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Winnoh

An AI assistant that learns from the sources you choose. Point it at a Slack channel, a subreddit, your docs, or any data stream. Ask anything. Get answers grounded in your context, not the internet's best guess.

Winnoh

The Problem

Building the Walmart AI project taught us something we couldn't stop thinking about. When you train an AI on a specific, bounded data set, the quality of the answers goes up dramatically. Executives could ask real questions about real visitor feedback and get real answers.

The problem with generic AI isn't intelligence. It's context. Ask ChatGPT what your customers are complaining about and you'll get a statistically reasonable non-answer. Ask an AI that's been fed your support channel and you get something you'd act on.

The Walmart project proved this with one client, one source, built end to end. The obvious next question was: what if anyone could do that? What if you could just point an AI at whatever information matters to you and ask it things?

Nobody was asking "which Slack channel should I read this morning." They were asking "what do I need to know today." Winnoh is the answer to that.

What We Built

Winnoh is a personal AI assistant you build yourself, source by source. You connect the information that matters to you. You ask questions. You get answers grounded in your context, with citations showing exactly where each answer came from.

Source Connectors

  • Slack: connect any channel you have access to. Winnoh reads message history, stays in sync, and understands thread context.
  • Reddit: connect any public subreddit. Filter by recency, post type, or minimum upvote threshold to cut noise.
  • Web and RSS: paste any URL. Winnoh crawls it, detects RSS where it exists, and re-crawls on a schedule.
  • Files: upload PDFs, Word docs, Markdown files, and CSVs. Drop in a research report, a contract, a set of meeting notes.
  • Notion and Google Docs: connect pages or entire workspaces via OAuth. Stays in sync as docs get updated.

The Ingestion Pipeline

  • Content from each source is chunked, preprocessed, and embedded into a vector store.
  • Each chunk maps back to its source, timestamp, and original URL.
  • On query, Winnoh retrieves the most relevant chunks across all connected sources.
  • Those chunks go to the LLM as context. The answer comes back with citations.
  • Sources resync on a schedule so Winnoh knows what happened yesterday, not just when you set it up.

Source Requests

  • If a connector you need doesn't exist yet, you can request it directly in the app.
  • Other users can upvote requests they want too.
  • The most-requested connectors get built next. Community-driven roadmap baked into the product.

What People Use It For

The product unlocks differently for different people. That's the point. You bring the context. Winnoh figures out the answer.

Slack + Docs

"What do I need to handle today?"

Points at your relevant channels and docs. Gets a prioritized briefing every morning.

Reddit

"Why are people switching away from my competitor?"

Points at relevant subreddits. Gets verbatim complaints, real language, and real reasons instead of analyst summaries.

Slack + Internal Docs

"How does our deployment process work?"

New hire onboarding. Points it at the engineering channel and your runbooks. No more interrupting the senior engineer.

PDF Files

"What are the key themes across these five reports?"

Drops in a folder of research PDFs. Gets a synthesis in minutes instead of an afternoon of reading.

Web / RSS

"What content topics are competitors hitting this month?"

Points at competitor blogs via RSS. Spots patterns in their content strategy without manually reading every post.

Reddit + Web

"What do people really think about product-market fit?"

Points at r/startups, r/entrepreneur, and a few founder newsletters. Builds a real picture from primary sources, not secondary summaries.

Let's Work Together

Want to build something like this?

AI that knows your context, not the internet's best guess. We build RAG pipelines, source integrations, and AI products that answer real questions from real data.