AI Model Training & Fine-Tuning Services
From raw data to a production model that earns its keep. We collect and label datasets, train and fine-tune ML models, fine-tune LLMs on your own knowledge base, and ship the whole pipeline with MLOps you can actually maintain.
- Custom models trained on your data, not a generic API wrapper
- LLM fine-tuning on your docs, 1C records and WhatsApp Business chats
- Full MLOps: versioning, monitoring, retraining and rollback
A-LUX is a Kazakhstan-based AI development agency that trains and fine-tunes machine learning models. We handle the full cycle: data collection and labeling, model training and fine-tuning, LLM fine-tuning on your own data, and MLOps for deployment and monitoring. Projects start from ₸1,200,000. Call +7 705 966-25-25 or message us on WhatsApp.
What we deliver
Four engineering blocks that turn your data into a working, maintainable AI system.
Data collection & labeling
We source, clean and annotate the datasets your model learns from: image bounding boxes, text classification, named entities, audio transcription. Inter-annotator agreement checks and a labeling guide so the quality is measurable, not a guess.
Model training & fine-tuning
Computer vision, tabular forecasting, recommendation, NLP. We pick the right architecture, train from scratch or fine-tune a strong base model, and tune hyperparameters until the metrics clear your business threshold, not just a benchmark.
LLM fine-tuning & RAG
Adapt large language models to your domain with LoRA/QLoRA fine-tuning or retrieval-augmented generation over your own knowledge base. The model speaks your products, prices and tone instead of hallucinating.
MLOps & deployment
We ship the pipeline, not a notebook: containerized serving, an inference API, dataset and model versioning, drift monitoring, scheduled retraining and one-click rollback when a new model underperforms.
Where it pays off
Concrete machine learning use cases we build for businesses in Kazakhstan and abroad.
Support automation
An LLM fine-tuned on your FAQ, order history and WhatsApp Business chats answers customers in Russian, Kazakh and English, escalates the hard cases, and cuts first-response time to seconds.
Demand & inventory forecasting
Models trained on sales pulled from 1C and Kaspi predict demand per SKU and location, so purchasing stops guessing and warehouses stop overstocking.
Computer vision QA
Defect detection on the production line, document and receipt recognition, shelf and planogram analysis in retail. Trained on your own images for accuracy that off-the-shelf APIs can't reach.
Lead scoring & churn
Classification models rank leads and flag customers about to leave, feeding your CRM and sales team a prioritized, daily-refreshed list.
How we work
A transparent path from a vague idea to a measurable model in production.
1. Discovery & success metric
We define the business outcome and translate it into a single ML metric and a target value. If a model can't beat a simple baseline, we tell you before you spend a tenge on GPUs.
2. Data & labeling
Audit your sources, build the dataset, and label it to a written standard. Most ML projects live or die here, so this is where we spend the care.
3. Train, evaluate, iterate
Baseline first, then experiments tracked end to end. You see the metrics each round and approve before we move to production.
4. Deploy & maintain
API, monitoring and retraining go live. We watch for data drift and retrain on a schedule so accuracy doesn't quietly decay.
Why A-LUX
An AI engineering team with 19 years of shipping software that has to work in the real world.
19 years, 400+ projects
A-LUX has delivered web, mobile and AI products since 2007. We've integrated 1C, Kaspi and WhatsApp Business many times over, so your model plugs into systems you already run.
Local + global
Based in Almaty, working with clients across Kazakhstan and internationally. Multilingual NLP in Russian, Kazakh and English is our home turf, not an afterthought.
You own everything
The model weights, the dataset, the training code and the pipeline are yours. No vendor lock-in, no per-prediction toll, no black box you can't move.
Honest about feasibility
We don't sell AI theater. If a rules engine solves it cheaper, we say so. Every project starts with a metric you can hold us to.
FAQ
Answers to common questions before ordering from A-LUX.
What does AI model training cost?
Projects start from ₸1,200,000. The final price depends on data volume and labeling effort, model complexity, whether we train from scratch or fine-tune, and the MLOps scope. After a short discovery call we give a fixed estimate. Call +7 705 966-25-25 or message us on WhatsApp.
What's the difference between training and fine-tuning?
Training builds a model from scratch on your data, best when your task is unique and you have enough examples. Fine-tuning adapts a strong pre-trained model (a vision backbone or an LLM) to your domain with far less data and compute. We recommend whichever hits your accuracy target for the lowest cost and reaches production fastest.
Can you fine-tune an LLM on our company data?
Yes. We fine-tune large language models on your documents, product catalog, 1C records and support history, or set up retrieval-augmented generation (RAG) over the same knowledge base. The result answers questions in your domain and tone in Russian, Kazakh and English, and can be wired into your website, app or WhatsApp Business.
How much labeled data do we need?
It varies by task. Fine-tuning a vision or language model can work with a few hundred to a few thousand quality examples, while training from scratch needs much more. If you have raw, unlabeled data, we handle data collection and labeling as part of the project, with documented quality checks.
What is MLOps and why does it matter?
MLOps is the engineering around a model that keeps it working after launch: dataset and model versioning, an inference API, drift monitoring, scheduled retraining and rollback. Without it, accuracy quietly decays as the world changes. We ship MLOps with every model so it stays reliable, not just impressive on day one.
Do we own the model and the data?
Yes, completely. You receive the model weights, the training dataset, the source code and the deployment pipeline. There's no vendor lock-in and no per-prediction fee. You can host it on your own infrastructure or let us manage it for you.
How long does a project take?
A typical engagement runs from 4 to 8 weeks, depending on data readiness and complexity. A focused LLM fine-tuning or RAG setup can be faster; a from-scratch computer vision model with heavy labeling takes longer. We share a timeline with milestones during discovery.
Do you work with clients outside Kazakhstan?
Yes. A-LUX is based in Almaty and works with clients across Kazakhstan and internationally. We collaborate remotely, deliver in English or Russian, and have experience deploying models to global cloud infrastructure.
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