Services & Capabilities
Practical AI systems that reduce manual work, surface institutional knowledge, and integrate into the tools your team already uses.
Most Requested
Your organization's knowledge — manuals, contracts, product specs, internal wikis — made instantly searchable through a conversational AI. Instead of keyword search, your team asks questions in plain language and gets accurate, cited answers in seconds.
Built on a retrieval-augmented generation (RAG) pipeline: documents are chunked, embedded, and indexed. At query time, semantically relevant passages are retrieved and passed to the LLM, which synthesizes a grounded response with source references.
Typical Stack
Core Capabilities
Modern lakehouse and analytics infrastructure — from raw ingestion pipelines to business-ready data marts. Built to scale, built to be maintained.
End-to-end phone agent systems — from telephony integration to LLM-driven conversation logic and voice synthesis. Handles real customer calls at scale.
Multi-step AI agents that read inputs, reason over context, call external APIs, and write outputs — replacing repetitive human-in-the-loop processes end-to-end.
Fast to Deploy · High ROI
Smaller, focused engagements — typically 2–6 weeks to production. These map closely to common pain points in Japanese organizations.
Connect a RAG knowledge base to LINE — Japan's dominant messaging platform. Employees or customers ask questions; the bot answers from your documents. No new app to install.
Record a meeting → get structured minutes in minutes. Transcription, speaker separation, action-item extraction, and formatted output to Notion, Google Docs, or email. Japanese and English supported.
Replace the monthly copy-paste ritual. An LLM agent reads source data, fills in templates, generates commentary, and emails the report. Works with existing Excel formats — no workflow changes needed.
Incoming emails are classified, summarized, and routed. For routine requests, a draft reply is generated and queued for one-click approval. Reduce response time from hours to minutes.
Upload product manuals, safety guides, or compliance documents. Staff ask questions in natural language instead of searching 200-page PDFs. Answers include page references. Ideal for manufacturing and operations teams.
A lightweight chatbot trained on your FAQ / support docs, deployed on your website or Slack. Handles JP/EN mixed queries. Routes unresolved cases to a human agent. Fast to set up, measurable deflection rate.
Engagement Model
A 30–60 min call to understand your data sources, team workflows, and the specific problem you want to solve. No sales pitch — just diagnosis.
A working proof of concept — usually in 1–2 weeks — so you can see the system with your actual documents before any large commitment.
Production-grade implementation with monitoring, access control, and documentation. Handed off to your team with full source code.
Ongoing support and refinement based on real usage data. Retainer or per-project — structured around what works for you.
Start a Conversation
Even a rough idea is enough to start. Describe what's slow, manual, or broken — and we'll figure out together whether AI can help.
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