Enterprises struggle to leverage large language models (LLMs) for internal knowledge discovery due to concerns about data security, intellectual property leakage, and the inability of generic models to access private content. Existing search solutions often require storing proprietary data in external clouds, creating unacceptable risks for many organizations.

Atolio provides an AI-powered enterprise search engine that indexes and retrieves data from within a company's private cloud, ensuring secure and permission-aware access to proprietary information. The platform integrates with existing workplace applications and leverages LLMs that do not train on customer data, guaranteeing that intellectual property remains protected. By consolidating knowledge from disparate systems and applying advanced information retrieval techniques, Atolio delivers contextually relevant answers, identifies subject matter experts, and reduces the time employees spend searching for information. The solution is deployed within the customer's virtual private cloud on AWS, Azure, or GCP, providing a fully self-hosted conversational experience.

Indexes data within the customer's own virtual private cloud (VPC) on AWS, Azure, or GCP

Integrates with workplace applications via pre-built connectors

Leverages LLMs that do not train on customer data, ensuring IP protection

Tracks individual access control lists (ACLs) at the document and system level

Employs a combination of signals and information retrieval techniques to deliver relevant answers

Identifies subject matter experts within the organization

Supports Azure OpenAI, native OpenAI, and Bedrock-supported models

Atolio is designed for large enterprises and hypergrowth companies that require secure, AI-powered search capabilities without compromising data privacy or control.

Atolio is priced per-user with volume, non-profit, and educational discounts, with no additional license costs for LLM usage, data ingest, or connectors.