Lingvist
Master vocabulary 10x faster with AI-driven spaced repetition and big-data linguistics.
Supercharge Google Sheets with enterprise-grade LLM orchestration for automated data intelligence.
AI Sheet Master is a high-performance Google Workspace integration designed to operationalize Large Language Models (LLMs) within spreadsheet environments. By 2026, it has positioned itself as a critical middleware for data analysts and marketers who require bulk-processing capabilities beyond simple chat interfaces. The tool utilizes custom GAS (Google Apps Script) functions to enable asynchronous execution of prompts across thousands of rows simultaneously. Its architecture supports multi-model routing, allowing users to toggle between OpenAI's GPT-4o, Anthropic's Claude 3.5, and specialized open-source models for tasks ranging from sentiment analysis and entity extraction to complex data normalization. Unlike generic AI extensions, AI Sheet Master focuses on data integrity and cost-efficiency, offering advanced features like context-aware cell referencing and PII masking to ensure enterprise-grade security standards. As businesses move toward data-centric AI operations, AI Sheet Master serves as the primary bridge between raw tabular data and actionable cognitive insights, significantly reducing manual data cleaning time by up to 85%.
Enables prompts to dynamically ingest data from multiple non-contiguous ranges as contextual vectors.
Master vocabulary 10x faster with AI-driven spaced repetition and big-data linguistics.
A simple terminal UI for git commands that streamlines complex workflows without the overhead of heavy GUIs.
Turn spreadsheets into intelligent data engines with native LLM orchestration and automated formula generation.
The minimalist's gateway to focused reading and intelligent content archival.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Bypasses Google's 6-minute execution limit by batching requests through a proprietary queueing system.
Logic-based switching between models based on task complexity and token cost.
Combines natural language extraction with strict Regex validation for structural integrity.
Automatically detects and redacts sensitive information before sending data to third-party LLM APIs.
Identifies logically identical entries in a list even if wording is different using embeddings.
Allows users to save complex, multi-step prompt chains as reusable private custom functions.
Manually writing thousands of unique, SEO-optimized descriptions for SKU lists.
Registry Updated:2/7/2026
Use Bulk Processor to execute over the next 10 minutes.
Categorizing thousands of support tickets for monthly reporting.
Converting a list of domain names into detailed company profiles.