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December 28, 2023

Anytype is built on the open-source AnySync protocol: a local-first protocol based on CRDTs. Users of Anytype can create spaces - graph-based databases with modular UI. Each space has unique access rights. Today, Anytype's beta is in single-player mode. Multiplayer mode, which will support local-first collaboration between multiple users, will be launched in the first half of 2024.

Anytype fulfils the seven ideals of local first software from here - https://www.inkandswitch.com/local-first/ , our team felt these things are important to all of us:

• No spinners: your work at your fingertips. Anytype keeps the primary copy of each space on the local device. Data synchronization with other devices happens quietly in the background - allowing you to operate with your data at your fingertips.

• Your work is not trapped on one device. Users can easily work on different devices. Each device keeps data in local storage, synchronisation between devices happens in the background using CRDTs to resolve conflicts.

• The network is optional. Everything works offline. Data synchronization need not necessarily go via the Internet: AnySync allows users to sync data via local WiFi networks. Still, there is a role for the network - it works as additional backup, helps with peer discovery and especially solves the closed-laptop problem (you made changes on laptop, when your phone was offline, the changes can either sync when both devices are online or via backup node).

• Seamless collaboration with your colleagues. Achieving this goal is one of the biggest challenges in realizing local-first software, but we believe with CRDTs it's possible. AnySync supports it & we will release multiplayer version soon.

• The Long Now. Because you have a local-first application, you can use it on your computer even if the software author disappears. This is also strengthened by open data standards and open code.

• Security and privacy by default. AnySync uses end-to-end encryption so that backup nodes store encrypted data that they cannot read. Conflict resolution happens on-device. The keys are controlled by users.

• You retain ultimate ownership and control. Users control encryption keys; there is no central registry of users (we don’t ask even your email). We added an option to self-host your backup to support full autonomy of users from the network.

Comments URL: https://news.ycombinator.com/item?id=38794733

Points: 24

# Comments: 8



from Hacker News: Front Page https://anytype.io/
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December 06, 2023

Hi HN! I'm Nicolas, co-founder of Lume, a seed-stage startup (https://www.lume.ai/).

At Lume, we use AI to automatically transform your source data into any desired target schema in seconds, making onboarding client data or integrating with new systems take seconds rather than days or weeks. In other words, we use AI to automatically map data between any two data schemas, and output the transformed data to you.

We are live with customers and are just beginning to open up our product to more prospects. Although we do not have a sandbox yet, here is a video walkthrough of how the product works: https://www.loom.com/share/c651b9de5dc8436e91da96f88e7256ec?.... And, here is our documentation: https://docs.lume.ai. We would love to get you set up to test it, so please reach out.

Using Lume: we do not have self-serve yet. In the meantime, you can request full access to our API through the Request Access button in https://www.lume.ai. The form asks for quick information e.g. email so that I can reach out to you to onboard you. Please mention you came from HN and I’ll prioritize your request.

How our full API product offering works: Through Lume’s API, users can specify their source data and target schema. Lume’s engine, which includes AI and rule-based models, creates the desired transformation under the hood by producing the necessary logic, and returns the transformed data in the response.

We also support mapper deployment, which allows you to edit and save the AI generated mappers for important production use cases. This allows you to confidently reuse a static and deterministic mapper for your data pipelines.

Our clients have three primary use cases

- Ingest Client Data: Each client you work with handles data differently. They name, format, and handle their data in their own way, and it means you have to iteratively ingest each new client's data.

- Normalize data from unique data systems. To provide your business value, your team needs to connect to various data providers or handle legacy data. Creating pipelines from each one is time consuming, and things as small as column name differences between systems makes it burdensome to get started.

- Build and maintain data pipelines. Creating different pipelines to that map to your target schema, whether for BI tooling, downstream data processing, or other purposes, means you have to manually create and maintain these mappings between schemas.

We're still trying to figure out pricing so we don't have that on our website yet - sorry, but we wanted to share this even though it's still at an early stage.

We’d love your feedback, ideas & questions. Also, feel free to reach out to me directly at nicolas@lume.ai. Thank you.

Comments URL: https://news.ycombinator.com/item?id=38547033

Points: 14

# Comments: 0



from Hacker News: Front Page https://www.lume.ai/
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