Tagged articles

Apache Ossie

7 articles · Page 1 of 1

Sep 28, 2026 · Artificial Intelligence

10 Financial Firms Share AI Agent Strategies for 98.5% Auto-Review, 0.003% Fraud

This article analyzes how 10 leading financial institutions implement AI agents in low-tolerance scenarios, detailing their approaches to data ontology, semantic layers, multi-agent architectures, risk control, and evaluation frameworks, achieving metrics like 98.5% automated review rates and 0.003% fraud rates while ensuring auditability and regulatory compliance.

AI AgentsAgent EvaluationApache Ossie

0 likes · 43 min read

10 Financial Firms Share AI Agent Strategies for 98.5% Auto-Review, 0.003% Fraud

DataFunTalk

Sep 15, 2026 · Industry Insights

AWS COA Open-Sourced: Semantic Layer Evolves into Agent Runtime Context Layer

AWS open-sourced Context Ontology Accelerator (COA) to bridge structured and unstructured data via AI-generated ontologies, governed metrics, and knowledge graphs served through MCP, signaling a shift from traditional semantic layers focused on unified metrics to agent-ready business context infrastructure combining ontologies, rules, and authorization for accurate, auditable agent decisions.

AWSAWS ContextAgentic AI

0 likes · 14 min read

AWS COA Open-Sourced: Semantic Layer Evolves into Agent Runtime Context Layer

DataFunTalk

Sep 13, 2026 · Industry Insights

AWS COA: Semantic Layer Evolves into Agent Runtime Context Infrastructure

AWS open-sources Context Ontology Accelerator (COA) to bridge structured and unstructured data, generate enterprise ontologies for knowledge graphs, and expose governed metrics, entity relationships, and business rules via MCP, marking a shift from traditional semantic layers to agent-ready context infrastructure.

AWSAWS ContextAgent

0 likes · 10 min read

AWS COA: Semantic Layer Evolves into Agent Runtime Context Infrastructure

DataFunSummit

Sep 1, 2026 · Industry Insights

How Ant Group Scaled Apache Ossie Semantic Layer from Zero to 5,000 Metrics

The article explains why large language models struggle with business data, introduces Ant Group's semantic‑layer approach built on Apache Ossie to impose strong business constraints, compares it with other retrieval methods, and details the engineering journey that delivered a unified source of truth for over 5,000 metrics while also announcing a related conference.

AI AgentsAnt GroupApache Ossie

0 likes · 4 min read

How Ant Group Scaled Apache Ossie Semantic Layer from Zero to 5,000 Metrics

DataFunTalk

Aug 26, 2026 · Artificial Intelligence

Can Apache Ossie Become the Unified Business Language for AI Agents?

The article examines Apache Ossie's emergence as an Apache incubating project that aims to provide an open, vendor‑neutral format for sharing semantic models—metrics, dimensions, relationships, and AI context—across BI, data platforms, and AI agents, while outlining its current capabilities, governance model, and remaining challenges such as concept‑level interoperability and query execution.

AI AgentsApache OssieSemantic Layer

0 likes · 14 min read

Can Apache Ossie Become the Unified Business Language for AI Agents?

Big Data Technology & Architecture

Jul 28, 2026 · Artificial Intelligence

Write Once, Query Anywhere: How Apache Ossie Completes Semantic Model Standardization

The article examines Apache Ossie's role as an incubating Apache project that defines a vendor‑neutral, AI‑ready semantic metadata standard, addressing semantic islands, improving AI Agent reliability, and enabling reusable, exchangeable business semantics across analytics, BI and data platforms.

AI AgentApache Ossiedata interoperability

0 likes · 10 min read

Write Once, Query Anywhere: How Apache Ossie Completes Semantic Model Standardization

DataFunTalk

Jul 19, 2026 · Industry Insights

Can Apache Ossie Become the Unified Business Language for AI Agents?

The article analyzes Apache Ossie's transition to an Apache incubated open semantic model, explaining how it aims to standardize business semantics across data platforms for AI agents, while highlighting its current focus on structural interoperability, governance, and the gaps that remain in conceptual and execution semantics.

AI AgentApache OssieSemantic Layer

0 likes · 16 min read