LLM-powered business systems, AI chatbots that handle response work, infrastructure that continuously collects and shapes data for AI use — we support the full stack of AI systems that move your business outcomes. We start from the problem worth solving, not the technology, and design from day one to avoid “PoCs that go nowhere” while keeping operations sustainable in the field.
First we separate problems AI can solve from problems AI should solve. We narrow use cases by weighing business impact, the realities of your data, and ongoing operational cost — and lock in technology choices and architecture before kick-off. A working PoC ships in weeks, in real-world use, and rolls into production from there.
RAG, agents, fine-tuning — we pick the configuration that fits the use case. Knowledge-base integration, evaluation sets, hallucination mitigation, and cost optimization are built in, so the AI sits inside your business and core systems with the reliability you need.
From AI chatbots that handle inquiries and automate workflow to chat-support tools that assist live operators. LINE, Web, Slack, Microsoft Teams integration, RAG-based responses with citations, and operator UIs with response history, suggestion drafts, and summaries — we choose what teams will actually keep using.
We build the systems that collect web data accurately and reliably and shape it into a form AI can use. Robust crawlers for dynamic sites and SPAs, LLM-driven structured extraction and tagging, change tracking and quality maintenance — designed for long-running operation, not one-time runs.
Typical timelines, scope, contracts, and deliverables. Useful when you’re scoping a project.