
Vercel
Netlify
Cloudflare Pages
Jekyll
tiiny.host
surge.sh
Neocities
A free, static web host for open-source projects on GitHub

Enterpret
Chattermill
MightyForms
Cliently
ClientZen
Workflowy
Back
Open source, privacy-first Voice of Customer analytics. A self-hosted alternative to Enterpret and Unwrap that strips PII from feedback before any LLM sees it.

Which is more popular?
Based on our record, GitHub Pages seems to be a lot more popular than Obsei. While we know about 505 links to GitHub Pages, we've tracked only 1 mention of Obsei.
Website, pricing, platforms and company facts side by side.
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| Website | pages.github.com | obsei.com |
| Pricing | ||
| Company | — | 2020 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of GitHub Pages yet.
Obsei is an open source, self-hosted Voice of Customer platform. It reads customer feedback from wherever it lives, removes personal data before any AI model sees it, and shows your team what customers are saying. What it does Collects feedback from the App Store, Google Play, Zendesk, Freshdesk,...
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
No analysis of Obsei yet.
Walkthroughs and reviews on video.
Intro to GitHub Pages
More videos
No Obsei videos yet. You could help us improve this page by suggesting one.
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing GitHub Pages and Obsei.
Obsei's answer:
Obsei removes personal data before any AI model sees your customers' words. Emails, phone numbers, card numbers and national IDs are stripped as feedback arrives, authors become pseudonyms, and the database is encrypted. The default classifier runs on your own machine, so you can analyse reviews, tickets and calls without sending them to a SaaS vendor or a public LLM. It is also open source under Apache-2.0, with no paid tier, and it works with AI agents through MCP, so Claude, Cursor or Codex can answer "what are customers saying?" with real, redacted quotes.
Obsei's answer:
Choose Obsei if you can't, or don't want to, send customer text to another company. Enterpret, Unwrap and Chattermill process your feedback on their servers and usually start at several thousand dollars a year. Obsei runs inside your own infrastructure, costs nothing, and lets you bring your own model, from a small local classifier to Ollama, Azure OpenAI or Bedrock. You also aren't locked in: the data stays in an encrypted DuckDB file you own, and every source, sink and model can be swapped.
Obsei's answer:
Product, support and CX teams who want to understand customer feedback at scale but work under privacy rules: banks, insurers, healthcare, public services, and companies working under GDPR or India's DPDP Act. It also suits app developers and open source maintainers who want to track App Store, Google Play, GitHub or Hacker News feedback for free, and engineering teams building AI agents that need customer evidence without exposing personal data.
Obsei's answer:
I started Obsei in 2020 as a small open source Python library to read app reviews and tweets with AI models. In 2022 it was a joint runner-up in the Reserve Bank of India's first global hackathon, HARBINGER, and my co-founder Girish Patel and I started a company, Oraika, around it. We had encouraging meetings with banks, but we were engineers with no experience of enterprise sales, and we couldn't close a deal. The project went quiet for almost three years.
In 2026 I came back to it. Customer feedback had become even more sensitive with LLMs everywhere, so I rewrote Obsei from scratch around one rule: understand customers without moving their personal data anywhere it shouldn't go. Version 1.0 shipped in October 2026. I maintain it in my free time, and the long-term plan is to move it to a neutral foundation such as LF AI & Data.
Obsei's answer:
Python 3.11+ with Pydantic for configuration, Typer for the CLI, httpx for connectors and Starlette for the server. DuckDB with its encryption extension for storage. Hugging Face Transformers for the default zero-shot classifier (bge-m3-zeroshot-v2.0), fastembed for multilingual embeddings and GLiNER for optional name redaction. The official MCP Python SDK for the agent server. The Studio UI is plain TypeScript bundled with esbuild, and the docs and website are built with Astro.
Share your experience with using GitHub Pages and Obsei. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


GitHub Pages is a free hosting service provided by GitHub, primarily intended for hosting static sites directly from a GitHub repository. While it lacks some of the advanced features found in other platforms, its...
Static Site Generators — It is a good way for developers to build sites on GitHub pages with the help of site generators. Yes, it has the ability to publish and release any static file. But it is recommended to...
We have no reviews of Obsei yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


My bookmarks have been public since 1998, and the previous version, bookmarks-v3.0, was a static site generated by Jekyll and published on GitHub Pages: it cost nothing, and for a list of public links it was good enough. The criterion... - Source: dev.to / about 1 month ago
The site itself is a statically generated Next.js app, built in CI and deployed to GitHub Pages via actions/deploy-pages. No server to manage, no hosting bill. - Source: dev.to / 7 months ago
Static sites are fast and cheap to host, but your data goes stale the moment you deploy. This post shows how a SvelteKit portfolio site serves live data from five external sources while still deploying as static HTML to GitHub Pages. - Source: dev.to / 8 months ago
Allow me to introduce Obsei (pronounced "Ob see" | /əb-'sē/). It is a low-code AI powered automation tool. Name was derived from three words OBServe, AnalyzE, Inform. - Source: dev.to / almost 5 years ago
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