DeepChives AI

Introduction to DeepChives AI

DeepChives AI is a document intelligence platform that enables users to interact with their existing files—such as PDFs, presentations, images, videos, and audio recordings—using natural language queries. It connects securely to cloud and local storage systems to index content semantically, allowing users to search by meaning rather than filenames or keywords. The platform is designed for professionals who manage large volumes of internal documentation, including knowledge workers, researchers, legal and compliance teams, and business analysts.

Unlike traditional search tools, DeepChives AI processes multimodal inputs (text, video transcripts, audio transcriptions, and OCR-extracted text from images) to build contextual understanding across file types. It supports both synchronous question-answering and generative tasks, enabling users to synthesize insights or draft new documents grounded in their proprietary content.

Key Takeaways

• Semantic search across documents, PDFs, slides, images, videos, and audio files
• Integration with major cloud storage providers: Dropbox, Google Drive, OneDrive, Box, Confluence, AWS, Azure, and local file systems
• Generation of new documents—including proposals, summaries, and letters—using the user’s own content and stylistic patterns
• Enterprise-grade security: SOC-2 Type II certified, data encrypted at rest and in transit, hosted within a virtual private cloud (VPC)
• Support for web-based results alongside internal documents to provide broader context
• Folder-level control over file synchronization—users can select specific directories or scan entire libraries
• Referral program offering 10% commission on successful referrals to paying customers

How DeepChives AI Works

DeepChives AI operates through a three-step workflow: connection, synchronization, and interaction. First, users connect their preferred storage accounts via OAuth or secure API keys. Second, they configure which folders or repositories to index—either selectively or comprehensively—with optional filtering by file type or date range. During indexing, the system extracts and embeds textual content, transcribes audio/video, and applies optical character recognition (OCR) to scanned images.

Once indexed, users interact with their documents through a chat-based interface. Queries are processed using large language models fine-tuned for domain-aware retrieval and synthesis. Responses are grounded in the user’s indexed corpus, with citations linking answers to source files and timestamps (for video/audio). Users may also prompt the system to generate new documents based on retrieved information, preserving tone and terminology consistent with their existing materials.

Core Benefits and Applications

DeepChives AI reduces time spent locating information across heterogeneous file collections, particularly in regulated or documentation-heavy environments such as legal discovery, technical support, or academic research. Teams use it to accelerate proposal drafting by auto-generating responses from past RFPs and case studies; to summarize lengthy meeting recordings or training videos; to cross-reference compliance documentation across departments; and to maintain consistency in customer-facing communications by drawing from approved templates and historical correspondence. Its ability to unify search and generation across modalities makes it especially valuable where information resides in siloed formats—e.g., contracts in PDF, meeting notes in Confluence, product demos in video, and sales calls in audio recordings.