Press Release
WarRin Protocol: A point-to-point anonymous privacy communication system
Dr.WarRin
Summary
This white paper provides an explanation of the WarRin protocol and related blockchain, point-to-point, network value, transport protocol, and encryption algorithms. The limited space will highlight the WRC allocation scheme and purpose of the WarRin Protocol Token, which is important for achieving the WRC’s stated objectives. This white paper is for informational purposes only and is not a promise of final implementation details. Some details may change during the development and testing phases.
1. Introduction
Traditional centralized communication systems such as WeChat,WhatsApp, FacebookMessage,Google Allo,Skype face a range of problems, including government surveillance, privacy breaches, and inadequate security, and the WarRin protocol proposes apoint-to-pointencrypted communications system that leveragesblockchain technology, combined with Double Ratc het algorithms, pre-keys, and extended X3DH handshakes. The WarRin Protocol uses The Generalized Directional Acyclic Graph and Curve25519,AES-256, and HMAC-SHA256 as the pronamor, allowing each account to have its own unique account chain, providing unlimited instant communication between points and unlimited scalability, anonymity, integrity, consistency, and asynchronousness.
2. WarRin Protocol communication system
2.1 Two types of communication
The Waring Protocol communication system divides chat channels into two types.
Two modes of communication
- General Chat mode: Using point-to-point encrypted communication, the service side has access to the key and can log in via multiple devices.
- Secret Chat mode: Encrypted communication using point-to-point can only be accessed through two specific devices.
The design combines some of the advantages of raiBlocks multi-chain construction with IOTA/Byteball DAG, which we call the Waring protocol. With improvements, we have given the WarRin protocol greater throughput and faster processing power while ensuring the security of the ledger, and network nodes can store the ledger in less space and search their communications accounts quickly in the ledger. When two users communicate, third parties contain content that neither manager can access. When a user is chatting in secret, the message contains multimedia that can be designated as a self-destruct message, and when the message is read by the user, the message is automatically destroyed within the specified time. Once the message expires, it disappears on the user’s device.
2.2 How chat history is encrypted
2.2.1 MTProto Transport Protocol
MTProto transport protocol
The WarRin communication system draws on RaiBlocks’ multi-chain structure for point-to-point communication. Each account has its own chain that records the sending and receiving behavior of the account. For example, in Figure 1, there are 7 accounts, each with 7 chain records of the account sending and receiving communications. On the graph, horizontal coordinates represent the timeline, and portrait coordinates represent the index of the account.
Transferring information from one account to another requires two transactions: one to send a communication from the sender’s transfer content, and one to receive information to add that content to the content of the receiving account. Whether in a send-side account or a receiving account, a PoW proof of work with the previous communication content Hash is required to add new communications to the account. In the account chain, poWwork proves to be an anti-spam communication tool that can be done in seconds. In a single account chain, the Hash field of the previous block is known to pre-generate the PoW required for subsequent blocks. Therefore, as long as the time between the two communications is greater than the time required to generate the PoW, the user’s transaction will be completed instantaneously.
In such a design, only the receiving end of the communication is required for settlement. The receiving end places the received communication signature on the account chain, which is called accepted communication. Once accepted, the receiving end then broadcasts the communication to the ledger of the other nodes. However, there may be situations where the receiving end is not online or is subject to a DoS attack, which prevents the receiving end from putting the receiving side communication on the account chain, which we call uncommoted transactions. The X symbol in Figure 1 represents an open transaction sent from Account 2 to Account 5.
Obviously, because only the sending and receiving sides of the communication are required to settle, such communication is very lightweight, all traffic can be transmitted in a UDP package and processed very quickly. At the same time, all communications in an account are kept in one chain, with great integrity, and the ledger can be trimmed to a minimum. Some nodes are not interested in spending resources to store the full communication history of the account; They are only interested in the current communications for each account. When an account communicates, its accumulated information is encoded, and these nodes only need to keep track of the latest blocks so that historical data can be discarded while maintaining correctness. Such communication is only possible if the sending and receiving sides trust each other and are not the final settlement of the entire network consensus. There is a security risk in the absence of trust on the sending and receiving ends, or in situations where the receiving end is attacked by DoS without the sender’s knowledge.
We have observed that although each account has a separate chain, the entire ledger can be expressed in the form of a WarRin object. As shown in Figure 2, this is represented by the WarRin astros trading on all accounts in Figure 1.
The first unit in the WarRin object is the Genesis unit, the next six cells represent the allocation of the initial token, and the other units correspond to the communication transactions between the account chains. We use the symbol a/b to represent a communication transaction, where the sender is a andthe recipient is b. The last 4/1 unit in Figure 2 is the last communication corresponding to Figure 1 – sending communication from account 4 to account 1. A transaction in Figure 1 is a confirmation of the latest block or the latest communication on the account chains of both parties to the communication, reflected in Figure 2 as a reference to the latest units of the account chains of both parties to the communication. Take unit 4/1, for example, where the latest block on account 4 was the receiving block for 2/4 trades and the newest block on account 1 was the send block for 1/5 trade. So on the DAG, the 4/1 cell refers to the 2/4 cell and the 1/5 cell.
The WarRin protocol uses triangular shrapned storage technology to crack impossible triangles in the blockchain through the shrapghine technology, with extensive node engagement and decontalination while maintaining high throughput and security:
- Complete shraping of blockchain status;
- Secure and low-cost cross-synth trading;
- Completely random witness selection;
- Flexible and efficient configuration
Complete decentralization ensures absolute security and scalability of the standard chain.
(Figures above show seven Ling-shaped objects:2/1 one;3/2 one… ）
2.2.2 Curve25519 Elliptic Curve Encryption Algorithm
Curve25519, proposed by Daniel Bernstein, is anelliptic curve algorithm for the exchange of The Montgomery Curve’s Difi Herman keys.
Montgomery Curve Curve Mathematical Expression:
Curve25519 Curve Mathematical Expression:
Curve25519 encryption algorithms are 
Generate a one-time random secret 
3. Incentives
On the basis of the WarRin agreement, by adding the incentive layer, we can effectively avoid the whole network being attacked and eliminate spam. As long as honest nodes control most of the calculations, for an attacker, the network is robust because of its simplicity of structure, and nodes need little coordination to work at the same time. They do not need to be authenticated because information is not sent to a location.
3.1 WRC Certificate
WRC issued a total of 2,500,000 pieces and continued to increment according to the WoRin gain function.
3.1.1 WoRin Gain Function
3.1.2 WoRin gain function control table
| The WoRin gain function is compared to the table | ||
| Number of layers /F | Growth factor /I | WRC circulation |
| [1,50] | 0.002 | 334918.8057 |
| [51,100] | 0.002 | 780024.2108 |
| [101,150] | 0.004 | 1177129.617 |
| [151,200] | 0.006 | 1487860.923 |
| [201,250] | 0.01 | 1722637 |
| [251,300] | 0.016 | 1894309.216 |
| [301,400] | 0.03 | 2101623.789 |
| [401,500] | 0.06 | 2217555.464 |
| [501,1000] | 0.1 | 2450712.257 |
| [1001,2000] | 0.12 | 2557457.3 |
According 
3.2 Allocation
WarRin protocol node distribution
3.2.1 Node allocation
Set the initial price 
For example, the number of tiers in which the 98th node is located is Tier 13, and the price of Tier 13 is 0.214,the tokens assigned by Tier 98 are
3.2.2 Total number of address assignments
Each node occupies one address, and the total number of 
4. The use
WRC is the native pass-through of the WarRin protocol, andWRC will assign to Genesis nodes according to the above allocation scheme, which together form the entire network, andWRC can be used in the following scenarios, including but not limited to:
Pay the network’s gas charges, i.e. for transferring money and invoking smart contracts;
System Staking tokens, used for node elections and token issues;
The capital is lent to the validator in exchange for the amount of the reward;
Voting rights for system proposals;
The means of payment for apps developed on WoRin Services;
WoRin Storage is a means of payment on the decentralization storage;
WoRin DNS domain name and WoRin WWW website means of payment;
WoRin Proxy agents hide the means of payment for body and IP addresses;
WoRin Proxy penetrates payment methods reviewed by local ISPs
……
5. Conclusions
Metcalfe’s Law states that thevalue of a network is equal to the square of the number of nodes within the network, and that the value of the network is directly related to the square of the number of connected users. That is 
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About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Alpharetta, Georgia, November 9th, 2026, ZEX PR WIRE,
As businesses move from AI experiments to systems that can take action, global technology executive Eric Kalin says the data beneath them deserves more attention.
Businesses are moving quickly from experimenting with generative artificial intelligence to exploring agentic systems that can participate in workflows and take action. Eric Kalin believes that shift is making an older enterprise challenge newly important: understanding the data those systems rely on.
After years of cloud adoption, application growth, system changes, and business expansion, enterprise information rarely sits neatly in one place. It can be spread across departments, databases, older systems, and multiple cloud environments. Some information may be current and well managed. Other data may be duplicated, outdated, difficult to access, or subject to different security requirements.
For Kalin, that means the conversation about AI readiness increasingly needs to become a conversation about data readiness.
“There is a tendency to start with what the AI can do,” Kalin said. “I think you also have to ask what you’re giving it to work with. Where did that information come from? Can you trust it? Is the system supposed to have access to it? Those questions become even more important when AI moves from generating an answer to taking an action.” Kalin has more than 25 years of experience across enterprise technology, cloud computing, data, consulting, sales, and business transformation. His career includes leadership roles at IBM, Accenture, Amazon Web Services, Microsoft, and Oracle. That experience has allowed him to see how enterprise technology environments have become more powerful while also becoming more complex.
Having More Data Does Not Mean Being Ready for AI
Organizations today can collect and retain enormous amounts of information. Kalin argues that volume alone says little about whether that information can support an AI application.
“Having more data doesn’t make you more ready for AI,” Kalin said. “Understanding your data does.” Before scaling an AI initiative, organizations may need to determine where relevant information is stored, how current it is, whether different systems agree with one another, and who is responsible for maintaining it.
The challenge becomes particularly important when information about the same customer, product, transaction, or business process exists in several places.
A sales team, for example, may work from one set of customer information while finance and operations rely on different systems. Each system may serve its purpose well, but an AI application attempting to work across the organization may encounter conflicting or incomplete information.
Kalin believes these situations illustrate why AI cannot be separated from the wider technology environment in which it operates.
Multicloud Environments Add Another Layer
The growth of cloud computing has given businesses greater flexibility in how they build and operate technology. It has also contributed to environments where applications and data may be distributed across different platforms.
For organizations operating across multiple clouds, the challenge is not necessarily to bring every piece of information into one location. It is to understand how information moves, which systems should be able to use it, and what controls need to follow it.
Kalin’s career has included extensive experience with cloud technology and global enterprise customers. He believes the same practical thinking that became important as cloud adoption matured is now becoming relevant to AI.
“Eventually, every major technology conversation gets more practical,” Kalin said. “You move from asking what is possible to asking how it actually works inside your organization. With AI, data is a big part of that second question.” That includes understanding which information matters for a particular AI application, rather than assuming every available source needs to be connected.
Agentic AI Raises the Stakes
Data quality and access already matter when generative AI is being used to summarize information, answer questions, or assist employees. Agentic AI adds another consideration because systems may increasingly participate in workflows and take action.
“With generative AI, you might be concerned about an inaccurate answer,” Kalin said. “With an agent participating in a workflow, you also have to think about what happens after that answer. What can the system access? What is it allowed to change? When does a person need to approve an action? The data and governance questions become very practical very quickly.” This is where security, permissions, and ownership become closely connected to data quality.
Making information available to AI does not mean making everything available without restriction. Organizations still need to determine who owns sensitive information, which systems can access it, and where human review remains necessary.
Kalin believes those decisions should involve more than technology teams alone. Business leaders often understand how information is actually used. Security teams understand the risks surrounding access. Data teams understand quality and structure. Bringing those perspectives together can help uncover problems before an AI application is widely deployed.
Perfect Data Is Not the Goal
Kalin also cautions against interpreting data readiness as a requirement to solve every information problem before experimenting with AI.
Few large organizations have perfectly organized data. Waiting for perfection can create its own barriers to progress.
Instead, early AI projects can help businesses identify which data issues actually matter for a specific use case.
“You don’t need to fix every piece of data in the company before you start,” Kalin said. “You need to understand the data that matters for what you’re trying to accomplish. Start there, learn from it, and build from what you find.” That approach keeps the focus on a defined business need rather than attempting a massive data project with no clear connection to an outcome.
As companies move from AI experimentation toward broader use of generative and agentic systems, Kalin expects questions about data quality, access, security, and governance to become harder to separate from the AI conversation itself.
The organizations with the largest amounts of information will not automatically be the ones best positioned to use AI effectively. Understanding what that information means, where it lives, how reliable it is, and how to use it responsibly may prove just as important as the AI technology placed on top of it.
Eric Kalin is a global business leader and technology executive with more than 25 years of experience across enterprise technology, cloud computing, data, artificial intelligence, consulting, sales, and business transformation. His career includes leadership roles at Oracle, Microsoft, Amazon Web Services, Accenture, and IBM. Based in Alpharetta, Georgia, Kalin has worked with global organizations and cross-functional teams throughout major periods of change in enterprise technology. His interests include data platforms, generative and agentic AI, multicloud environments, business strategy, and the connection between emerging technology and practical business needs.
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Claremore, OK, USA – November 9th, 2026, ZEX PR WIRE – Chad Choat has spent decades inside the home health industry in Oklahoma, first joining the family business in 1995 and later buying it from his mother in 2010. In that time, he has watched families make a hard decision under pressure, often right after a hospital discharge, with little time to compare providers.
“Most families are not trying to cut corners,” Choat says. “They are tired, scared, and doing this for the first time. They take the first name a discharge planner hands them.”
He says that rush is understandable. It is also where a few warning signs get overlooked.
Oklahoma requires a licensed administrator to run a home care agency. Choat holds that license himself and says it is the first thing a family should ask about, not the last.
“If an agency cannot tell you plainly who their licensed administrator is, that is worth pausing on,” he says. “It is a simple question. It should have a simple answer.”
Community Home Health runs on a fully integrated electronic medical record system. Choat says that matters less for the technology itself and more for what it prevents: a nurse, a doctor, and a family member working off different versions of the same patient’s care.
“When an agency still runs on paper charts and phone tag, information gets lost between visits,” he says. “Families should ask how the agency keeps everyone on the same page, not just whether someone shows up on schedule.”
Medicare tracks outcomes across home health agencies nationally, and Choat points to that as a tool families rarely use. Community Home Health is ranked in the top 1 percent of agencies in the country by that measure, and he says any agency should be able to point to where it stands.
“Ask how an agency’s outcomes compare to others, not just how they describe themselves,” Choat says. “Medicare publishes that data. A family does not have to take anyone’s word for it.”
Choat says the clearest sign of trouble is often the quietest one: a family that only hears from an agency when something goes wrong.
“Care should not feel like a black box,” he says. “If weeks go by and nobody has called to check in, that is a sign the communication is not where it should be.”
He says this is also where he sees agencies lean on new tools the wrong way. Community Home Health has moved further into AI-based tools for scheduling and coordination, but Choat is clear that technology is meant to free up time for people, not replace the conversation.
“A tool should make it easier for a nurse to call a family back faster,” he says. “If it is doing the opposite, something is backwards.”
Choat’s advice to families comes down to a short list of direct questions: who is the licensed administrator, how does the agency track and share records, how do its outcomes compare nationally, and how often will someone actually call.
“None of these are complicated questions,” he says. “But they are the ones that tell you the most.”
He says families who ask them early tend to have an easier time later, when care decisions often have to happen fast.
To read more, visit the website here.
Chad Choat is the owner and president of Community Home Health, based in Claremore, Oklahoma. He joined the company in 1995 and purchased it from his mother, the company’s founder, in 2010. He holds a state-issued license as a home care administrator and previously taught high school vocational agriculture. Choat also served on the Claremore City Council from 1998 to 2003 and has been involved in statewide political campaigns across Oklahoma.
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Altegio Announces Open Platform Connecting Beauty and Wellness Businesses With AI Agents at Web Summit 2026
Budapest, Hungary, November 9th, 2026, FinanceWire
At Web Summit 2026 in Lisbon, taking place November 9–12, Altegio will announce the launch of its new open platform designed to connect beauty and wellness businesses with AI assistants and enable the development of custom AI agents, integrations, and tools built on business data. The announcement marks the introduction of a platform that brings together AI connectivity and developer infrastructure for the beauty and wellness sector.
The role of SaaS is changing
AI assistants are becoming a common tool in everyday work. To provide truly useful answers and support business operations, however, they need access to a company’s own data. A beauty salon, for example, stores this data in its management system covering bookings, visit history, payments, salaries and inventory levels.
This is changing the role of software as a service (SaaS) products like Altegio. Once used primarily by front-desk staff, these products are now becoming systems of record that hold all the key information about a business and connect to AI agents and partner services.
Altegio handles 5.5 million bookings every month. Companies on the platform generate a combined turnover of over €100 mln a month, and more than 100,000 specialists access it every day. All this activity generates millions of records that feed into analytics and reports. This real business data can now be available to the user’s AI assistant and partner integrations, but only within the limits set by the business owner.
Explore business data with a familiar AI assistant
Altegio’s MCP servers are built on the Model Context Protocol (MCP), an open standard that lets AI assistants connect to external services. As a result, business owners no longer need to spend time looking for a specific report or setting up data filters. Instead, they can find the relevant data by asking the assistant simple questions:
– “Which clients haven’t visited in over 90 days?” The assistant uses visit history to build a list of those clients for the next marketing message.
– “Move Anna’s appointment to 3 p.m. with Maria.” The assistant checks the booking calendar for an available time slot and suggests the change.
– “How did revenue change this month, and which services grew?” The assistant compares the two periods and breaks revenue down by service and by employee.
Setup takes three steps, with no coding required. Just copy the connection address, add it to your assistant as a custom connector and approve access in your browser. Available features vary by assistant and subscription plan. Assistants with voice support also let users ask questions aloud. In ChatGPT, for example, voice commands use the same MCP connection.
Six MCP apps for different tasks:
- Altegio Pro MCP: Manage bookings, staff, services, work schedules, clients and location settings.
- Altegio Pro MCP (read-only): Receive analytics and answers about the business without being able to change anything. This suits professionals who need to view information but not edit it, such as a consultant, a receptionist or an accountant.
- Altegio Analytics Agent: Get answers about revenue, clients and team workload inside Altegio itself.
- Altegio Knowledge MCP: Ask questions in plain language and get straightforward answers from Altegio’s official help center, with links to relevant articles.
- Altegio Integrations Hub MCP (for developers): Plan, build and test an Altegio integration from Cursor or Claude Code. Develop your own add-ons and applications that can be sold to and used by Altegio’s client base of over 14,000 businesses.
- Altegio.me MCP (for customers): Find an available time slot, book, reschedule or cancel a visit in one chat with your favorite AI assistant, by typing or by voice.
“A salon owner doesn’t need another dashboard. They need answers to their questions. MCP delivers those answers today, and API v3 lets partners build the next layer on top of Altegio’s data. We believe business data belongs to the business: the more tools that can work with it, the more value the owner gets,” says Yri Petrou, CEO and co-founder of Altegio.
You stay in control of your data
The assistant can only see and change what the user’s Altegio account has permission to access. Permissions to read, write and delete are set separately. Before saving any change, the assistant asks the user to confirm it. Altegio runs on Hetzner data centers in Germany and meets GDPR requirements.
What partners and developers get
Altegio’s open API supports more than 200 methods and over 100 integrations in the Altegio Marketplace run on it. Business Management API v3 (currently in early access) is designed with AI agents in mind:
- Personal API keys for custom solutions and third-party applications. Each key acts on behalf of the user who created it and has that user’s current permissions. If an employee’s access is revoked, their key loses access too.
- Password-free authorization, so partner apps never receive the user’s Altegio password.
- Consistent terminology for key data entities (location, employee, service, client, booking, visit) ensures that developers and AI agents interpret the data consistently.
- Integrations Hub MCP helps developers turn an idea into a working tool directly inside an AI assistant. Developers can plan the integration, create an app and test it on their own test account.
At Web Summit 2026, the Altegio team will show how business owners can manage bookings and analytics through an AI assistant.
More about MCP apps: alteg.io/en/mcp
API documentation: developer.alteg.io
About Altegio
Altegio is a European holding company and a business management platform for appointment-based service companies. It offers an all-in-one platform for online booking, appointment scheduling, customer records, loyalty programs, financial management, payroll and inventory management. Its open API and MCP servers enable businesses to use their own AI agents to access their companies’ data.
More than 14,000 companies across over 90 countries rely on Altegio, and over 100,000 professionals use the platform every day. The team of over 130 people operates from seven offices across the EU, the UAE, Latin America and Central Asia.
Altegio was founded in 2022 and is headquartered in Budapest.
Press contacts:
Website: https://alteg.io/
Public relations contact: marketing@alteg.io
Contact
CMO
Andrei Kuzniatsou
altegio
marketing@alteg.io
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
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