REPLWARE｜Modern Data Stack Implementation
REPLWARE builds modern data platforms on open source, deployed in your data center, in the cloud, or hybrid — you decide where the data lives, and there is no per-seat licensing. Stop renting your software stack. The technology becomes yours.
What we usually walk into
For mid-sized enterprises the blocker is rarely "should we adopt AI". It is usually these four things, unresolved.
Data sits across ERP, MES and departmental spreadsheets. A cross-system monthly report takes two days of manual VLOOKUP, and by the time it is out the numbers are a week old.
Most SaaS data tools run only in the vendor's cloud. If customer lists, financials or process parameters must stay behind your firewall for compliance or a parent-company rule, those tools fail at the first gate.
Commercial BI and ETL tools are priced per seat. As adoption grows the renewal grows with it, and you have no credible alternative to negotiate with.
IT is two or three people. A vendor delivers a black box; every change means another statement of work, and the platform becomes one more legacy system nobody can maintain.
What REPLWARE does
Turn the two-day monthly report into a single click
We consolidate data from ERP, MES, CRM and departmental spreadsheets into one platform, with maintainable data models and automated orchestration — so every report has a single, traceable source of truth.
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You choose where it runs, with no per-seat licence
The platform can run in your own data center, a private cloud, a public cloud, or a hybrid setup — for example, sensitive data stays in your own data center while compute runs in the cloud. The same open source components run in both places, so the layout follows your data residency and compliance requirements. The stack is built on proven open source projects, so the platform belongs to you — no vendor lock-in, no subscription dependency.
Changing a report later takes no new statement of work
Our consultant and your assigned engineer develop together: the SQL, the data models and the architecture documents are produced jointly. At close, your team can extend and operate the platform on its own.
How we work
Timeline, commitment and definition of done are settled in the first meeting — not discovered after the contract is signed.
We map your current systems, data flows and bottlenecks, and confirm whether our approach applies.
A tailored proposal defining the platform's boundaries, the technical stack, and a concrete roadmap with dates.
One day per week on-site, building alongside your assigned engineer so the knowledge transfers as the platform goes up.
In the proposal stage we agree on one representative report or business rule. The engagement concludes when that logic runs end to end on the new platform; your team migrates the rest the same way.
Client results
“Laurence helped us implement the Modern Data Stack, rapidly building out our data platform in just about three months. The results were transformative: report generation time was slashed from 27 minutes to under 10 seconds. Furthermore, our team's report development speed has tripled. Laurence's expertise delivered both performance and agility.”
Selected clients
Published by REPLWARE
《從試算表到資料平台》— Building a data platform, and the data-driven future
The first systematic treatment of the Modern Data Stack published in Traditional Chinese, written by REPLWARE founder Laurence Chen. It covers the architectural thinking, the implementation practice, and the organisational resistance enterprises meet when adopting a data platform.
The book describes the method REPLWARE actually uses. Read it first, then decide whether you want us.
About us
REPLWARE was founded in 2020. We build data platforms on open source technology for mid-to-large enterprises in Taiwan, deployed on-premise, in the cloud, or in a hybrid setup.
Our clients tend to share two traits. Their data is subject to compliance rules or is commercially sensitive, so it cannot be handed to a SaaS vendor. And their IT team is small enough that a black-box system — where every change means another purchase order — is not viable. So we hand the architecture and the implementation method over to your engineers in full.
If you are evaluating a data platform, write to us. Let's talk first and see whether this is genuinely the right thing for you to be doing.