UnityRoot 中文EN
Consulting services · UnityRoot Solutions

Make AI actually land, starting
with a system that's ready for it

We help Taiwan SMBs and product teams adopt AI, move ageing systems to the cloud, and then stay on as an outside technical partner. The approach is plain: first make the system changeable and deployable, then put AI where it is actually worth something.

Book a free 30-min call See the three packages

Pricing by conversation: every project is different, so we don't publish price tags.

Who we work with

If this sounds like you, we can probably help

Product teams that want AI features You have a product and you can see where AI fits, but there is nobody on the team who does machine learning and no obvious place to start.

SMBs on an ageing stack The site or the internal system has run for years, deploys are manual, there is no dedicated ops person, and everyone is afraid that touching it will break something.

Teams that need an outside partner You ship, but the infrastructure is fragile: no monitoring, no alerting, and the critical knowledge lives in one or two people's heads.

We have been inside these industries ourselves: manufacturing years at Foxconn, ASUS, Lite-On and CliqStudios in the US, twenty years in finance, and our own operating experience in elder care and consumer apps. You will not need to translate your industry's language into engineer-speak first.

Packages

Three ways to work together

Most clients start with modernization to build trust, move on to AI integration, then continue on the retainer once it is live. Taking just one of the three is perfectly fine too.

Flagship

AI Integration Accelerator

Turn AI from "sounds good" into a feature that actually runs in your product, with a cost and a quality bar you can measure.

What we do

  • AI readiness assessment: data quality, use-case fit, API selection
  • Integration design: pick the right LLM for the case, commercial API or self-hosted
  • Build a working MVP: RAG question answering, chat endpoint, document classifier
  • Prompt engineering plus an evaluation harness, so quality can be measured and regression-tested
  • Optional: agent workflows wired to your internal tools over MCP

What you get

  • Use-case prioritization matrix
  • A working prototype with full source code
  • Evaluation rubric and cost model (token budget, latency estimates)
  • Handover documentation your team can carry forward

Typical timeline: 3–6 weeks for an MVP integration, 6–12 weeks for production-ready.

Contact us

System Modernization Sprint

Map the ageing system first, then move it in phases without stopping the business. This is where most engagements start.

What we do

  • Discovery audit: codebase, servers, database, deployment
  • A phased migration roadmap with a risk assessment on each phase
  • Hands-on execution: replatform to cloud, containerize, or refactor the key modules
  • Set up a basic CI/CD pipeline and handover docs the next person can follow

What you get

  • Audit report with a priority matrix
  • Cloud infrastructure set up (AWS EC2/RDS or equivalent)
  • A deployed new environment with a rehearsed rollback plan
  • A runbook for ongoing operations

Typical timeline: 4–8 weeks, depending on how complex the system is.

Contact us

Tech-partner retainer

We become your outside technical partner. No full-time ops hire, but somebody is watching the system, picking up incidents, and available to think with you.

What we do

  • Infrastructure monitoring and alert triage
  • CI/CD pipeline maintenance and upgrades
  • Security patching and dependency management
  • A monthly one-hour architecture review call
  • Incident response, with the response time written into the contract

What you get

  • A monthly ops health report
  • A patch and deployment log
  • The agreed incident response SLA
  • A quarterly infrastructure roadmap session

How it runs: ongoing, with a three-month minimum suggested, sized to your team.

Contact us

On pricing: every project differs in system state, data volume and risk, so we don't publish price tags. After the free call you get a written proposal stating the scope, what is explicitly out of scope, and the number.

How it works

Four steps, no surprises

1

Free 30-minute call

We work out where you are, what you want solved, and whether there is anything worth doing. No fee, no pitch.

2

Scope document and proposal

In writing: what is in, what is out, what gets delivered, and the price. Nothing starts until you agree.

3

Work begins, weekly check-ins

A steady reporting rhythm. If something is stuck you hear about it that week, not at the deadline.

4

Delivery and handover docs

You get the work, plus handover documentation and runbooks your team can actually read and run.

Why trust us

Start by looking at what we built

We can't promise you somebody else's numbers, but you can look straight at our own products. Care Logger and HalaMoney were designed, built, shipped and are still operated by us, and both are live on iOS and Android today.

The cloud architecture, deployment practice and AI techniques in our proposals are not slideware. They are what we run on our own products, and what we get up at night to fix.

See our apps

What we work with

Not a buzzword list, these are the tools running our own products.

Claude / LLM API RAG MCP Agent workflows AWS Cloudflare CI/CD PostgreSQL Flutter iOS / Android WireGuard
FAQ

Things people ask

Can we buy just the assessment?

Yes. Plenty of clients start with an audit or an AI readiness assessment, then decide whether to build it in-house or with us once they have the report and the priorities. The report is yours either way, with no lock-in.

Do we have to use Claude, or any particular API?

No. Model selection is part of the assessment. We choose against your use case, your cost ceiling and your data constraints, and self-hosted or on-device models are on the table.

Will our data leave the company?

Data boundaries are discussed during the assessment and written into the scope document. Where compliance or customer contracts forbid data leaving, we design toward self-hosted models, de-identification or on-premise processing.

Can we work in English?

Yes. Meetings, documents and code comments can run in Chinese, English or both. We are in Taiwan (UTC+8) and can take early or late calls to overlap with European and US hours.

What happens after the project ends?

Every delivery includes handover documentation and runbooks so your team can take it from there. If you would rather someone kept watching it, that is exactly what the tech-partner retainer is for.

Start with 30 free minutes

Tell us about your system, the problem you want gone, or just whether AI is worth anything to your business. You leave with an honest answer, including "not yet" if that is the truth.

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