Dr Patrick ChuAI Consultant — Academic Research Pipelines

Own your AI research team on your own isolated server.

I provision a structured research-support environment with defined roles, checked workflows, and review layers for your project or lab. You own the working environment and receive the guidance needed to operate it.

Your data never leaves your server. I don't need to see it — I teach your agent to do the work.

Request a working demonstration The setup is built and available for a working demonstration — configuration and support are scoped to the workflows you need.

Who runs the work — an example team structure

The same shape as every project here: a structured team of specialist AI roles, with one accountable human at the top and a QA layer that reviews outputs before release.

  • Patrick Chu — founderDirection, judgement calls & final deliveryOne accountable person
    • Personal AI assistantoperations · tracking · briefings · cross-checks
    • Project managementplans scope, sequencing & decisions
      • Domain specialistsstatistics · methodology · subject area
      • Developerbuilds analyses, documents & tools
      • QA / claim reviewchecks every output against the evidenceGates every release
▲Review before release

▲ Every output passes the QA review layer before it reaches you.

Roles shown are responsibilities, not named tools. The structure is adapted to each project — and in your own setup, the roles are configured to your workflows.

What the setup includes

  • A dedicated, isolated environment for your project or team — on a server you own
  • Defined research-support roles with separate responsibilities
  • Checked skills and workflows configured for your agreed use cases
  • Review and escalation steps for evidence-sensitive outputs
  • A practical setup guide and operating checklist
  • Onboarding and handover for you or a nominated team member
  • Optional ongoing support, scoped separately

A working structure, not a single chat window

A general chatbot answers from one interface. This setup separates planning, specialist review, production, quality checking, and operations into defined roles — so recurring work follows a clearer process with stronger checks. The purpose is not to remove human judgement; it is to give routine research support a disciplined structure.

Designed for different research settings

Solo professors

Add structured research-support capacity without recruiting and managing a full team — your own AI research team, directed by you.

Labs with students or RAs

Add a support and review layer around the lab. The system augments the team; it does not replace supervision or academic judgement.

Methods-intensive projects

Separate methodological review, technical production, and claim checking instead of asking one general-purpose tool to do everything.

Privacy-sensitive work

Keep the environment isolated on a dedicated server rather than placing the project in a shared workspace.

How setup works

  1. 1

    Fit review

    We identify the workflows you actually run repeatedly and confirm your privacy and infrastructure requirements — including whether an owned setup or a managed engagement fits better.

  2. 2

    Working demonstration

    You inspect the existing isolated setup — role structure, workflows, review gates — before deciding anything.

  3. 3

    Provisioning

    A dedicated, isolated environment is created on a server you own, with your agreed roles and workflows configured.

  4. 4

    Configuration and checks

    The workflows are prepared and tested; access, isolation, and hand-offs are verified before handover.

  5. 5

    Handover

    You or a nominated team member are trained to operate the environment, and you receive the setup guide and operating checklist.

Human judgement remains in charge

The system supports research work; it does not take academic responsibility. You remain responsible for your research decisions and institutional obligations. I am responsible for the setup, configuration, and support agreed in scope — and for a managed consulting engagement, I personally review and deliver the contracted output.

Pricing

Fixed-fee, USD-first — one approximate HKD anchor. Scoped before work begins.

TierFrom
Working demonstrationfree — 30 minutes, no commitment
Setup (fit review + provisioning + handover)from US$1,000 (≈ HK$8,000) — one-time
First workflow pilotfrom US$1,000 (≈ HK$8,000)
Serverprovided by you (≈ US$5–6/month) — your data stays on your server; AI model usage costs are borne by you as well (typically a few USD per month for light use)
Ongoing supportoptional, scoped on request

Additional workflows, deeper training, or a managed engagement are quoted by scope. See the FAQ →

See the working setup before deciding.

I can demonstrate the existing isolated environment and discuss whether an owned setup or a managed engagement fits your workflows better.

Request a demonstration