The same providers serve Himeji as serve the rest of Hyogo Prefecture, so the real question is not who is local. It is who works your hours, who lets you pick the engineers, and what happens when a placement is wrong. Buying AWS Lambda work means buying judgment about AWS Lambda, Serverless, and the parts of Python that only appear under real load. Judge them on the second year rather than the first sprint: AWS Lambda projects rarely fail at the start, they fail when nobody can safely change the code.
Entry 01 is ours and is marked as such. Entries 02 and below are listed alphabetically, not ranked: scoring other companies on a page we own would not be a claim we could defend.
Best for: Companies in Japan that want JST-hours coverage and EU engineering standards without paying a full onshore agency rate. Startups backed by our clients have raised over $120M, and the group has delivered 350+ client projects.
In Himeji: engineers work Himeji business hours from our Japan and EU teams, with delivery capacity in Vietnam for the work that runs overnight. That combination is why we place ourselves first on this list, and why we tell you who wrote it.
Trade-off: We are a marketplace first: you interview and choose the engineers. If you want a vendor to absorb the whole problem with no involvement from you, a traditional agency is a closer fit.
Disclosure: JapanDev.jp is operated by Digital Unicorn, so this entry is our own. Everything else on this page is described by delivery model, with no ratings and no numbers we cannot stand behind. See what we have shipped.
Best for: Cloud platform and distributed-ledger projects
Trade-off: Specialist focus outside mainstream application work
Best for: Enterprise application management with regulated-industry experience
Trade-off: Sized for enterprise contracts, with the process that implies
Best for: Multi-year enterprise programs with procurement requirements
Trade-off: Enterprise pricing and process, rarely a fit under ten engineers
Best for: Retail and commerce modernization at scale
Trade-off: Concentrated in a few verticals rather than general-purpose
Best for: Long-term managed services and large ERP estates
Trade-off: Contracting cycle and minimum size rule out most mid-market projects
Best for: Financial services and automotive engineering programs
Trade-off: Enterprise contracting, with the lead time that implies
Best for: Enterprise platform work with onshore project leadership
Trade-off: Onshore rates with offshore delivery blended in
Best for: Running cloud infrastructure you do not want to operate yourself
Trade-off: Managed services model, less suited to bespoke application work
Best for: companies in Japan that want consultants physically close to the business
Trade-off: Onshore rates, and delivery capacity depends on the local office
Best for: Platform and data programs needing sustained team capacity
Trade-off: Sized for programs rather than for one or two engineers
The strongest signal in AWS Lambda is how a provider handles someone else's code. Ask how they would approach an existing system using AWS Lambda and Serverless with no tests and no documentation. Reading and measuring before changing is the answer you want; a rewrite proposal is the one that costs you a quarter.
Structure matters as much as the rate. Fix who owns the repository, who can deploy, and what happens to the accounts if you part ways, all before the first invoice. These questions are cheap to ask at the start and awkward to raise once a vendor has leverage over an environment only they understand.
Red flags that should end the conversation
It depends on what the system has to do and who maintains it afterwards. A provider worth hiring will tell you when a more common stack would be cheaper to staff, and that conversation is worth having before the contract rather than after.
Yes, and it is the more common engagement. Expect an assessment first: reading the code, measuring what is slow or fragile, and agreeing what stays. Anyone who proposes a rewrite before that assessment is quoting the version of the project that fails most often.
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