RLHF Services.

When your model knows the subject but its answers are not the ones your experts would approve, reinforcement learning from human feedback teaches it their judgment.

Crunch-IS runs RLHF services from start to finish: your experts rate the answers, we train the model on their preferences, measure it on your cases before and after, and leave it in your infrastructure.

Plan My RLHF Project

Benefits of Our RLHF Services

Answers Your Experts Would Approve

The model learns what your best reviewers prefer (not what a generic rater thinks sounds right).

Fewer Answers Outside Your Rules

Answers that break your policies, tone, or safety rules are rated down, so the model learns to avoid them.

Less Review After Launch

When the model already answers the way your experts would, fewer answers need a person to check or rewrite them.

More From Your Experts' Time

Your experts rate a smaller set of answers, and an AI judge checked against them covers the rest, so improving the model does not take over their week.

RLHF Process

Here is what happens after you send the form.

01

You Send the Form

Tell us what your model does, where its answers fall short, and who on your team knows what a good answer looks like.
02

We Check Whether RLHF Fits

We test your model on real cases and recommend prompts, fine-tuning, or preference training, with a written scope and price.
03

We Write the Guidelines With Your Experts

Your experts and our engineers agree on what makes one answer better than another, with examples.
04

Your Experts Rate the Answers

We set up the comparisons in Argilla and check that reviewers agree before the data is used.
05

We Train the Model

We train with DPO, or with a reward model and PPO, and track every run.
06

We Measure and Hand Over

We compare the model before and after on the same tests, deploy it in your infrastructure, and hand over the data, code, and documentation.

RLHF Services We Offer

01 RLHF Readiness Check

RLHF is the most expensive way to change how a model behaves, and many problems do not need it. We test your model on real cases and tell you whether better prompts, supervised fine-tuning, or preference training will fix what is wrong. If RLHF is the answer, the check sets the goal, who rates the answers, and the price.

02 Preference Data From Your Experts

The model learns whatever the ratings teach it, so the people rating matter most. We write the rating guidelines with your domain experts, set up side-by-side comparisons of answers, and check that different reviewers agree before the data is used. The RLHF data stays yours for every later training run.

03 Reward Model Training

A reward model learns your experts’ preferences so it can score new answers without a person. We train one when the project uses PPO or needs an automatic scorer for new answers, and check whether its scores match your reviewers on cases it has not seen before relying on it.

04 DPO and PPO Training

We train the model on the preferences with the method that fits. DPO training works directly on pairs of better and worse answers. PPO uses the reward model and lets the model keep learning from new answers. We start with DPO when it is enough, because it is simpler and cheaper to run.

05 AI Feedback at Scale

Expert time is limited. Once an AI judge agrees with your experts on a test set, it can rate many more answers, and your experts review only the cases where it is unsure. This approach, known as RLAIF, keeps people in charge of what counts as a good answer.

06 Before-and-After Evaluation

We run the same test set on the model before and after training, so you can see what improved and catch anything it got worse at. The tests come from your real cases and stay in your repository for the next training run.

Our RLHF Capabilities

Human Feedback in Argilla

We run rating and expert review in Argilla, so every rating has a reviewer and a source, as on an EdTech publishing platform.

Open Models and Provider APIs

We train open models such as Llama and Mistral on infrastructure you control, and use providers’ preference-tuning APIs where they offer them.

Training Libraries

We run reward model, DPO, and PPO training with open-source libraries such as Hugging Face TRL.

Experiment Tracking

We track training runs, prompts, and outputs in LangSmith, so each model version can be traced to the ratings and settings behind it.

Deployment and Monitoring

We deploy the trained model with versioning and rollback, then watch its answers in production through our LLMOps practice.

What You Get

Preference Data You Own

The ratings, guidelines, and reviewer notes are yours, documented so your team can add to them and train again.

Rating Guidelines in Writing

Your experts’ criteria for a good answer are written down with examples, so new reviewers rate the same way.

A Model That Stays Yours

Weights, training code, and settings stay in your infrastructure, with no license or dependency on us.

Before-and-After Results

You see the model’s results on your own cases before and after training, so the decision to ship rests on evidence.

Why Choose Crunch-IS as Your Partner

Your Experts, Not a Crowd

Data vendors sell their own raters. We build the process around the people who already know what a good answer is in your business, and make their time count.

We Train the Model, Not Just Label

As an RLHF company that also builds and runs AI systems, we take the work past the ratings file: reward model, training, evaluation, and deployment.

We Tell You When You Don’t Need It

If better prompts or supervised fine-tuning fix the problem, we say so before any ratings are collected.

What Our Clients Say About Us

They come up with lots of scalable and best-practice ideas that enable us to achieve what we have right now.

Nicky, Softcat | Video testimonial Crunch-IS

Nicky Senior Business Analyst at Softcat

Crunch-IS was great at leading us on what good should look like and bringing our ideas to life for evaluation and review.

Matthew, Softcat | Video testimonial Crunch-IS

Matthew Head of Digital Strategy at Softcat

Crunch-IS impressed me with is the quality of developers. It is simply much better than in any other company we’ve tried working with.

Klaus, YouWe | Video testimonial Crunch-IS

Klaus CEO at YouWe

We are impressed with their performance, how they are engaged with product development, and how they care about the product.

Sebastian Jara, Accountflow | Video testimonial Crunch-IS

Sebastian Co-Founder & CTO at Accountflow

It’s been a very enjoyable experience. All has been fantastic about communicating, and working.

Marta, GIA Networks | Video testimonial Crunch-IS

Marta Consultant at GIA Networks

Our partnership with Crunch-IS has been an invaluable resource as we’ve scaled.

Ryan, WorkDove | Video testimonial Crunch-IS

Ryan CTO at WorkDove

What I found in Crunch-IS was the technical competency, ability to think outside the box, and very good English.

Garrett, Tabulate | Video testimonial Crunch-IS

Garrett COO at Tabulate

They have a large impact on the whole architecture we ended up with. Overall, I’ve been pleased and impressed with everything Crunch-IS did for us.

Kenneth, Zuar | Video testimonial Crunch-IS

Kenneth CTO at Zuar

Crunch-IS impressed us with their technical excellence and the sheer ‘meeting of minds and cultures’ and open, honest exchanges. This was not a decision we took lightly, and 5 months into the engagement we continue to be really impressed with how Crunch-IS approach the collaboration, and we’re delighted with the calibre of the team we have working with us.

Gary Managing Director at a UK Software Development company

Working with Crunch-IS was easy. They were patient with us as we worked through the contract questions and patient again as we were getting our billing set up. The design work was elegant and the developer delivered the app we had contracted for on time and good quality.

Scott VP of Software Engineering at Analytic Index

The team at Crunch-IS was very nice to work with. They worked diligently and were very professional. When questions or technical problems arose, they answered them quickly and were always ready and kind about helping us.

Miia Business Management at Conmark Systems

Crunch-IS developer helped us deliver an important feature for our project much faster than expected.

Rosario VP of Engineering at Profitap

Crunch-IS facilitated a seamless, collaborative effort throughout the project. The team maintained open lines of communication, kept detailed records of task assignments, and adhered to project timelines. Their expertise regarding both design and development sets the company apart.

Sisun CEO at Chintech

Crunch-IS provides ongoing development support that meets project requirements as needed. Despite their offshore location, they are easy to work with and accessible through communication channels

Bob CTO at Timegen

The best vendor we could possibly find. Crunch-IS blends practical development with innovative design principals. Internal and external feedback to app development has been positive. They complete project milestones by the planned schedule and deliver within budget. The team’s responsive and willing to engage in productive dialogue.

Jeff CEO at USA Software Company

Crunch-IS exceeded my expectations. I appreciated the developers’ resourcefulness in the face of constraints and complex requirements. The company able to deliver and complete the project successfully.

Kate Product manager at Mezonin

The project has gone smoothly so far. Crunch-IS has an exceptional work ethic. Consequentially, they’ve been able to tackle every challenge that comes their way. They manage day-to-day work on their own well but also communicate with us regularly to make sure we’re on the same page.

Andrew CMO at Qinetics

The app Crunch-IS worked on is clean, streamlined, and functions as intended. Crunch-IS goes above and beyond to ensure that both teams are in tune. The passionate team crafts an enjoyable experience through their positive demeanor and effective project management skills. The team was very friendly, and working with them was a pleasure.

Ian CEO at Biomicc

01 / 07

Start New project

RLHF Services FAQ

What are RLHF services?

RLHF services take a model from human ratings to a trained, tested model. They cover writing rating guidelines, collecting human preference data, training a reward model, preference training with DPO or PPO, and measuring the result. Some providers sell only the ratings; we do the whole chain, with your experts doing the rating.

What is RLHF, and how does it work?

RLHF, or reinforcement learning from human feedback, teaches a language model judgment. People compare pairs of the model’s answers and pick the better one. Those choices train a reward model that scores answers, and RLHF training then teaches the language model to give answers that score well.

What is the difference between RLHF and DPO?

Both learn from the same pairs of better and worse answers. Classic RLHF first trains a reward model and then updates the language model with reinforcement learning, usually PPO. DPO skips the reward model and trains on the pairs directly, which makes it simpler and cheaper. We start with DPO and move to PPO when the model needs to keep learning from new answers.

How is RLHF different from fine-tuning?

RLHF is a form of fine-tuning. Supervised fine-tuning teaches the model from examples of correct answers; RLHF teaches it from people’s preferences between answers, which suits tasks where quality is a judgment call. RLHF usually follows supervised fine-tuning, which our LLM fine-tuning services cover.

Who gives the feedback, and can we use our own experts?

Your own domain experts give the feedback, and we recommend it, because they know what a good answer is in your field. We write the guidelines with them, set up the rating so it takes as little of their time as possible, and extend their ratings with an AI judge checked against them.

How much preference data do we need?

It depends on the task and on how far the model is from what you want. We measure that gap during the readiness check and tell you how many ratings the project is likely to need before any are collected.

How is the price set?

We price each project after the readiness check, because the work depends on the task, the model, and how many ratings are needed. You receive a written scope and the price before work starts.

Your RLHF project starts here.

Talk through your model and the answers your experts would change on a free call.

Book My Free Call

Crunch-IS Success Stories

VIEW ALL

LLM Fine-tuning for Content Management and Creation in EdTech

3×: improvement in prompt accuracy
40-50%: faster time to content publication

Knowledge Access Transformation with RAG and AWS

60%: faster work with company documents

AI-Enhanced Compliance LMS Platform for Construction & Safety Training

Stay Up-to-Date with the Latest Trends