AtScale

Peter Dolan and Chris Oshiro were on the ground this week at #READY2026 representing AtScale and our joint Adaptive Analytics solution with InterSystems. The questions enterprise teams are asking right now about AI reliability, governed metrics, and consistent data are exactly the problems this partnership is built to solve. Thanks InterSystems for the hospitality! CC Scott Gnau Mary Ann Fusi #SemanticLayer #EnterpriseAI #DataGovernance

Your AI made a loan decision that nobody can explain. According to JPMorgan and Goldman's own 10-Ks, that's not a technology problem. It's a material risk. In 2026, explainable AI is a regulatory requirement. AtScale provides the semantic trace behind every AI-driven decision: a governed, auditable log of exactly which business rule, which metric definition, which data source drove the output. When your agent denies a loan or flags an AML alert, it can show its work. Every time. Compliance teams sleep better. Regulators ask fewer questions. And your AI actually earns the word "trusted." #FinancialServices #ExplainableAI #SemanticLayer #AIGovernance

At Semantic Layer Summit 2026, Josh Klahr, Jamie Davidson (Omni), Mark Palmer, Ken Wong (Databricks), and David P. Mariani (AtScale) will explore how open semantics can create a more portable, interoperable foundation for AI and analytics. In this OSI panel, they’ll discuss what that means in practice: 🔸 Defining metrics once and using them across BI tools, data platforms, and AI agents 🔸 Reducing rework as architectures and technologies change 🔸 Understanding where open standards are headed and how to build for what comes next May 20. Free. Virtual. Register today! semanticlayersummit.com #SemanticLayerSummit #SemanticLayer #EnterpriseAI

The AI hype cycle is ending. The results cycle is beginning. To lead that shift, Mark Palmer is joining AtScale as Chief Marketing and Strategy Officer. Mark has built category-defining businesses across data, analytics, and AI as CEO of StreamBase, CPO at TIBCO, and most recently as an advisor to Warburg Pincus on AI and data strategy. He joins a leadership team that now includes Jay Schuren (President), Luis Maldonado (CPO), and Bryan Abou-Rjaily (CRO), all brought in during a period of hyper growth. Enterprises are learning the hard way that AI needs more than context for their data. AtScale provides a single source of computational truth, so both AI agents and human analysts receive the same governed, accurate, and sub-second answers every time. Read the full announcement → https://lnkd.in/eeR7V8_q #SemanticLayer #EnterpriseAI #AgenticAI #DataGovernance #AtScale

AI investments that don't deliver have something in common: no governed foundation underneath them. The enterprises seeing real returns built semantic infrastructure first: consistent metrics, trusted business definitions, shared context across every agent and analyst. The result is AI that holds up in a CFO review and agentic workflows that don't require a rearchitecture every six months. Semantic Layer Summit 2026 is where those teams share exactly what they built. 🔸 Production case studies from Carrefour, Papa Johns, Blue Yonder, TELUS, Vodafone, and Slickdeals 🔸 The agentic AI panel: Anthropic, NVIDIA, Accenture, WPP, Chevron, and OpenHands Community on the infrastructure gap between pilot and production 🔸 The open semantics debate — OSI, portability, and what enterprise AI infrastructure actually requires Free. Virtual. May 20. Read the full breakdown and register: https://lnkd.in/e5eP4Sxp #SemanticLayerSummit #SemanticLayer #AgenticAI #EnterpriseAI

Most enterprises are investing in the wrong layer. The models are getting better, but the results aren't. Gartner, McKinsey & Company, and practitioners running live tests are all pointing to the same gap. This week's Semantic Layer Newsletter pulls together the research, including a practitioner bake-off where a raw LLM returned $4.1M in expected deal revenue when the right answer was $2M, and a framework for what's being called "context rot": what happens when you flood an LLM with metadata and drown the signal. The throughline: the bottleneck isn't the model. It's the context layer. #SemanticLayer #EnterpriseAI #DataGovernance

Your factory floor can predict a failure. Your procurement system doesn't know it happened for three days. That gap between the sensor that caught it and the ERP that needs to act on it is where "predictive maintenance" goes to die. Agents can't fix what they can't see across systems. And right now, most manufacturing AI is operating half-blind. AtScale maps sensor data, financial ledgers, parts inventory, and supplier timelines into a single governed semantic layer, so when an agent detects a defect trend, it can check the budget, trace the raw material batch, and flag the right people before a line halt turns into a production quarter. The factory of the future needs more than sensors. It needs context. #Manufacturing #AgenticAI #SemanticLayer #Industry50

70% of consumers trust an AI agent to buy on their behalf. And yet almost no retailer has governed what that agent actually knows about their business. When "net margin" means something different in the POS system than it does in the warehouse, and an AI agent is acting on that data in real time, you get a flawed action, executed at machine speed. David P. Mariani's blog breaks down why autonomous commerce requires more than clean data pipelines: 📌 The industry average for store inventory accuracy sits at ~65%. AI agents routing orders against that data will make incorrect decisions, on average. 📌 Inconsistent metric definitions across finance, marketing, and operations get operationalized by agents, not just debated in meetings. 📌 Ungoverned agentic workflows create an "agent tax" redundant queries, conflicting results, and runaway compute costs The retailers that deploy autonomous AI successfully will be the ones that govern their business context before they hand it to agents. Read the full breakdown → https://lnkd.in/e57aqkbW #SemanticLayer #AgenticAI #RetailAI #DataGovernance #EnterpriseAI

30 days to Semantic Layer Summit. May 20th. Free. Virtual. Here's who should be there: 🔸 AI, data and analytics leaders deciding how to build AI infrastructure that doesn't fall apart under real enterprise conditions 🔸 Analytics engineers who are tired of maintaining five definitions of the same metric across four tools and agents 🔸 CDOs and heads of data figuring out how to govern AI outputs without slowing everything down 🔸 AI and data platform teams trying to give agents reliable business context 🔸 Anyone evaluating open semantics or how semantic models fit into modern enterprise AI architecture Practitioners and leaders from Anthropic, Chevron, Carrefour, Vodafone, Snowflake, ServiceNow, Papa Johns, ServiceNow, Blue Yonder, Slickdeals, TELUS, Accenture, WPP,and Omni are all on the agenda. Real deployments. Real tradeoffs. One day. No travel budget required. Register at semanticlayersummit.com #SemanticLayerSummit #SemanticLayer #EnterpriseAI