The freedom of Markdown.
The power of Word.

Antalogy’s integrated AI Assistant chat lets you brainstorm, edit, summarize, or audit documents without leaving your workflow. Unlike locked-in cloud AI suites, you decide where the model runs:

• Local: run quantized LLMs on your own GPU/CPU for total isolation.
• On-prem / private cloud: connect to your private inference server, Kubernetes cluster, or enterprise LLM harness.
• Cloud: plug into your preferred LLM provider for maximum capability.

Antalogy supports any LLM with an OpenAI-compatible API. You can switch endpoints per document, per LLM chat, or per compliance tier. The AI Assistant adapts to your security posture without changing your workflow.

While .docx is engineered for print rendering, Markdown is engineered for data exchange. Its hierarchical, plain-text structure aligns perfectly with how LLMs parse, reason, and generate text.

• Higher accuracy: clean structure reduces hallucination rates and improves formatting fidelity in AI outputs.
• Faster inference: less overhead means quicker tokenization and response generation.
• Future-proof archives: Markdown remains readable, editable, and interoperable across decades and platforms. No platform (OS) dependencies. No vendor lock-in. No format decay.

Switching from DOCX to Markdown cuts token waste by 31–35%, making every token count and stretching your AI budget further across documents of all sizes*:

*Based on typical business documents containing headers, lists, tables, and standard formatting.

The context window is the AI’s working memory. Every token spent on XML scaffolding or hidden styling is a token stolen from your actual content.

• DOCX impact: structural noise fills the AI’s memory faster. As documents grow, the model reaches its limit sooner and begins to “forget” early instructions, clauses, or data to accommodate later sections.
• Markdown impact: by stripping the noise, Antalogy maximizes the effective context window. You can feed significantly more substantive content into a single prompt while ensuring the AI maintains perfect recall from the first line to the last.

“Image bloat” occurs when you upload a .docx file containing images directly into a Large Language Model (LLM). It wastes massive amounts of your token window and drastically increases API costs, while often degrading model performance. Because LLMs process visual information by converting images into large mathematical matrices (or high-token sequences), a single hidden or unoptimized image can consume more tokens than the entire text of a long document.

• DOCX burden: images are embedded as binary objects wrapped in heavy metadata. AI parsers often treat this as opaque token sequences, wasting context space and increasing latency.
• Markdown advantage: images live in Markdown documents as lightweight references, separated from the text. Antalogy’s integrated AI Assistant skips images when sending your document to the LLM, so you can freely work with Markdown documents that contain embedded images. Many kilobytes of binary overhead become a single line of text — keeping the AI focused on your words, not your file structure.

We do not track your usage, we do not log your keystrokes, and we do not collect any personal or behavioral data. There are no tracking scripts, analytics tools, or telemetry frameworks embedded in the software. What you write, edit, or process stays strictly on your machine.

Antalogy is compiled into a native desktop binary using Go and Wails. It does not look for, connect to, or maintain any cloud backend. Your documents (.md and .docx files) are read and written directly to your local file system. We have no servers capable of receiving or storing your documents.

The user interface is powered by Svelte and rendered through your operating system's native webview engine (WebView2 on Windows and WebKit on macOS) instead of a bundled Chromium instance. This ensures the app operates isolated within your local system environment with no unauthorized internet connectivity.

The integrated AI Assistant is entirely dormant by default. Antalogy does not route your text through any proprietary AI proxies or intermediate cloud setups. No content is ever sent to an AI model without your explicit, manual action.

• Connection to an AI model only occurs if you explicitly input your own OpenAI-compatible API keys or point the app to your own local inference server (such as LM Studio or Ollama).
• When active, you may optionally attach your open document content, selected text, or a local file to a chat message. This is done solely through dedicated buttons in the Assistant pane — nothing is attached automatically or in the background.
• When active, the application communicates directly from your device to the endpoint you specified. No text, prompts, or token matrices are ever sent to us or any third party.

Because we operate in complete transparency, we invite any user, engineer, or security auditor to drop Antalogy into a secure sandbox or monitor its network traffic using tools like Wireshark. You will find exactly zero unexpected network calls leaving your machine.

Antalogy is currently developed and maintained by an independent group of software engineers in bootstrap mode. As the product transitions into a formal legal structure for enterprise utilities (such as high-volume B2B bulk conversion pipelines and OEM/White Label licensing), this policy will remain anchored to the core principle that your standalone desktop files are yours alone.

For any privacy-related or technical questions, feel free to reach out directly to the engineering team at: info@antalogy.com