Services
Automation rarely arrives as a clean brief. Usually there is a legacy system in the way, an integration that does not exist, or a data model nobody trusts. These are the disciplines we bring to that, and they are also how izardis has worked since before AI was the headline.
Strategy work with a deliverable at the end of it, not a workshop series. We map what you run today, where the cost sits, and what sequence of changes actually pays. Most engagements start here and run two to six weeks.
Custom products and internal systems, built to be handed over. You get the repository, the documentation and the deployment pipeline, and the engineers who wrote it are available afterwards rather than reassigned the day it ships.
For software that is already live and has to stay that way. Integration, optimisation, maintenance and support, with a response commitment written into the agreement rather than implied.
Warehousing and business intelligence, and the unglamorous data cleanup that has to happen first. Most AI projects that stall, stall here: the model is fine, the data underneath it is not.
QA engineers on staff, not borrowed from the development team when a release slips. Functional, performance and security testing, plus building the automated suite so the next release does not need the same effort.
Interfaces for the internal tools automation tends to leave behind: exception queues, review screens, admin panels. The places where a person has to step in are exactly the places worth designing properly.
How we engage
A defined deliverable at a fixed price, quoted after the audit. Best for a first automation or a contained build.
Named engineers at a monthly rate, working as part of your organisation with US-hours overlap.
We keep what we built running, with a response commitment and a monthly report on how it is performing.
That is what the audit is for. Thirty minutes on a call, written findings within the week, no cost attached.
