Understand the need
We clarify what the model should do, who will use it and how it should work with existing systems.
Instead of trying to make one general-purpose model fit everyone, we start by understanding your needs, choose a suitable small language model, adapt it to your use case and integrate it into your product.
SLLM is the name we use for our service approach: custom solutions built on small language models.
LLM means large language model; the commonly used abbreviation for a small language model is SLM. SLLM is not an established model category in the literature. We added the extra “S” to emphasize the small scale of the models we develop. By SLLM, we mean small language-model solutions adapted to a particular need—not a separate family of models, but our approach to development.
Not every problem needs a larger model. We define the scope, available data, deployment environment and success criteria together, then choose a model and approach that fit.
We clarify what the model should do, who will use it and how it should work with existing systems.
We select a suitable small model and apply a fitting method, such as supporting it with your data, fine-tuning or another form of adaptation.
We assess the outputs against agreed criteria and, where appropriate, connect the model to your application or workflow.
A model’s performance depends on data quality, task scope and evaluation criteria. The model and deployment environment are chosen to fit each project.
Tell us what you need and where you plan to use it. We can discuss a suitable model, scope and development steps together.