Render Analytics service
Custom Language Models / SLMs
Language models trained on your data, for your use case.
General-purpose LLMs are powerful but not always optimal for specialized domains. We fine-tune and deploy small language models (SLMs) and domain-specific models on your proprietary data to deliver higher accuracy, lower cost, and better privacy.
What Render Analytics implements
- Fine-tuning of open-source LLMs (Llama, Mistral, Phi)
- Domain-specific training data curation
- RAG (Retrieval-Augmented Generation) architectures
- Private deployment on your infrastructure
- Model evaluation and benchmark testing
- Ongoing model maintenance and retraining
Related services
- AI & Automation: As an AI implementation team, we help organizations move from readiness assessments to deployed agentic systems that automate workflows, generate insights, and build competitive advantages.
Service FAQs
What is a small language model (SLM)?
SLMs are compact AI models (typically 1B–13B parameters) that can be fine-tuned on specific domains and run on modest hardware. They offer better privacy, lower cost, and higher accuracy for specialized tasks than large general models.
Do I need to own my own servers to run a custom model?
No. We can deploy models on cloud infrastructure (AWS, Azure, GCP) or on-premises depending on your privacy and compliance requirements.
What is RAG and when should I use it?
Retrieval-Augmented Generation connects a language model to your knowledge base so it can answer questions based on your specific documents, policies, and data — without requiring full model retraining.