hn-ai-summarizer vs OpenBrief

hn-ai-summarizer and OpenBrief are both summarizers tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

hn-ai-summarizer

The tool runs on a schedule, pulls the top Hacker News stories, summarizes them with an AI model, and delivers a filtered, translated briefing to a Telegram channel or chat. It lives entirely on your own hardware via Docker, so no data leaves your infrastructure. That self-hosted constraint is the whole point — and also the ceiling. There is no hosted version, no web UI for non-technical users, and no notification channel beyond Telegram. If your team communicates in Slack or needs a browser-based dashboard, this does not cover that.

OpenBrief

The workflow is a single desktop session: import a local file or supported web link, generate a transcript (pulling existing captions when available to skip unnecessary processing), ask questions grounded in the transcript, and export a clean Markdown file. Nothing leaves your device. That privacy guarantee is the product — not a feature tier. Where it breaks: this is a one-shot summarization and Q&A tool, not an agent. It does not connect to calendars, trigger follow-up tasks, or push notes anywhere automatically. Teams that need downstream automation — routing action items into Notion, Slack, or a CRM — have to handle that export step themselves.

Attribute	hn-ai-summarizer	OpenBrief
Pricing	Free	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	Yes
Self-hosted option	Yes	Yes
Platforms	Docker, self-hosted servers, Raspberry Pi, NAS	Mac, Windows, Linux
Released	—	2026-05
Pros	Scheduled AI summarization of top Hacker News stories, so you read the signal without manually triaging the full front page each day. Keyword-based interest filtering — configured per-user — so stories outside your focus areas (say, anything not tagged AI or security) are excluded before the briefing is assembled. Translation support for non-English readers, which means you get the summary in your working language rather than having to run stories through a separate translation step. Fully self-hosted via Docker with an MIT license, so your reading preferences and API credentials never touch a third-party cloud service — the alternative being tools that log your queries on vendor infrastructure. Telegram delivery with scheduling, which means the briefing arrives at a time you set rather than requiring you to open a dashboard and remember to check it.	All processing stays on-device with no account required, so recordings covered by NDAs or participant confidentiality agreements never touch a third-party server. BYOK model integration means you choose the LLM provider and pay your own API costs directly — no markup, no vendor lock-in to a single model, so swapping providers when pricing changes is a configuration edit. Captions-first transcription pulls existing captions before running a full transcription pass, so you avoid unnecessary API calls and get output faster on content that already carries captions. Q&A answers are grounded in the transcript, which means you get citations back to what was actually said rather than a model synthesizing outside its source. Markdown export delivers a portable file you control — summaries, timestamps, and notes move into any downstream tool without reformatting.
Cons	Telegram is the only supported notification channel. Teams or individuals whose async communication runs through Slack, Discord, or email cannot use this without modifying the source code — there is no plugin or webhook abstraction in the current codebase. There is no web UI. Configuration lives entirely in environment variables and the docker-compose file, which means every setting change requires SSH access and a container restart. Non-technical users or shared-team deployments stall at the setup stage. The tool has no REST API or output format beyond Telegram messages, so any team wanting to pipe summaries into a second system — a Notion database, a team wiki, a Slack bot — is writing custom glue code rather than using a supported integration. With three GitHub stars and zero forks at the time of scraping, community support is minimal. When the upstream Hacker News API or a chosen AI provider changes behavior, the maintainer is a single point of failure. Teams with production-critical digest pipelines move to more actively maintained alternatives at the first breaking change.	There is no automation layer after the export step: action items, decisions, and summaries land in a Markdown file and stop there. Teams that need notes pushed into Notion, Jira, or a CRM build that connection manually — or switch to a cloud tool like Read.ai that ships those integrations. BYOK means you are responsible for API key management, provider selection, and any costs that come with heavy usage. Users who want a managed, zero-configuration experience — where the LLM is already wired in — will find the setup friction real before the first transcript runs. The tool is scoped to summarization and Q&A on a single source at a time. There is no cross-source synthesis, no batch processing across a library of recordings, and no way to ask a question that spans multiple files — a gap that becomes visible the moment a researcher wants to compare themes across a dozen interviews.

Bottom line

Only OpenBrief exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between hn-ai-summarizer and OpenBrief?

hn-ai-summarizer is Free and open source, while OpenBrief is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is hn-ai-summarizer better than OpenBrief?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.