esnc.me is a second-brain service for companies that want every decision, document, and conversation to be queryable. It is described as private by default and built for teams that want answers drawn from their own material rather than uncited output. The site says each answer is cited to its source.
The service offers three shapes of second brain. Org Essence models a company’s voice, principles, decision history, and brand tone; Retrieval is for querying a company’s corpus of documents and records; and Expert Clones are meant to reflect subject matter experts’ judgment and voice. The page says these are custom essences trained on a company’s data. It also says the system can answer using docs, Slack, transcripts, and tribal knowledge, and that responses link back to a source document with the span they draw from.
Delivery is listed as a chat widget, Slack app, API, or all three. The examples and source map on the page refer to sources such as Notion, Slack, Drive, PDFs, Zendesk tickets, Gmail, Linear, call transcripts, Figma, and documents, and the site says continuous ingestion keeps the essence in sync with Slack, Drive, and new docs. It also says the infrastructure runs on the customer’s chosen cloud, region, and keys, with read-only sources and isolated keys held by the customer. Export of the full corpus, fine-tuned weights, and retrieval index is described as available at any time.
The site frames no lock-in as a principle and says there are contractual guarantees, but it does not describe a specific licensing model. It identifies itself as “Second Brain as a Service” and invites interested companies to start a project and receive a discovery questionnaire.
esnc.me is a RAG, search & retrieval project. It focuses on making company knowledge, documents, and conversations easily searchable and accessible through an AI-powered assistant. esnc.me is a B2B product aimed at companies seeking to organize and access internal knowledge. esnc.me is available on the web.
Key capabilities include AI-powered search, cited answers, and document ingestion. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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