From LLM-based AI Agent design to RAG pipelines,
multi-agent workflow automation, and prompt engineering.
We architect and operate AI systems tailored to your business.
AI adoption isn't about choosing a model.
It's about designing
which tasks become agents,
what context to inject,
and how to evaluate outcomes.
Acres builds production-grade AI systems.
We map your business logic to single or multi-agent architectures. Built on LangGraph state machines with task routing between agents, Tool Use for external system integration, MCP for shared context, and A2A for agent-to-agent coordination — all production-grade.
We transform internal documents, manuals, and databases into AI-ready knowledge systems. Semantic Chunking, Hybrid Search (BM25 + Vector), and Cross-encoder Reranking to minimize hallucinations, with evaluation pipelines to measure answer quality against hard metrics.
We wire AI into your existing systems — ERP, CRM, messengers, email — through automation workflows. Orchestration platforms like n8n and Make, combined with LLM nodes for trigger-based automation: webhooks, schedulers, conditional branching, all production-ready.
We design training programs so your team can operate and improve AI systems on their own. Prompt engineering workshops, Few-shot / Chain-of-Thought pattern design, governance frameworks for Korea's AI Basic Act (in force since Jan 2026), and red teaming for prompt injection defense.