We want the model to know our company documents. Is fine-tuning the answer?

Almost certainly not. Fine-tuning teaches style and format far better than it teaches facts, and a tuned model cannot be updated when a document changes. Retrieval over your documents is cheaper, more accurate, and updates instantly. That is what we would build.

How much data do we need?

A few hundred high-quality, consistent examples is a realistic floor for a narrow task, and a few thousand is more comfortable. Quality matters more than volume. A thousand inconsistent examples will teach the model to be inconsistent.

What does it cost to run afterwards?

Depends on the provider and model size. A tuned smaller model is often cheaper per call than prompting a large one, which is sometimes the whole reason to do it. Hosting an open-weight model yourself trades per-call cost for infrastructure you now maintain, and we will lay out both before you decide.

How often will it need retraining?

Whenever the underlying task changes: new categories, a changed format, a shift in the language your customers use. There is no schedule. We agree the triggers up front and monitor for them, because a silently stale model is the common failure mode.

What if the fine-tuned model isn't better?

That is a real possible outcome and we build the evaluation so you find out early, not after deployment. If the tuned model does not beat the baseline, we report it, ship the baseline, and you have spent an assessment rather than a full build.

LLM Fine-Tuning

Start with the honest part: fine-tuning is usually not the right first move. If you want the model to know your documents, retrieval over those documents is cheaper, faster to build, and updates the moment you edit a file. A tuned model has to be retrained. Most teams who arrive asking for fine-tuning actually need better prompting or a retrieval setup, and we will say so. When fine-tuning genuinely is the right call, it is for a narrow set of reasons, and this page is about those.

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An engineer evaluating model outputs against a labelled dataset.

Trusted by + clients worldwide.

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Our LLM Fine-Tuning Services

Fit Assessment First

Before any training, we test whether prompting or retrieval already gets you there. A week spent here often saves the entire project budget.

Dataset Building & Review

The dataset is the work. We help you assemble, clean, and label examples, and hold back a proper evaluation set you never train on.

Training & Evaluation

We run the tuning, then score the result against the base model on your held-out set. If it does not beat the baseline, we say so and stop.

Deployment & Retraining Plan

We wire the model into your app and write down what triggers a retrain, because a tuned model quietly drifts out of date as your work changes.

Our Process

How We Approach a Fine-Tuning Request

Typical Timeline: 1-2 weeks for the fit assessment, 4-8 weeks more if fine-tuning turns out to be the right call

01

Try the Cheap Things

We build a prompting and retrieval baseline first and measure it. Plenty of engagements end here, with a working feature and no training bill.

02

Check the Data

Fine-tuning needs a few hundred to a few thousand consistent, correct examples. If you do not have them, that is the real project, and we will scope that instead.

03

Train and Compare

We tune, then score the result against the baseline on examples the model never saw. The comparison is the deliverable, not the model file.

04

Deploy With a Retrain Trigger

The model goes into your app with monitoring, and we agree in writing what change in your process means it is time to retrain.

When Fine-Tuning Actually Earns Its Cost

Three cases hold up in practice. First, output that must follow a consistent format, tone, or classification at volume, where prompting gets you to roughly right and you need reliably right across thousands of runs. Second, a narrow domain vocabulary the base model handles badly, specialised terms, internal codes, an industry shorthand. Third, cost and latency at scale, where a smaller tuned model matches a large one on your specific task for a fraction of the per-call cost. Notice what is not on that list: teaching the model facts about your company. That is a retrieval problem, and fine-tuning does it badly. If your case is one of the three, we will build it. If it is not, we will point you at the cheaper answer and you can keep the budget.

Technologies We Work With

Why Choose Boldally for LLM Fine-Tuning

We Talk Most Clients Out of It

If retrieval or a better prompt does the job, we will tell you before you spend on training. That advice costs you a short call.

Measured Against a Baseline

A tuned model that does not beat the base model on your own held-out examples is a failed experiment, and we will report it as one.

The Data Pipeline Is the Real Build

Collecting, cleaning, and labelling examples is ordinary data engineering, and it is the work we have been doing on client systems since 2019.

No Case Studies We Don't Have

We have not publicly shipped a fine-tuned model. We will scope a first engagement small enough that you are not relying on a track record we cannot show.

FAQ

Frequently Asked Questions

Common questions about this service. If yours isn't here, just ask.

Selected case studies

Attar Shastra
A Shopify Hydrogen storefront for a natural attar brand, built to sell to customers in India and abroad.
Chroma Tech Services
An internal employee portal that gives an industrial analytics firm one place to share documents.
Emerhub CRM
A custom CRM on Firebase and Vue.js that speeds up client onboarding with real-time form editing.

View all case studies

What Our Clients Say

We work closely with the teams we build for, and we stick around after launch. Here's what some of them have to say.

Gagandeep is a phenomenally talented senior developer who was a vital part of our success! Diligent, goal oriented and an innovative leader, I couldn't speak highly enough of Gagandeep

James Charles

Founder, The Air App

Gagan worked with Emerhub and Companies House for over a year, demonstrating great flexibility in adapting to different tech stacks and evolving business requirements.

Lauri Lahi

Co-founder and chairman, Emerhub

I got to witness first hand the great skills of Gagandeep while working alongside him on a project. First-class in everything and extremely talented in his craft. It was a tough project that no companies had ever built before and he tackled it and then some!

Andrew Petcash

Advisor, The Air App

Boldally Studio delivered exceptional results on our MSP Global website. The design is visually impressive, and the site's performance is outstanding. We're extremely pleased with their work and highly recommend their services.

Sonam Parashar

Director, Msp Global

Well done to the Boldally Studio team for their dedication and efficient work process. They consistently delivered projects on time and followed the direction I provided with precision, which I found truly impressive.

Manoj Kumar

Founder, Bhaagyashaali Welfare Foundation

Boldally Studio provided us with continuous support and helped us at every step, providing valuable feedback and understanding our needs effectively. We are satisfied with the overall outcome and process. Highly recommend Boldally Studio if you're looking for excellent output.

Supriya Vij

Founder & CEO, VTeach

Gagandeep and his team did a commendable job on our Laravel development project. It was a pleasure working with him, and the team demonstrated solid technical skills throughout the process.

Abraham Scaria

Director, Asna Software Solution

It's just how I imagined it. I really love the website—it looks great and works well. The custom software is very helpful and easy to use. It makes our daily work much easier.

Anil Kumar

Director, Chroma Tech Services

Big thanks to Boldally Solutions Private Limited for designing our website. The team was dedicated, supportive, and truly understood our needs. We're very happy with the results and highly recommend them for quality work.

Karishma Vij

Head of PR, VTeach

We are very happy with the website made by Boldally Studio. It looks great, is easy to use, and shows all our services clearly. The team was helpful, understood our needs, and delivered everything on time. We highly recommend Boldally Studio to anyone looking for a good and professional website.

Gurvinder Singh

Owner, Upkar Group

Have a project in mind?

Tell us what you're trying to build or fix. We'll talk through scope, timeline, and the right approach for your team.

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LLM Fine-Tuning

Trusted by + clients worldwide.

Aladdin Media

Asna Software Solution

Attar Shastra

Bhagyashaali Welfare Foundation

Chroma Tech Services

City Line Collection

Companies House

Dietitian Miksha

Emerhub

Gaadi Buy

Galecia Group

Globus Machines Pvt Ltd

Hasten

Heavenly Home

Lazy Baby

OnKampus

MSP Global

My Dream Home Care

Niya Overseas

Organish Herbal

SEO Scout

Tex Trend

The Insurance Problem

The Air App

TriStates

Upkar Group

V-Teach

VK Car Loan

VSKA

Vyzion Innovations

WatsupUSA