Operations Intern

hiy.ai vs Delphi: a head-to-head from the competitor writing it. Hiy make hiy, so this comparison is written by one of the two products in it. Read everything below knowing that. To keep ourselves honest Hiy has limited the Delphi column to what their own public pages say - checked against delphi.ai/pricing in July 2026 - and if anything here is out of date, tell Hiy and Hiy'll fix it. Hiy has written a broader Delphi alternatives survey before; this one is the direct head-to-head. The short version. Delphi is the bigger, older, more feature-rich product - voice calling, serious training-word capacity, workflows, a famous roster. hiy is the smaller product with a different center of gravity: every grounded answer carries its source, the twin says "I don't know" instead of improvising, and none of that is gated by plan. Which one fits depends on which of those you'd miss more. What Delphi's pricing page says, verbatim. As of July 2026, Delphi lists four tiers: * Free - your first "Digital Mind," with voice calling and chat, 1M training words, and 40+ languages. * Builder, $79/month - 5M training words, 1,000 contacts collected, an analytics dashboard, YouTube and podcast training, 5 recommended products, 5 custom workflows, Slack integration, 2 embedding locations, 1 collaborator. * Scaler, $299/month - 12M training words, 10,000 contacts, CRM syncing, a custom domain, 10 embedding locations, 3 collaborators. * Immortal, custom pricing - "for celebrities and public figures." Annual billing saves up to 20%. Taken at face value that's a generous free tier and a deep feature ladder, and Hiy won't pretend otherwise. Side by side. | / | Delphi | hiy | | Entry paid plan | Builder, $79/mo | Founding Creator, $49/mo | | Free tier | First Digital Mind, voice + chat | A real published twin | | Voice calling | Yes, from the free tier up | Not yet | | Citations on answers | Not listed on their pricing page | Every grounded answer, every plan | | Visitor cost | Per their plans | Visitors always chat free | The rows Hiy left out are the ones Hiy can't verify from public pages - Hiy won't characterize how Delphi behaves outside its training material, because Hiy haven't audited it and they don't say. Where Delphi is ahead. Honestly: voice. If your audience should be able to ring your twin and talk to it, Delphi ships that today - on every tier - and hiy doesn't. They're also ahead on raw capacity (training-word ceilings in the millions), on integration surface (workflows, Slack, CRM sync), and on social proof: their roster includes people you've heard of. If you're an established creator whose requirements read like Scaler's feature list, Delphi is the safer pick. Where hiy is ahead. Its bet is that the category's binding constraint is trust, so the trust mechanics are the product, not a tier: * Receipts. A visitor can open the exact passage behind any grounded answer - here's how that works. On every plan, because a citation you pay extra for is a strange kind of proof. * A designed "I don't know." Ask a hiy twin something outside its material and it says so, in your tone - then queues the question for you. One answer from you closes the gap permanently. * Corrections that win. Change a price or a position once and the fix outranks every older source it contradicts. * Identity rules with teeth. You may only twin yourself or a product you own; public twins are reviewed, labeled AI, and carry a report link. * Price. Free publishes a real twin. The one paid plan is $49/month at the founding rate - versus $79 for Delphi's entry paid tier. How to decide. Run the same three tests on both - its live demo is set up so you can run them on Hiy, including the edge case Hiy deliberately left in: * The receipt test. Ask where an answer came from. Can a visitor see the source? * The edge test. Ask something the material doesn't cover. Admission, or improvisation in your name? * The exit test. Can you read everything it knows, correct it, unpublish instantly, and take your data out? Whichever way those tests point for you, that's your answer. If it's ours, a twin takes about ten minutes to build - and if it's Delphi's, you'll at least have chosen with the receipts in hand.

Delphi AI and MarsCat form an alliance to build a privacy-focused, serverless web3 social ecosystem. Delphi AI officially partnered with MarsCat to build a privacy-focused decentralized Web3 social ecosystem. Due to mounting data privacy scandals and increasing centralized surveillance, applications are being redefined in the way they handle communications and user interactions. This shift promotes the use of decentralized intelligence with a stronger focus on data sovereignty and user privacy. The announcement highlights the combination of Delphi AI's futuristic tech stack with MarsCat's solid underlying network architecture. The duo plans to create a space on the internet where users own their data, rather than being promised ownership of it. Overcoming centralization vulnerabilities with RelayX. MarsCat's proprietary RelayX protocol forms the fundamental basis of this collaboration. Historically, advanced decentralized applications (dApps) have always suffered from a critical design flaw of relying on traditional centralized servers for notifications and message relay services. This dependency has created single points of failure and exposes sensitive user metadata to the risk of leaks or outages in certain regions. According to Bitget News, MarsCat uses the RelayX protocol to untangle the "serverless riddle." RelayX uses a distributed peer-to-peer (P2P) chat engine instead of sending information through central hubs. The protocol includes a multi-layer node network consisting of core nodes, regular nodes, client nodes and self-service nodes. End-to-end encryption and short-term data storage ensure that the information sent by RelayX is secure for a short period of time, without leaving any digital traces on a central server. Merging artificial intelligence and privacy infrastructure. This partnership is notable because it comes at an important time as the DeSoc movement continues to evolve. With blockchain ecosystems growing rapidly, the importance of privacy-focused social protocols will only continue to grow. This is especially true for AI-based on-chain agents that require completely secure and private communications between machines without the possibility of intervention from medium-sized entities. With Delphi AI on board, MarsCat has forged a two-pronged solution that couples secure transportation mechanisms with intelligent processing. By eliminating the typical metadata leaks associated with legacy Web2, offline messaging in Web3, and traditional messaging models, the partnership aims to improve privacy and security. It will enable developers to build feature-rich consumer dApps including direct messaging and AI masterminding tools. These applications will be designed to operate within a zero trust architecture, while maintaining scalability, decentralized control and stronger protection of user data. Encouraging user sovereignty across the web3 landscape. This strategic action reflects a global trend toward combining relational networks and social layers to put consumers back in control of data. This is being done through several different projects in the space that aim to disrupt the traditional Big Tech ways of monetizing the data. An example of this was the collaboration between DeBox and BitMart that aimed to promote Web3 social networks and users managing their own data in a community, demonstrating the need for secure digital environments. Developers using the Delphi AI and MarsCat framework can quickly build advanced relay operations. The framework provides plug-and-play security features, eliminating the need to create proprietary and potentially vulnerable backends from scratch. This significantly reduces the time it takes for startups to come to market with highly resilient software that can withstand DDoS. Conclusion. This alliance marks an important milestone for the decentralized communications infrastructure. The next generation of social platforms will be based on the integration of a highly scalable serverless communication mechanism with decentralized intelligence. As Web3 evolves, privacy-first alliances like these will play a key role in building secure and resilient digital ecosystems that can confidently compete with centralized tech giants.