AI Automation

AI automation layered on top of enterprise systems and workflows.

Mawai.ai designs AI agents and automation systems that connect to ERP, SAP, documents, databases, APIs, and internal workflows with governance and human oversight.

Enterprise AI agents that do useful work.

AI agents are most valuable when they are tied to specific operational tasks, allowed to access approved tools, and measured against process outcomes.

Workflow Agents

Route tasks, support approvals, classify requests, coordinate handoffs, and assist with exception handling.

Reporting Agents

Summarize KPIs, explain variances, generate operational updates, and help teams interpret business data.

Knowledge Agents

Retrieve answers from approved documents, SOPs, policies, tickets, project records, and operational knowledge bases.

Support Agents

Triage internal tickets, suggest resolution paths, retrieve relevant documentation, and escalate exceptions.

Approval Agents

Prepare context for approvals, identify policy requirements, flag missing information, and support human decision-makers.

Operations Agents

Monitor workflow signals, summarize open issues, assist with follow-ups, and reduce repetitive coordination work.

RAG Systems

Ground AI answers in enterprise knowledge.

Retrieval-Augmented Generation allows AI systems to answer questions using approved internal knowledge rather than relying only on generic model memory.

Document retrieval from SOPs, policies, manuals, contracts, tickets, and internal knowledge bases.

Vector database architecture for semantic search and context retrieval.

Source-grounded answers with better traceability and lower hallucination risk.

Role-based access so users only retrieve information they are allowed to see.

Governed knowledge refresh processes for changing enterprise content.

MCP Architecture

Controlled AI access to tools, APIs, and business systems.

Model Context Protocol patterns help structure how AI systems connect to enterprise tools without giving uncontrolled access to sensitive systems.

Expose approved tools and business actions to AI agents in a controlled way.

Connect agents to ERP data, ticketing systems, databases, APIs, and workflow tools.

Maintain permission boundaries, audit logs, and human-in-the-loop checkpoints.

Separate model reasoning from system execution for safer automation.

Create reusable integration layers for future AI automation use cases.