Data preparation, model training and evaluation, data engineering and ML services for the job.

Data, models and ML services

This direction owns the foundation of AI systems: data that makes a model predictable and models whose quality is measured before launch.

Data and models

Data for AI: collection, labeling, quality

Pipelines, warehouses, labeling and synthetic data: data that makes a model predictable.

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Data engineering

We build ingestion, storage, and marts so reports reconcile and quality checks run before publication.

Data labeling

We prepare labeled text, images, audio, and video against agreed rules with two review passes.

Synthetic data

The generator adds rare cases, and the model is checked on real data.

Data audit for AI

We collect the sources into a register, grade quality, map PII and access, and hand over a scorecard and roadmap.

Chat with data

An analyst asks a question in plain words and gets SQL, a chart, and a short answer from your warehouse.

Data and models

Model fine-tuning and evaluation

Fine-tuning, quality evaluation, red teaming and model observability.

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LLM fine-tuning

We tune a 7B–70B model with LoRA, SFT, or DPO and show quality on a held-out set before launch.

LLM quality evaluation

We measure accuracy, faithfulness to sources, and model resilience on your tasks.

Data and models

ML services: vision, forecasts, language

Computer vision, predictive analytics, NLP, recommendations and MLOps platforms.

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Computer vision systems

Cameras find the defect before an operator, and borderline cases go to a person.

Predictive analytics systems

The model forecasts demand, churn, and equipment failure ahead of time.

Anomaly detection systems

The system catches atypical behavior in a stream, including failures outside the known list.

MLOps platform development

Training, versions, and model rollout are described as code and reproduce with one command.

Natural language processing systems

We extract meaning from text: sentiment, entities, classification, and summarization.

Recommendation systems

We match each user with items and content from their own behavior.

Speech recognition systems

Speech to text for your domain: terms, names, and multiple speakers.

Reinforcement learning systems

The agent learns in a simulator and optimizes a long-horizon goal.

AI forecasting

We build demand, sales, and load forecasts on your history and validate them on a backtest.

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