Technology

Architecture-first AI for SAP and enterprise systems.

The hard part is not choosing a model. It is connecting AI safely to data, workflows, permissions, tools, APIs, ERP systems, and monitoring.

Controlled tool access for AI systems, allowing agents to interact with approved enterprise APIs, databases, and workflow actions.

Retrieval architecture that grounds AI output in approved documents, tickets, policies, SAP context, and enterprise data.

Semantic retrieval layer for internal knowledge, SOPs, product documentation, reporting context, and operational history.

Integration patterns for SAP, ERP, CRM, databases, reporting tools, ticketing systems, and internal platforms.

Multi-step AI workflows with task planning, tool calls, context management, human approvals, and exception handling.

Access control, audit logs, reliability checks, evaluation, escalation rules, and monitoring for production AI systems.

Production Reality

Enterprise AI needs guardrails from day one.

Without architecture, AI pilots become isolated demos. With proper integration and governance, they become operational systems.

Identity-aware access to documents, systems, and tools.

Human review for sensitive approvals and business-critical actions.

Audit trails for prompts, retrieval context, outputs, and tool execution.

Model and workflow evaluation to measure accuracy, latency, and business impact.

Reusable components that reduce time-to-value across future AI use cases.