AI Model Training
Train and fine-tune deep-learning models and large language models on our in-house GPUs, with training data collected and prepared at big-data scale.
AI models trained on the right data
From raw data to a trained AI model
Set algorithms that work across large sets of data to train your AI models, then inspect and fine-tune their performance.
We cover the whole journey in-house: BigParser, our data collection platform, gathers and structures the data; our big-data platform cleans and prepares it; and our own GPU infrastructure trains and fine-tunes deep-learning models and LLMs for your use case.
What we deliver
One pipeline, from data collection to a model you can deploy.
Data Collection with BigParser
Our in-house BigParser platform collects web content and documents and turns them into structured data sets, alongside your own data.
Training Data Sets
Labelled data sets, from classification examples to question-and-answer pairs, ready for supervised training and fine-tuning.
In-house GPU Training
Train deep-learning models on our own GPU infrastructure, not a shared public cloud.
LLM Fine-Tuning
Adapt large language models to your domain, your terminology and your languages.
Evaluation & Benchmarking
Measure accuracy and output quality on held-out test sets before any model goes live.
Deployment & Retraining
Deliver versioned models into your application and retrain them as new data arrives.
Machine learning in production since 2017
In 2017 a mobile operator asked us to screen the content of 120 million SMS a day, in real time, for fraud and phishing, in a language our team did not speak.
Machine learning made it possible, and we have been building ML and AI systems ever since. Today the same expertise powers WayMore, our AI-powered operating system for companies, and chat.waymore.ai, the AI platform behind it.
From big data to in-house GPUs
BigParser collects the data, Apache Spark on the Hadoop ecosystem cleans and prepares it at scale, and our in-house GPUs train and fine-tune the models, with Apache Airflow orchestrating every step.
How we work
A repeatable cycle that keeps your AI models accurate over time.
1. Collect & Prepare
Gather data with BigParser and from your own sources, then clean, label and split it for training.
2. Train & Fine-tune
Train or fine-tune models on our in-house GPUs and tune them against the metrics that matter to you.
3. Evaluate & Deploy
Benchmark the model, deliver it into your application, and retrain it as new data arrives.
Explore our Data & AI services
Each service stands on its own, and together they take you from raw data to AI in production.
AI Model Development
Build AI-powered applications, from LLM-based assistants to automated workflows, grounded in your data.
Model Training
Train, inspect and fine-tune machine-learning models on your full data sets.
Data Cleansing
Eliminate errors and inconsistencies with automated cleansing pipelines that keep your data reliable.