Services/Custom AI models

Custom models — AI that speaks your language

Generic AI knows a little about everything and nothing about your case. We build lean, specialized models (small language models, SLMs) and fine-tune existing ones with methods like LoRA and QLoRA on your data — creating AI that truly understands your products, your terms and your tone.

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Generic model

I don't have specific details on that. In general there are many screw types — please check the datasheet.

Your model

Item A-220 uses an M6×20 cylinder screw (DIN 912). Matching: nut A-118, washer A-203.

Trained on your data+37% more accurateLoRA · runs under your control

01 The benefit

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More precise results

The model knows your products, terms and cases — instead of generic approximations.

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Lower cost

A lean, specialized model is cheaper to run than a large general-purpose model.

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Data sovereignty

The model runs on your case and under your control — important for sensitive data.

// In plain words

We take an AI model and teach it your knowledge specifically — without rebuilding it from scratch. That's faster, cheaper and more accurate.

02 How it works

Fine-tuning with LoRA — your knowledge as a small add-on

We don't rebuild the model. We freeze the large base model and train only a small adapter — a few percent of extra parameters that carry your knowledge. That's the core of LoRA and QLoRA.

Base model · frozen ❄General knowledgeStays unchanged. No expensive retraining.

Adapter · trainedYour knowledge · ~0.4%Small, quickly trained, swappable.

Your model · runsSpecialized AIUnderstands your products, terms and tone.

training.run — loss curve

Step0 / 240

Loss—

Accuracy—

Click “Start training” — we train only the adapter (LoRA), not the whole model.

03 Services

Feasibility check & data prep

We check whether a custom model is worth it and get your data into trainable shape.

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Fine-tuning (LoRA / QLoRA)

We train an adapter on your data — precise, cost-efficient and traceable.

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Building SLMs

Lean, specialized language models (small language models) for exactly one use case.

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Evaluation & deployment

We measure quality and put the model where it needs to run — including on your own infrastructure.

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04 FAQ

Plainly explained

+What is LoRA fine-tuning?

LoRA (Low-Rank Adaptation) is a method where you don't retrain the whole AI model, only a small additional component — the adapter. The base model stays frozen. This makes training much faster and cheaper, and the result is easy to swap or update.

+How is QLoRA different?

QLoRA is a particularly resource-efficient variant of LoRA. The base model is compressed (quantized), which makes training possible on smaller hardware — at comparable quality. For many companies that means a custom model without needing a data center.

+What is a Small Language Model (SLM)?

A Small Language Model (SLM) is a lean language model with far fewer parameters than a large general-purpose model. Because it's smaller, it's cheaper to run, faster and easier to control — and it can be specialized for your specific use case instead of doing a little of everything.

+Does my data stay with me?

Where it makes sense and is necessary, training and the finished model run under your control — on your infrastructure or in an environment you define. This is especially important when you work with sensitive or confidential data.

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Got a model idea?

Tell us briefly what you're working on. We'll respond with an honest assessment — even when a custom model isn't the right answer.

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