SumizAI vs Hjarni

What Hjarni is

Hjarni is a knowledge base designed specifically for ChatGPT and Claude, solving one of the most repetitive problems in everyday work with language models - having to re-explain the same context in every conversation. Instead of saving notes in a separate tool detached from the model, Hjarni lets information be saved once and connected to ChatGPT or Claude through MCP (Model Context Protocol), giving the model direct access to that knowledge in every subsequent conversation. The application comes from Belgium, within the European Union, and runs as an online service under a freemium model.

Key features and functionality

Hjarni's core mechanism is a one-time note save that a language model gains persistent access to through MCP integration, instead of requiring the user to manually paste the same context at the start of every new conversation. The integration works with both ChatGPT and Claude, setting Hjarni apart from solutions tuned to a single model provider and letting users maintain a coherent knowledge base regardless of which model they're currently using. MCP, an open standard letting models securely access external data sources, means Hjarni doesn't have to rely on unofficial workarounds or manual content copying - the model can query the knowledge base on its own during a conversation, exactly when a given piece of information is needed. The notes feature lets saved knowledge be organized in a way that naturally matches the structure of the projects or topics a user is working on.

Who it's for

Hjarni is aimed primarily at people who regularly use both ChatGPT and Claude and are tired of re-explaining the same project context at the start of every new session with either model. Consultants and freelancers running multiple parallel client projects appreciate being able to quickly switch context without manually reminding the model of every client's details from scratch. Technical teams working on complex systems use Hjarni as a centralized source of knowledge about project architecture and conventions, accessible to both supported models at once. People running long-term research or creative projects value the time saved by eliminating repetitive, tedious re-entry of context.

Use cases

While working on a long-term coding project, a developer saves key architectural decisions and code conventions in Hjarni, and both ChatGPT and Claude then access them through MCP in every subsequent session, without needing the context explained again. A consultant handling several clients at once keeps separate notes for each in Hjarni, letting them quickly switch between different project contexts without risking mixing up information. A team working on product documentation updates the knowledge base in Hjarni as the project evolves, confident that AI models used by different team members answer based on the same, current information. Someone conducting research over many weeks uses Hjarni to store findings from previous sessions, letting the model continue the analysis exactly where it left off.

Pricing and business model

Hjarni runs on a freemium model, offering free access to core knowledge-base functionality and a paid subscription unlocking larger note storage limits and expanded integration capabilities. This model lets users test the real value of eliminating repetitive context entry before deciding on a paid subscription that supports working across a larger number of parallel projects.

Comparison with SumizAI

Hjarni and SumizAI address different aspects of working with AI models. Hjarni is a specialized knowledge base integrating directly with ChatGPT and Claude through MCP to eliminate the need to repeat context. SumizAI, by contrast, is a platform enabling conversations with multiple AI providers at once in a single interface, without a specialized mechanism for persistent knowledge directly connected to the model. Someone using Hjarni as a memory layer for ChatGPT and Claude might use SumizAI in parallel when they need to compare those models' answers against other AI providers' perspectives on the same question.

AI notes read directly by the model

Hjarni is, in practice, an ai notes system designed so the model can read them on its own through MCP, setting it apart from a traditional notepad meant to be read only by a human. The more valuable ai notes that go into Hjarni, the less time the user wastes repeating the same explanations in every new conversation with the model, significantly speeding up work on long-term projects over time. Teams sharing access to a common ai notes base in Hjarni build centralized project memory, accessible to every team member regardless of which supported model they happen to be using. Regularly updating such ai notes keeps the knowledge base current even as project decisions change quickly.

What SumizAI is

A note-taking application built around a conversation with an AI model. You ask a question, the answer streams back, and the answers worth keeping become Markdown notes — filed into a vault that is a folder on your own disk.

A vault is a directory holding base.md, a generated table of contents up to six levels deep, and a notes/ folder with one .md file per note. Before a note is written it is checked against the ones already there, so the fourth note about the same idea gets merged instead of added. Links between notes are ordinary Markdown links to files that exist.

The model is never ours: you bring your own API key to one of seven providers — Anthropic, OpenAI, Gemini, Groq, OpenRouter, a local Ollama or your own server — and pay that provider directly. A question sends the table of contents plus at most five relevant notes within a 24,000-character budget, and the app shows you which five it used.

Every answer kept this way becomes one of these ai notes, ready to search again months later without hunting back through old chats.

Side by side

Where they differ

• Both mention AI. The difference is whose key it runs on: SumizAI never resells inference — you connect one of seven providers (Anthropic, OpenAI, Gemini, Groq, OpenRouter, a local Ollama or your own server) with your own API key and pay that provider directly. Check what Hjarni does with the model bill before comparing prices.
• Hjarni is freemium: there is a free tier and a paid one, and the line between them is the thing to read before committing. SumizAI has one plan at a dollar a month, so there is no feature held back for a higher tier — and an unpaid account still opens and exports every vault it already has.
• AlternativeTo's description of Hjarni does not mention Markdown, so check what format your notes end up in before you fill it up. SumizAI writes standard .md files to a folder you picked, and an unpaid account can still export all of them.
• Hjarni runs in the browser. SumizAI is a desktop and mobile application, and on the desktop the vault is a folder on your own disk rather than a document in someone's cloud.
• Both are run from the EU: SumizAI's operator is registered in Poland and the servers are in Germany.

Which one to pick