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Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Low-code AI automation for social data collection and analysis
Obsei streamlines gathering, AI-driven analysis, and routing of unstructured social and review data, enabling automated insights, alerts, and ticket creation with minimal code.
Obsei is a low‑code framework that lets data engineers and product teams build end‑to‑end pipelines for unstructured social and review content. By configuring an Observer you can pull data from Twitter, Reddit, Facebook, app‑store reviews, news sites, and more without writing custom scrapers.
Collected items flow into the Analyzer, where plug‑in AI tasks such as sentiment classification, language translation, PII detection, or custom models can be applied. The results are then handed to an Informer, which can create tickets in Jira, push records to Elasticsearch, store dataframes, or trigger Slack alerts. Observers optionally persist their cursor state in SQLite, PostgreSQL or MySQL, making the workflow suitable for cron jobs, Airflow DAGs, or serverless functions.
Install with pip install obsei[all] or select only the needed extras (e.g., twitter-api, analyzer). The modular design enables rapid prototyping, but the project is currently in alpha, so users should prefer released versions for production. Documentation and community channels are available for support.
When teams consider Obsei, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Social listening dashboard
Continuously collect brand mentions from Twitter and Reddit, analyze sentiment, and push daily summaries to a Slack channel.
Automated ticket creation
Detect negative customer complaints in app‑store reviews, classify issue type, and automatically open tickets in Jira with relevant tags.
Market research dataset
Scrape product reviews from Amazon and Google Play, run classification and translation, and store the enriched dataset in a CSV for model training.
Compliance monitoring
Scan public comments for PII, flag matches, and send alerts to a secure Elasticsearch index for audit.
Obsei runs on Python 3.7 or newer.
Yes, you can install only the extras you need, such as `twitter-api` or `analyzer`, via pip.
Observers can persist their cursor or last‑fetched timestamp in SQLite, PostgreSQL, MySQL, or other supported databases.
Obsei is primarily a code‑first library; a UI is not provided out of the box.
The project is currently in alpha; it is recommended to use released versions and evaluate stability before critical production deployments.
Project at a glance
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