Division 01
Cloud & DevOps engineering
Migration, delivery automation, container platforms and cost work for teams running production systems. Client work and our own SaaS.
What we doSt. Louis Park, Minnesota · United States
Authecity Systems LLC migrates, automates and runs cloud infrastructure, and builds the model-backed features that sit on top of it — inside services people already use, with the costs and failure modes worked out before launch. The same company runs a retail division selling on Amazon in the United States.
Division 01
Migration, delivery automation, container platforms and cost work for teams running production systems. Client work and our own SaaS.
What we doDivision 02
Consumer goods sold on Amazon US under the QuickShopa name, bought through authorised wholesale channels. Distributor enquiries welcome.
Trade informationServices
A short list rather than a long one. Each is work we have done end to end, not a capability we would be learning on your budget.
Request an assessmentModel-backed features inside services that already exist, taken past the demo into something with error handling, rate limits and a cost ceiling. Document search over your own content, drafting and summarising inside existing workflows, classification that removes a manual step.
Moving applications off shared hosting and ageing servers into environments that can be rebuilt from source rather than nursed by hand.
CI/CD pipelines, infrastructure as code and observability, so a release is a routine event and not a Friday-night decision.
Containerising applications with Docker and orchestration where it earns its operational cost — and saying so plainly when it does not.
Reading the bill line by line, finding the idle and the oversized, and designing environments that stay affordable once we have gone.
AI engineering
A demo takes an afternoon. The engineering is everything after the model call: what it costs per user, what happens when it is wrong, and whether anyone opens it twice. We build the second part, on the same cloud we would have built for you anyway.
01 / Where it goes
Search across your own documents, drafting and summarising inside an existing workflow, classification that removes a manual step. Features added to software your team already opens, rather than a separate AI product that has to win its own audience.
02 / What it costs
Token spend is a variable cost sitting underneath fixed pricing, which is how a popular feature becomes a loss. We meter it per feature, cap it, cache what repeats, and tell you what a bad month looks like before you commit to it.
03 / When it is wrong
Models are wrong, slow, and occasionally down. Timeouts, retries, a deterministic fallback, and a way to measure output quality that is not “it looked fine when we tried it”.
Our own product
A web and mobile anti-counterfeiting service for businesses producing or distributing fast-moving consumer goods in markets where fakes are common. A shopper checks a unit before paying; the brand gets a record of where and when its products are being verified.
Built cloud-native with separated application, storage and database tiers — the same architecture we set up for clients.
Selected work
SaaS platform
A verification service with separated application, storage and database tiers, designed so consumer-facing checks stay fast while brand reporting runs behind them without competing for the same resources.
Non-profit
A cloud-hosted subdomain joined to an existing church website and secured with HTTPS, without moving the parent site.
Modernisation
A customised WordPress recruitment platform moved from shared hosting onto a Linux cloud server with a managed database.
Contact
Current hosting, a cloud bill that keeps climbing, a deployment nobody wants to run. Describe it in a couple of sentences and we will come back with a practical next step rather than a proposal deck.