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XRP Ledger Gets x402 Facilitator For AI Agent Payments: Why This Is Bullish
newsbtc53d ago

XRP Ledger Gets x402 Facilitator For AI Agent Payments: Why This Is Bullish

t54.ai has launched an x402 “facilitator” on the XRP Ledger (XRPL), a payments relay that lets AI agents pay for API calls and digital services in-line with normal HTTP requests using XRP or RLUSD. The pitch is simple: turn pay-per-request into a native part of the web stack, no accounts, no API keys, and settlement that happens on-chain. AI Agents Can Now Pay Via XRP Ledger The release plugs XRPL into x402, an open payments standard built around the long-reserved HTTP status code 402 Payment Required. In an x402 flow, a client requests a resource, the server replies with a 402 and machine-readable payment requirements, and the client retries the request with proof of payment. Coinbase’s x402 documentation frames the goal as programmatic access “without accounts, sessions, or complex authentication,” so both humans and autonomous agents can pay for usage-based services directly over HTTP. Related Reading: The 200 Million XRP Exodus: Investors Swap Speculation For Private Custody On X, t54.ai described the facilitator as “now live on the XRPL,” adding that agents can pay with “XRP and RLUSD – no API keys, no accounts, no friction.” Another post positioned x402 as “the open standard for machine-native payments,” where the server responds with HTTP 402 “Payment Required” and the agent pays immediately, with the facilitator handling verification and settlement on-chain. Popular XRP community account BankXRP wrote via X: “t54ai just launched the x402 facilitator AI agents can now pay for API calls and services with frictionless $XRP or $RLUSD micropayments using the HTTP 402 standard. No API keys. No accounts. Instant, sub-cent fees. Real machine-to-machine economy on the fastest, most scalable ledger in crypto.” t54’s XRPL deployment is designed to be “plug and play,” emphasizing no custody and no API keys. The public documentation for the XRPL x402 facilitator says it processes x402 payments on XRPL using payer-signed presigned Payment transaction blobs, and supports XRP plus IOU tokens including RLUSD (and USDC). Resource servers verify and settle by calling standard facilitator endpoints like /verify and /settle, mirroring the core x402 architecture where the facilitator is the chain-aware component that validates payment payloads and executes settlement. Related Reading: This Korean XRP Exchange Data Has The Community Losing It t54.ai also claims the system is already “in production” with BlockRunAI, a unified gateway that provides agents access to “30+ models (GPT, Claude, Grok, etc.).” In that integration, agents pay per request via x402, and the resulting payment volume “is now settling on XRPL,” effectively turning model inference and tool calls into metered on-chain commerce. Why This Is Bullish For XRP The “bullish” framing here isn’t about a single partnership logo, it’s about inserting XRPL into a broader emerging standard for agent-native commerce. x402 is explicitly designed to be network-agnostic, but in practice, standards only become real once developers can ship them with minimal ceremony. A working facilitator on XRPL means one more credible rail for high-frequency, low-value payments where the unit economics break traditional billing. It also cleanly links XRPL’s identity—fast settlement and low fees—to a use case that’s structurally growing: autonomous software paying other software. x402’s ecosystem pages and docs emphasize pay-per-use pricing and minimal integration overhead; that aligns with agent workflows where “thousands of API calls” and tool invocations need granular billing rather than subscriptions. None of this guarantees meaningful volume. But it does make the path to volume legible: more x402-enabled endpoints, more agent clients, and more facilitators that can clear payments cheaply and predictably. At press time, XRP traded at $1.4126. sd Featured image created with DALL.E, chart from TradingView.com

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India unveils Bharatiya GPT at AI Summit, blending ancient wisdom with artificial intelligence
organiser53d ago

India unveils Bharatiya GPT at AI Summit, blending ancient wisdom with artificial intelligence

At the AI Summit in India, the spotlight shifted from global technological discourse to a powerful idea rooted in India’s civilizational legacy: large language models (LLMs) were built from India’s own ancient manuscripts. During a thought-provoking conversation between Dhairya Maheshwari of Sputnik India and R. Ramakrishnan, founder of BharatiyaGPT, a unique vision for India’s technological future emerged. In today’s world, most large language models are trained mainly on Western data. Indian innovators asked a powerful question: what if the future of AI could also learn from India’s centuries-old knowledge in fields like science, medicine, mathematics, philosophy, and life sciences? This philosophy gave rise to a pioneering initiative i.e., an India-centric LLM ecosystem, built from the ground up on the treasures of Indian wisdom preserved in over one crore (10 million+) ancient manuscripts that are written across forty-plus distinct scripts and spanning multiple domains. The journey is not just technological, but cultural, scientific, and historical. 🚨This is what everyone should talk about AI India Summit not one off incident of Galgotia Bharat has successfully made LLMs scanning Lacs of Ancient Manuscripts ❗️ •Ancient Medicine & Surgery•Ancient Mathematics •Ancient Sciences •Ancient Ayurveda pic.twitter.com/JUnrOXuAal — RapperPandit (@RapperPandit) February 18, 2026 While developing “Immverse AI,” the team realised that merely adapting western datasets would never capture India’s intellectual heritage. The solution? Create Bharatiya LLMs i.e., language models trained explicitly on Indian manuscript literature across disciplines. This initiative will make knowledge easily available to everyone. Knowledge that was earlier limited to libraries, archives, or a few scholars. Also Read: Deepfakes pose serious risk to democratic discourse: Lok Sabha Speaker OM Birla Introducing the Bharatiya GPT Family At the summit, the launch of Bharatiya GPT marked a new chapter in AI innovation. Unlike generic AI models, this variant is deeply rooted in indigenous sources. It is paired with a bouquet of smaller, domain-focused Large Language Models (SLMs) each tailored for a specific field of ancient Indian expertise. A few of the highlights: Ayurveda, one of the world’s oldest medical systems, finds new expression through Lok Swasti GPT. Built from six principal Sanskrit manuscripts: Ashtanga Hridayam, Sushrut Samhita, Charaka Samhita and others, this model offers detailed insights into ancient medicine and surgery, health maintenance, and wellness systems that have endured for millennia. Built on foundational text such as Aryabhatiya, Lilavati, and Bija Ganitam, Ganit GPT revives classical Indian mathematics. Concepts from algebra, trigonometry, number theory, and computational insights from ancient scholars like Aryabhata and Bhaskara are now accessible with modern clarity. Leveraging Kautilya’s Arthashastra, one of the most advanced treatises on economics, statecraft, governance, and strategic management, this model brings ancient political and economic theory into conversation with present-day challenges. A philosophical guidebook that influences spirituality and life management, Bhagavad Gita GPT allows users to explore the text’s verses, context, and layered meanings interactively. It combines spiritual depth with analytical clarity. Other Important Tools Other remarkable models include exploration tools based on Gandha Shastra, i.e., ancient Indian perfumery and aromatic science, dating back to the Rigveda, and specialised insights drawn from the Ramayana and the Mahabharata. These models not only return accurate verses (shlokas) in response to queries but also help interpret them with contextual explanations grounded in the original manuscripts. What makes these models transformative is not merely text retrieval. Ask a question, and you don’t just get a paraphrased answer; you receive the original shlok, its underlying meaning, explanation, and conceptual linkage within the scripture. This is AI that respects context, respects tradition, and respects knowledge as science rather than mythology. Importantly, this initiative highlights that India’s ancient texts were not merely religious or devotional writings, but scientific documents that are highly systematic, empirical, and closely linked to real-world sciences. Using AI, these texts are being decoded for learners, researchers, educators, and curious minds across the world, not just within India. At the AI Summit, the message was clear: this is not just innovation for India, it is innovation for the world. By infusing AI with Indian scholarly heritage, these models are democratising knowledge that might otherwise remain locked in libraries, understood only by specialists, or lost in translation over centuries. Young generations who grew up learning about Ayurveda, mathematics, governance, and philosophy in fragments will now be able to interact with a living repository of ancestral intelligence with AI as the bridge.

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