B2B ad examples

Você não precisa ser um especialista em dados para alcançar grandes resultados! No Banco Inter, Vinicius Rungue conseguiu extrair insights valiosos com o Alteryx, mesmo sem experiência prévia com a ferramenta ou formação na área de dados. Isso é o que buscamos na Kriptos: empoderar usuários de todas as áreas com soluções acessíveis e poderosas, que transformam desafios em conquistas. Descubra como podemos facilitar o seu dia a dia e impulsionar sua performance! #Alteryx #Inovação #TransformaçãoDigital #ferramentalowcode #kriptos #bancointer

Amplitude é uma ferramenta que transforma dados em decisões estratégicas. Assim como destacou Lucas Borges, a facilidade de uso no dia a dia é um dos grandes diferenciais que a demonstração de Amplitude no evento conseguiu mostrar. Caso queira conhecer a melhor solução e como o Kriptos pode te ajudar a extrair o melhor dela, fale conosco. https://lnkd.in/d4z6ZM9w

Legacy workflows slow growth. Learn how modern data teams are scaling with AI-driven automation in our latest whitepaper.

Data shouldn’t hold you back. Cut operational costs by up to 80% with AI-driven automation built for modern data teams.

Wie met data en algoritmes werkt, weet: met beloftes en hype ontstaan kaartenhuizen. Duidelijke keuzes en vakmanschap leiden tot oplossingen met impact.💥 Daar werken we bij BigData Republic elke dag aan. In kleine teams ontwerpen, ontwikkelen én optimaliseren we data- en AI-oplossingen die doen wat ze moeten doen: betrouwbaar draaien, meegroeien en waarde leveren. Geen consultancy-clichés, wel afwisseling, groeikansen en kennisdeling. Klinkt als jouw manier van werken? Ontdek BigData Republic. 🚀 #BigData #TechCareers #DataVisionaries

Dashboards shouldn’t slow teams down. Stop fighting your analytics stack and start getting answers instantly.

Dashboards shouldn’t slow teams down. Stop fighting your analytics stack and start getting answers instantly.

ZoomInfo, 6sense, RocketReach, and 50+ more data teams license our signal data. If the biggest names in sales tech trust our data, your product can too.

Your engineers have better things to build than data pipelines. License 25+ production-ready signal types via API. News, hiring, patents, Reddit, SEC filings, and more.

Aspia classifies every insured field by capacity, volatility, and structural floor from 10 years of continuous observation, independent of the carrier's own risk assessment. When a cedant can demonstrate field-level governance, treaty pricing reflects it. When they can't, the gap is yours to carry. This is already in operation: one major reinsurer requires systematic monitoring as a governance condition of their agricultural treaty.

You know what they've bought and planted. You've never had an independent view of what their land can structurally do - its proven ceiling, how it behaves in a bad year, how it compares to similar land nearby. Aspia classifies every field based on 10 years of continuous observation.

We’re excited to share that AWS has officially published AutoMQ’s Partner Success Story featuring FunPlus. AutoMQ is an AWS Differentiated Partner and is available on AWS Marketplace, so AWS customers can subscribe to AutoMQ directly through their existing cloud procurement workflow. The newly published AWS Partner Success Story highlights FunPlus, a global interactive entertainment company behind games such as State of Survival, King of Avalon, Guns of Glory, and DC: Dark Legion. For gaming platforms running high-throughput Kafka workloads on AWS, cost is often hidden in the network path, not only in broker instances. The FunPlus case shows how AutoMQ on AWS helps reduce that pressure: 1️⃣ Reduce cross-AZ traffic fees by changing the Kafka storage and replication model. 2️⃣ Keep Kafka-compatible APIs so existing producers, consumers, and stream processing jobs continue to work. 3️⃣ Run a cloud-native Kafka architecture on AWS while aligning infrastructure spend more closely with workload growth. 🔎 The result: 𝟓𝟎% 𝐥𝐨𝐰𝐞𝐫 𝐊𝐚𝐟𝐤𝐚 𝐜𝐨𝐬𝐭 by reducing cross-AZ traffic fees. 👉 Read the AWS Partner Success Story: https://lnkd.in/gHau9fnp Subscribe on AWS Marketplace: https://lnkd.in/gi_xPM9H For more Kafka and AutoMQ engineering insights, follow AutoMQ on LinkedIn or join the AutoMQ Slack community: https://lnkd.in/gk8txSCU #Kafka #ApacheKafka #AWS #AWSMarketplace #StreamingData #GamingInfrastructure #AutoMQ

Switch from Monarch without rebuilding. Get AI-assisted model conversion, intelligent OCR, AI-powered template generation, and award-winning support.

"ASA’s Neurodiversity Training was a great launchpad for building a more inclusive workplace, as well as improving our library spaces too.”

"My team are much better equipped to support neurodivergent employees." See what our Neurodiversity Training covers.

Addresses from digital wallets aren't always correct. Our Shopify plugin makes sure they are before the order ships. ✅

Irish addresses are manually typed or pulled from digital wallets. Our Shopify plugin makes sure they're correct before the order ships. ✅

Imagine a material MIFIDPRU figure is challenged tomorrow. Could you quickly produce the source data, calculation logic, adjustments, assumptions, reconciliations, approvals and reporting history? If gathering that evidence would mean pulling together spreadsheets, emails and information from different teams, there may be gaps worth addressing. How defensible is your MIFIDPRU reporting?

A MIFIDPRU number changes. The important question is: why? Was the source data corrected? Did an assumption change? Was the calculation methodology updated? A strong reporting process doesn't just produce the latest figure. It preserves the evidence needed to understand and explain how that figure changed. Make every MIFIDPRU number defensible.

𝗔𝗱𝗼𝗯𝗲 is running AutoMQ in production across 𝟰𝟬+ 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 in place of vanilla Kafka. Pranshu Jain at Adobe just shared this production data point. What stood out to me is how focused the change was: existing Kafka clients stayed untouched, while Kafka data moved from broker-local disks to object storage. According to Pranshu, that removed most of the infrastructure cost around the Kafka layer, along with the 2 a.m. rebalancing pages. The broader architecture is equally interesting: 𝘈𝘶𝘵𝘰𝘔𝘘 → 𝘖𝘱𝘦𝘯𝘛𝘦𝘭𝘦𝘮𝘦𝘵𝘳𝘺 → 𝘝𝘪𝘤𝘵𝘰𝘳𝘪𝘢𝘔𝘦𝘵𝘳𝘪𝘤𝘴 + 𝘚𝘪𝘨𝘕𝘰𝘻 → 𝘔𝘊𝘗 → 𝘰𝘱𝘦𝘯 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘮𝘱𝘳𝘦𝘴𝘴𝘪𝘰𝘯 → 𝘊𝘭𝘢𝘶𝘥𝘦 𝘰𝘯 𝘈𝘮𝘢𝘻𝘰𝘯 𝘉𝘦𝘥𝘳𝘰𝘤𝘬 → 𝘈𝘐𝘖𝘱𝘴 Across the overall observability stack, the #Datadog bill was 𝗿𝗲𝗱𝘂𝗰𝗲𝗱 𝗯𝘆 𝗿𝗼𝘂𝗴𝗵𝗹𝘆 𝟳𝟬% this quarter. Prompt caching cut inference spend by more than half. That architecture is a natural fit for observability. The workload is data-intensive and cost-sensitive, and telemetry volumes can change quickly, making elastic scaling a regular requirement rather than an edge case. AutoMQ's S3-backed, stateless Diskless Kafka architecture addresses these pressures: durable data sits in object storage rather than on broker-local disks, while compute can scale without moving large volumes of partition data. We're seeing more companies adopt AutoMQ for observability, and a clear pattern is emerging: Diskless Kafka is becoming a core architectural pattern for modern observability data stacks. It's also exciting to see Adobe use Kafka as the streaming backbone for an observability + AI stack, connecting high-volume telemetry with AIOps. Congratulations to Pranshu and the Adobe team, and thank you for sharing the architecture. 👉 See Pranshu's original post for the full implementation: https://lnkd.in/p/dEGrAAmm 🌐 Go under the hood of AutoMQ's diskless Kafka architecture: Kafka-compatible streaming backed by object storage, designed to reduce data movement and broker-local disk operations: https://lnkd.in/gmXZJaUd How are you using Kafka to build a modern observability platform? I'd be interested to compare approaches across telemetry ingestion, storage, query, and AIOps. #AutoMQ #Kafka #Observability #AIOps #Adobe #Datadog

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Today, Axiom extends our industry-leading observability platform with purpose-built features for generative AI development. Building with AI means accepting inherent unpredictability. Even well-tested systems produce occasional outliers, and small prompt adjustments can cascade into material changes in output quality. Traditional observability wasn't designed for this probabilistic reality. That's why we're launching AI observability features that give engineering teams the visibility they need to ship AI products with confidence. What's new: └ Rich AI telemetry capture with our TypeScript SDK – minimal code changes, maximum insight └ AI-native trace visualization for debugging complex multi-step workflows └ Automatic cost tracking via our free ModelDB API └ Pre-built dashboard that appears instantly with your first AI telemetry Our approach builds on OpenTelemetry standards, ensuring your data remains portable and vendor-agnostic. We've started with TypeScript and first-class Vercel AI SDK integration to help teams move fast. Frontier model providers already trust Axiom to handle petabytes of telemetry from their systems. And teams building breakthrough video generation models, multi-modal AI, and production-grade agentic systems rely on our infrastructure daily. Now we're making these same capabilities accessible to every team building with AI. This is our first major release in a broader AI engineering initiative. We have much more coming – but start here to transform how you observe, understand, and improve your AI systems.

Spotlight + AI is here ✨ - Investigate anomalies in seconds—no guesswork, no endless query iteration. → Select a region on a chart → Spotlight compares it against baseline behavior → Get a clear, trustworthy summary of what’s different Learn more ↓

Your team’s productivity shouldn’t depend on who knows where the data lives. Ask Gloria connects to all your business apps, CRM, emails, sheets, dashboards and delivers answers in seconds. Join 2,000+ businesses already saving up to 80 hours per week. 💡 Try it free for 7 days today!