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Omnesis

A private knowledge layer for ChatGPT and other agents

Details

External ID
49877752
Source
HN
Company
—
Product
Omnesis
Website domain
omnesis.dev
Launched
Sept. 28, 2026
Cohort
—
Upvotes
10
Upvotes percentile
0.5853269537480064
Tags
—
Fetched at
Sept. 30, 2026, 5:01 p.m.
Updated at
Sept. 30, 2026, 5:01 p.m.

Description

Imagine giving ChatGPT or any other agent access to your Whatsapp/iMessage, bank transactions, health data, web pages you see, metadata about all the photos you took, places you visited, all your emails/documents, call logs, meeting notes, your voice mails, and more….I built a context layer for that purpose. You can connect your Openclaw, Hermes, Claude, ChatGPT, Codex, etc to it. It gives your favorite agent "context superpowers". All the data is indexed and connected into a graph, self-hosted on your own hardware. Voice notes are transcribed, OCR runs on images in mails and pdfs, etc.Omnesis offers a flexible data access model. For each agent you can define which source(s) they have access to and also guard data access with a privacy policy written in prose. You can also directly talk to the Omnesis agent which has no web search / internet tools — via a web portal or companion app — to ask the most intimate questions about your digital life.I built this to be flexible. You can run all necessary models on zero-data-retention inference providers, or — if you can afford it — on your own hardware. I’ll keep investing in Omnesis’s security. Because it brings together sensitive data from many sources, please install it only on machines you control and keep secure.The project also includes what I call “Omnesis Brain”. This is my work-in-progress take on what a “second brain” could look like on top of that context layer. Imagine an agent constantly analyzing your personal data in flux to maintain a more structured and grounded understanding of what’s happening in your life. This is experimental and disabled by default.This has been a fun project to build over the last 6 months. Keen to answer questions!

Enrichment

Theme
niche social and community platforms
Vertical
Horizontal
Function
Search & retrieval
Audience
Prosumer
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
private knowledge base for ai agents
Manually corrected
False

Could you build this?

No Building a cross-platform, local-first personal index across encrypted messaging databases (iMessage, WhatsApp), bank data, health data, and local files requires deep systems engineering and reverse engineering private OS databases.

What it would actually take: This requires native daemons across macOS, Linux, iOS, and Android (Swift, Rust, Kotlin) that parse proprietary local application databases (e.g. SQLite for chat.db, browser histories, health stores), background file system watchers, local vector databases (e.g. SQLite-vec or LanceDB) with on-device embedding models, and strict local sandboxing to protect sensitive data.

Discussion

4 comments analyzed.

Competitors

Other products that read as similar to this one — 148 launches clear the similarity bar, closest 8 shown.

Attention rank: #67 of 149 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 334 days after the earliest competitor.

Other launches for this product