01 / CHOOSE A PROBLEM
Try a use case
Route support tickets, choose the next action and identify requests for a quote. Demos without an account, with results and code.
Open the use case book →FABRYKA AI RESEARCH
INDEPENDENT ARTIFICIAL INTELLIGENCE RESEARCH LABORATORY · WARSAW, POLAND
We build models. Then put them to work.
We study how language models learn, how to make them more efficient, and how to evaluate them reliably — with a particular focus on Polish-language AI.
Find a use case →Explore Polish models →
NEW MODEL / REMIGIUSZ KINAS / BASAL OMNI 1.0 MAX
Text. Images. Audio.
One concrete decision.
Basal Omni is a new 12B decision model built on Gemma 4. Explore applications, author-reported results, experimental media support and integration documentation.
Open weights · PL + EN · Experimental release · Omni hosting in preparation
FABRYKA AI USE CASE BOOK
A Polish model.
Your specific problem.
Try working examples, explore API code and transparent measurements. Meet Basal, Muszka and Poziomka — each with clear authorship and actual availability.
02 / MEET THE MODELS
Polish models and creators
A catalog of model families. Authors, sources, limitations and statuses: available, experimental and listed in the catalog.
Browse the catalog →03 / ADD YOUR PROJECT
Using a model? Show us how.
Share an example, pilot or deployment. Describe the problem and the result — we will prepare a use case together.
Fabryka AI is an independent service and is not organizationally affiliated with the creators of the featured models or with Hugging Face. Model names, brands and trademarks belong to their respective owners. Catalog inclusion does not imply sponsorship or endorsement of Fabryka by the authors. Model weights come from the authors’ Hugging Face repositories; hosting follows the license of the specific version. Each model card provides its source and license. A model license does not grant trademark rights. Model sources and licenses →
FROM QUESTION TO PUBLIC ARTIFACT
Research → Experiments → Evidence → Applications
01 / RESEARCH PROGRAMMES
Three lines.
One research agenda.
How much quality can we achieve with a given budget of data, training and inference — and how can we measure it reliably? These three programmes connect our current work and planned studies.
01 / RESEARCH PROGRAMME
Small Language Models
Training Polish language models from scratch. We study scaling laws, tokenizers, data mixtures and distillation to understand how much capability a compact model can learn.
Explore programme →, Small Language Models02 / RESEARCH PROGRAMME
Efficient Inference
Making language models practical on commodity GPUs. We study quantization, speculative decoding, including DFlash, routing and the trade-offs between throughput, latency and quality.
Explore programme →, Efficient Inference03 / RESEARCH PROGRAMME
Polish AI Evaluation & Data
Building the data and measurements that Polish AI needs. This programme connects Polish DynaWord, CodeSOTA benchmarks, OCR evaluation and methodologies for comparing Polish LLMs.
Explore programme →, Polish AI Evaluation & Data02 / SELECTED RESEARCH OUTPUTS
Work you can inspect.
Explore public model weights, data and benchmark evidence. Each linked artifact carries its own documentation and scope.
MODEL
Pollock Mini LM · 125M
A compact language-model release. Model card, weights and usage information are available in the public repository.
DATASET
Polish DynaWord
A public Polish-language dataset supporting our work on language-model training and data composition.
BENCHMARK INFRASTRUCTURE
CodeSOTA
Model comparisons and benchmark evidence. Individual entries identify their sources and evaluation context.
03 / OPEN RESEARCH
Follow the work.
Inspect the evidence.
Our research connects questions, baselines, experiments and artifacts. We use Fabryka Track to record training runs, compare configurations and investigate results.
Dated experiment write-ups are preserved in our research notes. Track provides the tools for recording experiments; access to individual runs depends on the project.
04 / RESEARCH INFRASTRUCTURE
Tools for doing
the research.
Training, measurement and serving are part of the same experimental workflow. We build the infrastructure that helps us investigate each step.
MEASURE
CodeSOTA
Public infrastructure for model comparisons, benchmark results and evaluation evidence.
Explore CodeSOTA ↗RECORD
Fabryka Track
Experiment tracking for training runs, metrics, logs, checkpoints and configuration comparisons.
Explore Track ↗EXPERIMENT
Compute laboratory
GPU systems for training and inference experiments, with hardware and workload conditions documented alongside results.
Inference research →05 / PEOPLE
A lab is the people
doing the work.
Meet the Fabryka AI team: researchers, engineers and contributors working across models, data, evaluation, agents and infrastructure.
- 15
- team members & contributors
- 2
- advisers
FOUNDER / RESEARCH
Kacper Wikieł
Language models, training infrastructure, model optimization and evaluation.
CO-FOUNDER / RESEARCH & ENGINEERING
Arkadiusz Słota
Datasets, evaluations, training infrastructure and systems engineering.
AI AGENTS / LLM INFRASTRUCTURE
Piotr Zientara
Founder of Xfaang. Builds autonomous AI agents and LLM products, connecting data, evaluation and infrastructure.
AI AGENTS / RECRUITMENT
Piotr Styła
Agent teams, web and mobile applications, recruitment and onboarding.
AI ENGINEERING / FULLSTACK
Kuba
Theoretical physics, computer vision for oncology, and generative and agent systems.
FULLSTACK / MICROSERVICES
Kamil Kaczmarek
Bots, microservices and production tools, from idea to deployment.
AGENT WORKFLOWS / ML STRATEGY
Konrad Talik
Long-running agent workflows and ML strategies informed by data exploration and visualization.
DATA / SYSTEMS ENGINEERING
Piotr Rybarczyk
Data pipelines, systems engineering and technical planning.
EVALUATION / TOKENIZERS
Maciej Sawicki
Evaluation tooling, reproducible experiments and Polish byte-level BPE tokenizers.
RESEARCH TOOLING / COMMUNICATION
Radomir Mastalerz
Research tooling, experiment documentation and presentations.
TRAINING INFRASTRUCTURE / PRODUCT
Dawid Majewski
Training infrastructure, developer tools and the Fabryka Track interface.
MODEL TRAINING / EVALUATION
Adam Skrodzki
Small-model training experiments, model-based evaluation and benchmark methodology.
PRODUCT / SOFTWARE ENGINEERING
Łukasz Czerwiński
Software engineering and contributions to the Fabryka Track interface.
TOKENIZERS / TECHNICAL REVIEW
Paweł Puzio
Polish tokenizers, technical reviews and research planning.
RESEARCH REVIEW / PLANNING
@bartoszkobylinski
Contributions to research discussions, planning and review.
RESEARCH & PRACTICE
Our advisers
Supporting the team with research methodology, evaluation and domain expertise.
ADVISER / ML RESEARCH
dr Juliusz Straszyński
Research expertise in machine learning and language models.
ADVISER / AI & BUSINESS PROCESSES
dr hab. inż. Piotr Senkus
Expertise in management, business processes and applied AI.
06 / TECHNOLOGY TRANSFER
Research,
put to work.
Selected technologies developed or evaluated at Fabryka become production systems. Our inference platform makes open models available through an API, with tools for chat, routing and token-level analysis.
The platform also serves models developed by other teams. Availability through our API is separate from authorship of a model.
07 / ABOUT FABRYKA AI
Independent research.
Built in Poland.
Fabryka AI is an independent artificial intelligence research laboratory in Warsaw. We build datasets, train models from scratch and develop methods for efficient inference and reliable evaluation.