AgentsAugust 29, 2026via InfoQ AI/ML
Presentation: Architecting the Data Layer for AI Agents: From Transactional Systems to MCP and Semantic Models
Why it matters
As agents move from pilot to production, the data infrastructure underneath them becomes the bottleneck. This talk walks through real patterns for context optimization, token efficiency, and safe agent access to live transactional systems — the unsexy but critical layer most practitioners ignore.
Key signals
- Data mesh architecture for agent-native data access
- Low-latency database optimization for real-time agent decisions
- Semantic ontologies and dynamic MCP tool selection for context window efficiency
- Balancing deterministic logic with non-deterministic LLM behavior
- Token overhead reduction in transactional systems
- Security and precision constraints in enterprise agent deployments
- Speaker: Fabiane Nardon (TOTVS)
- Published: August 29, 2026
- TOTVS case study on enterprise data preparation for agents
- Data mesh and low-latency database architectures for agent context
- Semantic ontologies and dynamic MCP tool selection
- Token optimization and context-window management
- Focus on precision, security, and cost in agent deployments
The hook
Enterprise data layers aren't ready for agents. Here's how TOTVS is rearchitecting to feed token-hungry autonomous systems without breaking the bank.
Fabiane Nardon shares how TOTVS prepares enterprise data for token-hungry AI agents. She discusses balancing deterministic logic and non-deterministic LLMs across precision, security, and cost. Nardon details using data mesh, low-latency database architectures, semantic ontologies, and dynamic MCP t…