-tuning end to end: RLHF preference and reward data, SFT demonstrations, prompt engineering, red-teaming and expert evaluation, across domains and 25+ languages.

Do you provide RLHF and SFT data?

Yes — pairwise and ranked preference data for reward modeling, plus high-quality demonstrations for supervised fine-tuning, across domains and languages.

Can your experts handle STEM and specialist prompts?

Yes. Our SME bench includes math, science, code, medical, legal and finance specialists for prompts that need genuine domain judgment.

Do you support red-teaming and safety work?

Yes — adversarial prompt discovery, jailbreak and misuse testing, and policy-aligned safety labeling.

How do we pilot this?

Start with a small rated batch against your rubric; you approve the output before we scale.