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We just shipped the product we're most excited about since we launched Blaxel: Agent Drive. tl;dr: It’s a shared filesystem for AI agents. Mount it to multiple sandboxes at the same time, with concurrent read-write access. Write a file in one sandbox, read it from another. For agents, it becomes a shared memory layer that lives outside any individual sandbox. https://lnkd.in/eAUTf7Ms Here’s why we built it. Over the past year, we’ve worked with hundreds of teams running agents in production. The pattern keeps showing up. Once the harness and sandbox are solved, the next bottleneck is sharing context across runs. Teams end up building custom S3 or GCS export-and-import pipelines. Or they accept that every agent session starts from scratch. That means redundant token usage, slower resolution times, and engineering time spent on plumbing instead of product. Agent Drive removes that handoff layer. Agents share a filesystem the way teams share a Google Drive folder, except it is purpose-built for agentic workloads: - Small-to-medium files - High concurrency - Frequent reads and writes across multiple sandboxes Agent Drive is in private preview. If you are building multi-agent systems or agentic workflows that need shared context, I’d love to hear what your agents need to share. Docs: https://lnkd.in/eA_sa6d6

A channel is not a use case. A use case is a job, and banks have 20+ of them: customer support, KYC, fraud, disputes, invoice automation, outbound calls, and more. Running them as 20 separate vendor projects means 20 security reviews and no shared learning. On Blits.ai they run on one governed platform, with the same guardrails, audit trail and test suite.

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Humans research sequentially. Agents research in parallel. For decades the loop was manual: frame the question, search, skim, take notes, cross-check, draft, argue with yourself, repeat. It works. Attention is the bottleneck. Agentic LLM systems run that same loop, but at scale. They plan, fan out, read, extract, compare, draft, critique it, and re-query. Dozens of threads at once, all with tirelessness that’s hard to match. At Brightwave, our view is there’s no replacement for human judgement, and that the future of AI looks like experienced, thoughtful oversight of fleets of agents. Rather than manually grinding through huge document collections, your agents fan out and pursue a research plan in parallel, turning over every stone and connecting the dots so you can get to brass tacks faster. This isn’t some far-off vision of the future, Brightwave works like this already. Speed up your process by 25x. Try it today. https://lnkd.in/gHsuNTTs

Stop wasting hours on manual reviews. With Brightwave, you can work 150x faster than a human analyst and surface 20x more hidden risks. Spend less time crunching data and more time making an impact. Get access within minutes and start crunching data better than traditional consumer LLM's.

베스핀글로벌과 구글 클라우드가 주최하는 Game Night: Melt into Bespin 행사에 여러분을 초대합니다! 게임인 여러분들을 위한 네트워킹 파티와 각종 이벤트, 푸짐한 경품까지! G-star 2025의 금요일 밤을 알차게 즐겨보세요 🎉 🗓️ 일시: 2025년 11월 14일 (금) 18:30 ~ 23:00 📍 장소: Melt 부산(해운대) 🙆♂️ 대상: 게임 업계 임직원 ✅지금 신청하기 : https://lnkd.in/gdejQAYn

🚀반복 업무는 AI에게, 당신은 더 '크리에이티브'한 일에 집중하세요. 마케터의 데이터 분석부터 개발자의 시스템 모니터링까지. 이제 지시만 하면 스스로 계획하고 실행하는 AI Agent가 든든한 팀원으로 합류합니다. 베스핀글로벌이 마케팅·IT 부서의 업무를 획기적으로 줄여줄 핵심 비법을 공개합니다. ✅실무자가 꼭 봐야 할 E-book 핵심 내용: - Marketing: 타겟 분석부터 캠페인 실행까지 자동화하는 법 - IT/Dev: 에러 탐지 및 인프라 운영 자동화(AIOps) 실전 사례 - 내 업무에 바로 적용 가능한 AI Agent 시나리오 야근 없는 스마트한 워크플로우, 남들보다 먼저 경험하고 싶다면? 지금 바로 전략 리포트를 무료로 받아보세요.

Your SEC exam is in 47 days. Hapax already found 12 gaps.

Two-thirds of enterprise marketing teams sit at the transition between Fragmented and Integrated. The Lighthouse Method moves you forward in 90 days, against the BGS framework you already run.

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Your team has better things to do than wait on hold. AZcall helps handle phone menus, scheduling, and everyday calls so work keeps moving. See how AZcall works.

𝗪𝗵𝗲𝗻 𝘁𝗵𝗲 𝗵𝗲𝗮𝘁 𝗵𝗶𝘁𝘀 𝘁𝗵𝗲 𝗨𝗞, 𝗶𝘁 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗺𝗮𝗸𝗲 𝘂𝘀 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲. 𝗜𝘁 𝗮𝗳𝗳𝗲𝗰𝘁𝘀 𝗼𝘂𝗿 𝗳𝗮𝗺𝗶𝗹𝗶𝗲𝘀, 𝗼𝘂𝗿 𝗰𝗼𝗺𝗺𝘂𝘁𝗲𝘀, 𝗼𝘂𝗿 𝗵𝗲𝗮𝗹𝘁𝗵, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝘄𝗲 𝗿𝗲𝗹𝘆 𝗼𝗻. If you have teammates, friends, family, or customers in the UK, you've probably seen it already. The UK is resilient. People adapt. Teams keep going. But heatwaves reveal where the strain appears first, from transport and water to healthcare and energy. And this isn't just a UK story. With El Niño and climate change driving more frequent extreme weather, we're seeing the same patterns emerge around the world. That's why we built the Axonis Weather Intelligence Application for the UK and Ireland, powered by Axonis Decision Intelligence. It connects trusted public data to help people understand what changing weather could mean across: 🏥 NHS demand 💧 Water resources 🚆 Rail operations 🌾 Agriculture ⚡ Energy 🚰 Hosepipe restrictions We built it for ourselves, then realised it could help others too. Because this isn't just about spotting risk. It's about recognising patterns early and helping people stay one step ahead. Explore the Weather Intelligence Application: weatherimpact.ai We're grateful for the open, accessible public data across the UK and Europe, especially from: 🌦️ Weather & Climate Met Office (UK) World Meteorological Organization (WMO) Copernicus ECMWF (C3S) European Centre for Medium-Range Weather Forecasts - ECMWF NOAA: National Oceanic & Atmospheric Administration 🏛️ Public Sector NHS England Network Rail Environment Agency National Grid 🔬 Research & Climate The Alan Turing Institute Royal Meteorological Society (RMetS) And a special thanks to BBC News and The Guardian for their reporting, which also contributed to the insights used by ADI.

𝗔𝗜 𝘀𝗵𝗼𝘂𝗹𝗱𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗮𝗻𝘀𝘄𝗲𝗿 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀. 𝗜𝘁 𝘀𝗵𝗼𝘂𝗹𝗱 𝗱𝗼 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸. AZcall makes task-driven phone calls, navigates phone trees, waits on hold, and works toward an outcome so employees can stay focused on their jobs.

200 E-Mails täglich im Postfach des Einkaufs. Irgendwo dazwischen: 3 Auftragsbestätigungen mit Fehler. Der händische Abgleich ist aufwändig und teuer. Darauf hoffen, dass es passt, ist aber auch keine Option. KogniLink bietet die Alternative: Jede Bestätigung wird automatisch gegen die Bestellung im ERP abgeglichen: Positionen zugeordnet, Stückmenge, Preise, Einheiten und Summe verglichen, Abweichungen markiert. Geprüft in unter einer Minute. Nur Ausnahmen landen beim Einkauf, mit Kontext zur Entscheidung. Jede Prüfung ist 100% nachvollziehbar. Das Ergebnis: In mehreren Fertigungsunternehmen spart der Abgleich heute zwischen 25 und 55 Stunden pro Monat. Das Verfahren für die intelligente Prüfung geht weit über die Prüfung mittels LLMs hinaus, und sorgt für eine deutlich höhere Ergebnisqualität. Die Funktion ist Teil unserer KI-Plattform für Fertigung & regulierte Industrien. Angeschlossen an euer ERP, PLM, DMS und E-Mail-Postfächer, automatisiert sie tägliche Fleiß- und Tipparbeit in Fachabteilungen. Vom Belegabgleich über die Recherche in 8D-Reports, die Prüfung von Analysenzertifikaten bis zur Compliance-Überwachung von SOPs und Lieferketten. On-Premise, schon auf kleiner, kostengünstiger Hardware, kein Dokument verlässt das Haus. Klingt zu gut? Überzeugt euch selbst: kostenloser Pilot, eure Testdaten, keine Verpflichtung.

Arcade is the only MCP runtime built to run real agents in production. With Arcade, your agents get: secure agent authorization, high-accuracy tools, and centralized governance.

MCP gives you the protocol. You still need the runtime. Here's what breaks when you move from demo (one user, hardcoded creds) to production (1000+ users, real systems) – The gap MCP doesn't fill: →Multi-user OAuth flows that work inside agent loops →Token lifecycle management without exposing credentials to the model →Tool optimization for accurate agent selection →Governance with audit trails showing who did what, when →Version control and centralized execution with failover logic That's the infrastructure gap that kills 70% of agent projects. Arcade is the MCP runtime that solves it—sitting between your agent and 1000+ tools with proper authorization, execution integrity, and operational control. Try it yourself → https://lnkd.in/gMDkkrAD

Most talks about AI agents stay theoretical. This one doesn't. Alyx 2.0 is an AI engineering agent built for real AI workflows — error analysis, prompt experimentation, trace debugging — all executed autonomously inside Arize AX. Join Arize engineers Priyan Jindal and Jack Zhou for a live 45-minute demo and technical deep dive into how they actually built it: → The planning architecture behind multi-step reasoning → How they solved context management at scale → Testing strategies that got an agent to production Practical lessons. Real design decisions. Live Q&A at the end.

What does it look like when an AI agent actually understands your debugging workflow? Alyx 2.0 — now live in Arize AX. Unlike most AI assistants that follow a single decision tree, Alyx breaks down complex tasks, reasons across multi-step workflows, and acts autonomously across your entire AI lifecycle: ↳ Error analysis ↳ Prompt experimentation ↳ Trace debugging We're hosting a live walkthrough to show you exactly how it works. Save your spot → https://lnkd.in/gpEggkGi

Bank of America built Erica seven years before the rest of the industry caught up. As the "build once, reuse" strategy expands into agentic workflows across markets and wealth, Arthur is the observability and governance layer built to operate at that scale.

The banks already running agentic AI in production are discovering they need to retrofit governance after the fact. U.S. Bank has the opportunity to do it the right way — with Arthur as the foundational observability and governance layer for every agent, before they scale, not after.

We invite you to read the full TRACES technical report Inside: the definitions, evaluation rubric, and registry of problems spanning biomedicine, clinical translation, and frontier-model engineering. Led by Apodex Lead Scientist Sheng Wang, the report brings together the technical framework underpinning this effort. Behind it: 10 STEM PhDs, two months of research, and 561 industries surveyed to identify 423 problems worth solving—real, high-stakes questions that can take human experts years to work through. Bring a problem. Bring a solver. Both doors are open. *Submit a Problem: https://lnkd.in/gmurNBMN *Submit a Solver: https://lnkd.in/g7ZsKZzE

Join us at #GITEX2025 for hands on demos. Test near human machine translation with context preservation, cross lingual semantic search, document QA and summarization, RFP and contract assistants, and meeting summarization for Arabic and English. All built on #Pronoia for enterprise latency, quality, and scale. We are at Hall 8, Booth H8-19, Oct 13 to 17, Dubai World Trade Centre. Bring your use cases and we will map a path to production during the session. Get your free invitation: https://lnkd.in/dr89YHCf

🌍 We at Arabic.AI are leading the market — and redefining what “Arabic-first AI” truly means. While most global models adapt to Arabic, ours was born in it. From Pronoia, our 32B-parameter Arabic-first LLM, to AI Agents built for legal, finance, retail, and government workflows — we’re helping enterprises and ministries across the region solve real business problems with precision, dialect fluency, and enterprise-grade security. What makes us different? ✅ 16+ years of Arabic data excellence ✅ Near-human accuracy across dialects ✅ On-premise & cloud deployment options ✅ Human-in-the-loop expertise for quality and compliance ✅ Seamless integration with your systems — and your people We’re not just building AI tools. We’re building the future of Arabic intelligence. Oh, and by the way… I love the Riyadh office vibes today! 🇸🇦☕✨ There’s something about the energy here that just feels like the future is being built right in front of us. #ArabicAI #Pronoia #AIinArabic #Riyadh #Vision2030 #EnterpriseAI #AITransformation