From the Award-Winning Regulatory Experts

RuleXis

2 Million-Token Context Window

See how RuleXis processes your entire corpus — policies, board packs, and regulator updates — in one pass.

Hand-drawn sketch showing puzzle metaphor with scattered disconnected pieces and frustrated professionals on left, versus completed puzzle with RuleXis logo at center connecting all regulatory elements seamlessly with satisfied compliance team on right
How many tokens is your document?
Paste text or enter a word count. We estimate tokens for OpenAI (32k) and Google/Gemini (2M). Defaults use your measured ratio (1.4056 t/word); toggle conservative to use 1.64 t/word.
Privacy note: all calculations run in your browser.
Measured: 1.4056 t/word Range guide: 1.3–1.7 t/word
Your Document
0 words = 0 tokens
Using measured ratio (1.4056 tokens/word)
ChatGPT (32k tokens)
0%
0 tokens
✓ Fits comfortably
Capacity: 32k tokens
RuleXis / Gemini (2M tokens)
0%
0 tokens
✓ Plenty of room
Capacity: 2M tokens

Note: Most models ≈ 32k tokens; RuleXis handles up to 2M tokens in one go.

Tip: If your text contains tables, or your file is a PDF, the token count may be considerably higher due to 'hidden characters' within the format of the file.

The 2 Million-Token Context Window

Most compliance and governance platforms — especially those built on ChatGPT or similar models — are limited by their context window. This window, measured in tokens, defines how much text an AI can hold in its short-term memory at once. For many competitors, that’s around 32 000 tokens — roughly 20 000 words — barely enough to process a handful of policies or minutes together.

RuleXis works differently.
Our intelligent agents choose the right model for each task from a model garden, allowing us to use advanced architectures like Google Gemini, which offers a 2 million-token context window.
That means RuleXis can read, reason over, and explain entire regulatory corpora — not just fragments.

This counter shows you the scale of that difference.

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