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Models, agents andModeller, ajanlar ve the engineering behind ALTAI.ALTAI’nin arkasındaki mühendislik.
- From 2.2 GB to 2.5 MB: Building the Fastest Turkish Sentence Embeddings with Model2Vec and TurboQuant How we distilled a 24-layer multilingual transformer into a 2.5 MB static embedding model that runs 800x faster.
- OpenSimula examples walkthrough A guided explanation of the OpenSimula pieces used in examples/simula.
- Convert your raw corpus to SFT data: A walkthrough with AfterImage to generate legal research conversations A guided explanation of the AfterImage pieces used in examples/caselaw_rag/generate.py.
- AfterImage is now open source for infrastructure-level dataset generation A Python library and CLI for synthetic conversational datasets — grounded, diverse, and observable. Today we are releasing AfterImage as open source.
- Building a Small yet Highly Capable LLM-as-a-Judge: Fine-Tuning Gemma 3 4B for Evaluation Tasks Open-source language models have made incredible progress in reasoning and instruction following — yet they still struggle with one crucial skill: evaluation.
- Fine-Tuning Is Not Dead: How Synthetic QA Fine-Tuning Makes RAG Smarter At Altai, we are frequently asked one question — why bother fine-tuning when you can just use RAG? Here is the answer.
- Small Models, Big Impact: Why Altai's SLMs Outperform LLMs for Business Needs Businesses are eager to harness AI — but the biggest, most expensive models aren't always the right answer. Here's why smaller, domain-specific models win.
- Launching Altai: Unlocking Enterprise AI with Customization & Open Source Enterprises are eager to leverage LLMs but adoption is hard. Here's why we built Altai — and what we're doing differently.
- Distilling Efficiency: Experiments in Compressing BAAI/bge-m3 using a Synthetic Dataset The rapid progress in NLP is mainly due to large neural network models — but size comes at a cost. Here's our approach to compressing bge-m3 with synthetic data.
- Are you tired of getting only garbage instead of Markdown from PDFs? Yeah, same. That's why we built llm-food — a FastAPI-based service that converts documents and URLs into clean, LLM-friendly Markdown with batch processing support.
- Introducing AfterImage: Custom Vision Models Without the ML Overhead Training a custom image classifier used to mean weeks of setup. AfterImage changes that — bring your data, get your model.
- Why Most Enterprise AI Projects Fail (And How to Fix It) According to Gartner, over 85% of AI projects never make it to production. After talking to hundreds of enterprise teams, the reasons are almost always the same.