
Chattermill
MightyForms
Cliently
ClientZen
Workflowy
Back
Yess
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.

Canny.io
productboard
Dovetail
Chattermill
Survicate
Thematic
Sentriment
Enterpret is the leading customer feedback analytics platform that unifies large volumes of feedback across tickets, calls, and reviews to surface customer insights and drive product decisions faster.

Which is more popular?
Based on our record, Obsei seems to be more popular. It has been mentioned 1 time since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | obsei.com | enterpret.com |
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| Platforms | — | |
| Company | 2020 | Startup from India · 50 - 99 employees · 2020 |
| Listed in |
In their own words, as submitted to SaaSHub.


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,...
Enterpret is an AI-powered customer feedback intelligence platform that helps product, support, and customer experience teams understand what customers are saying across multiple feedback channels. The platform consolidates feedback from sources like support tickets, surveys, product analytics,...
What each product offers, as listed by its team.


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


No analysis of Obsei yet.
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
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Introducing Enterpret 2.0: A new era for Customer Intelligence
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Obsei and Enterpret.
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.
Enterpret's answer:
Enterpret stands out by combining AI-powered feedback analysis with deep business context. Unlike traditional tools that simply collect or categorize feedback, Enterpret unifies feedback from all sources and enriches it with product, customer, and organizational data. Its adaptive taxonomy continuously learns and evolves, enabling teams to uncover the “why” behind feedback and generate accurate, actionable insights at scale.
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.
Enterpret's answer:
Enterpret goes beyond surface-level sentiment by using AI to deliver structured, data-backed insights from feedback across 50+ sources, enriched with business context.Its adaptive multi-level taxonomy automatically organizes feedback into a dynamic hierarchy, uncovering the “why” without manual tagging. With Wisdom AI, teams can ask questions in natural language and get instant, cited insights, making decision-making faster, clearer, and more reliable.
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.
Enterpret's answer:
Enterpret is designed for product, customer experience, and support teams at B2B and enterprise companies. It is especially valuable for organizations that receive large volumes of customer feedback and need a scalable way to analyze it and turn it into actionable product and business decisions.
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.
Enterpret's answer:
Enterpret was built to solve a common problem: customer feedback is scattered across multiple tools and channels, making it difficult for teams to extract meaningful insights. We saw that companies were sitting on valuable customer signals but lacked the tools to connect and analyze them effectively. Enterpret was created to bring all feedback into one place and use AI to transform it into clear, actionable insights that drive better product decisions.
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.
Enterpret's answer:
Enterpret leverages modern AI technologies including large language models (LLMs), natural language processing (NLP), and machine learning to analyze unstructured customer feedback. It also integrates with various data sources and enterprise systems to enrich insights with business context and ensure scalability, security, and real-time processing.
Share your experience with using Obsei and Enterpret. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


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
Tracking Enterpret since Mar 2026.
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