cynkra


Intelligently R

From natural language interfaces to automated analysis pipelines, we make AI accessible and practical within the R ecosystem.

Our Offer

Supercharge R with AI

RAG and Agentic Tools


We build Retrieval-Augmented Generation (RAG) systems and agentic workflows that work with your R data pipelines. From document analysis to automated decision-making agents using your R infrastructure.

No-Code AI Workflows


Our blockr.ai framework lets you analyze data using natural language instead of code. Create plots, transform data, and build workflows by describing what you want in plain English.

Local LLMs


We set up local Large Language Models (LLMs) that keep your data on your own servers. Your data stays private, models learn your specific needs, and you avoid ongoing cloud costs.

Open Source


We build and contribute to open source AI tools for R: vector databases like rchroma, natural language interfaces like the ask package, and other tools that make AI work with R.

Custom AI Integration

We specialize in privacy-aware AI solutions using local Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. Our solutions keep your data private while providing customized models that understand your domain-specific requirements.

Contact us
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Featured Projects


A high-performance vector database implementation for R, enabling efficient similarity search and retrieval for AI applications.

Key Features

  • High-performance vector similarity search
  • Efficient indexing for large datasets
  • Integration with R AI workflows
  • Support for multiple distance metrics
open source project

Our ask package lets you interact with AI models directly from R, going beyond simple text responses.

Key Features

  • Script and documentation editing in place
  • Code and test generation
  • Package documentation querying
  • Natural language data processing
  • Support for both cloud (GPT-4) and local (LLama) models
open source project

blockr.ai extends our blockr framework with AI capabilities for natural language-driven data analysis.

Key Features

  • AI-powered plot creation through natural language
  • Intelligent data transformations
  • Integration with leading AI models
  • Composable blocks for flexible workflows
  • Seamless integration with the blockr ecosystem
open source project

Local AI Solutions


  • Complete Data Privacy

    Keep your sensitive information within your infrastructure using local Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.

  • Customized Models

    We set up and fine-tune local LLMs (Llama, Mistral) that understand your domain-specific terminology and requirements.

  • Performance & Cost Efficiency

    Lower latency and reduced costs through local deployment, with optimized vector databases for fast and accurate information retrieval.

  • Seamless Integration

    Build efficient RAG pipelines for domain-specific knowledge bases and develop hybrid solutions that combine local and cloud AI capabilities.

Latest From the Blog

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Olajoke Oladipo /

Introducing cheetahR: A Lightning-Fast HTML Table widget for R

R/Tables/htmlWidgets

Say hello to cheetahR — the fastest way to explore massive datasets in R. Now available on CRAN, cheetahR is a high-performance table widget and a modern alternative to {reactable} and {DT}. Built for speed, it lets you interactively explore large datasets with smooth rendering and fully customizable layouts. Plus, it integrates seamlessly with Shiny, making it perfect for powerful, data-heavy dashboards.

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David Granjon, Nelson Stevens, Nicolas Bennett /

Introducing dockViewR 0.1.0: a layout manager for R and Shiny.

Shiny/R

Create fully customizable grid layouts (docks) in seconds to include in interactive R reports with R Markdown or 'Quarto' or in 'shiny' apps . In 'shiny' mode, modify docks by dynamically adding, removing or moving panels or groups of panels from the server function. Choose among 8 stunning themes (dark and light), serialise the state of a dock to restore it later..

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Mike Page /

Introducing shinydraw: a no-code tool for shiny wireframing

Shiny/R

Streamline your Shiny app design: Introducing shinydraw for effortless wireframing

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David Schoch, Christoph Sax /

R with RAGS: An Introduction to rchroma and ChromaDB

LLM/RAG/R

Large language models (LLMs) are developing rapidly, but they often lack real-time, specific information. Retrieval-augmented generation (RAG) addresses this by letting LLMs fetch relevant documents during text generation, instead of just using their internal—and potentially outdated— knowledge.

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Tamás Tóth, Jonas Goldstein, Christoph Sax /

Website Relaunch

We're thrilled to announce the launch of our completely redesigned website! After months of careful planning and development, we've created a new digital home that embodies our core values: minimalism, functionalism, and clarity.

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Maëlle Salmon, David Schoch, Kirill Müller /

Setting up igraph for success in the next decade

igraph/R

One year ago, a small group of us at cynkra submitted a project proposal to the R Consortium's ISC, which got approved. We are very grateful for this support. In this post we shall explain what the motivation for our project was, what we accomplished... and what we hope to work on next!