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先端技術

応用研究・プロトタイピング

具体的なビジネス上の問いに照らして、新しい技術を体系的に調査します。技術動向の調査、実現可能性の検証、実際に動作するプロトタイプを通じて、明確な知見をお届けします。

概要

Not every promising technology is ready, and not every ready technology fits a given problem. Applied research closes that gap with evidence: what the technology can do today, what it would take to use it, and where the real risks lie.

We run research as a disciplined engineering activity, with a stated question, a reviewed method, reproducible experiments and an honest write-up. Some prototypes lead directly to products. Others end with a clear recommendation to wait, and reaching that conclusion early has real value.

ビジネスでの活用領域

  1. 01

    Technology feasibility studies

    Focused investigations into whether an emerging capability, such as a new model architecture, sensor type, protocol or platform, can meet specific requirements for accuracy, latency, cost or integration in your environment.

  2. 02

    Proof-of-concept builds

    Working prototypes that test the riskiest technical assumption first, using real or representative data, so stakeholders can see and evaluate the capability instead of relying on vendor claims.

  3. 03

    Benchmarking and evaluation

    Structured comparison of competing models, frameworks or vendors on your own data and tasks, using reproducible test harnesses that can be rerun as the available options improve.

  4. 04

    Research translation

    Turning academic papers and open-source research into engineering assessments: what has actually been demonstrated, under what conditions, and what would be needed to apply it in production.

エンジニアリングアプローチ

  1. 01

    Question and criteria

    We agree on the research question, the evaluation criteria and the result that would justify proceeding before any experiment runs, so findings cannot be reinterpreted after the fact.

  2. 02

    Landscape review

    We survey published research, open-source projects and commercial offerings to understand where the field currently stands and to avoid rebuilding what already exists.

  3. 03

    Experiment design

    Experiments are designed to isolate the riskiest assumptions, with baselines, controls and datasets documented so your team or an outside reviewer can reproduce the results.

  4. 04

    Prototype build

    We build the minimum working system needed to test the hypothesis, favoring speed of learning over polish while keeping the code clean enough to reuse.

  5. 05

    Findings and recommendation

    Results are reported plainly, including negative and inconclusive findings, with a recommendation to proceed, adapt, wait or stop and the reasoning behind it.

技術とプラットフォーム

Research tooling

  • Python
  • Jupyter
  • PyTorch
  • Hugging Face
  • Weights & Biases

Experiment management

  • MLflow
  • DVC
  • Docker
  • GitHub Actions

Prototyping

  • TypeScript
  • Next.js
  • FastAPI
  • Streamlit
  • Unity

Hardware and edge

  • NVIDIA Jetson
  • Raspberry Pi
  • Arduino
  • ROS 2

記載の技術名は各社の商標であり、提携関係や推奨を意味するものではありません。

提供する成果物

  • Research brief with question and success criteria
  • Landscape review with annotated references
  • Reproducible experiments and datasets
  • Working prototype with source code
  • Findings report with recommendation
  • Production pathway outline where results support it

経営層からのよくある質問

What if the research shows the idea will not work?

Then the engagement has done its job. A clear, evidence-based negative result prevents a larger commitment to something that would not have succeeded. We report those findings as carefully as positive ones, and often identify an adjacent approach worth considering instead.

Who owns the intellectual property from a research engagement?

Ownership is set in the engagement contract, and client-specific work products are typically assigned to the client. We identify any pre-existing tools or open-source components up front, so licensing obligations are understood before development begins.

How do prototypes move into production?

A prototype is built to learn, not to scale. When results justify it, we plan a production path that addresses architecture, security, data governance and integration, reusing prototype components that hold up and rebuilding those that were deliberately kept simple.

応用研究・プロトタイピングの取り組みについて相談する

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