Two things. And one product we built.
We used to list a dozen services. Most firms do. It made us look bigger and it made us worse, because the work we are genuinely good at is narrow: high-stakes software initiatives — deciding what should be built, and then designing and building it. everTest is the third thing, and it is a product rather than a service line.
Software strategy & architecture
Deciding what should be built, how it should be built, what it should cost, and whether the plan in front of you survives scrutiny. Often the cheapest thing we do and the most valuable — several of our longest client relationships began with a few weeks of this and nothing else.
What you get
- An architecture review that says plainly what will not survive contact with scale
- Build, buy or rebuild — with the maintenance cost of each, not just the license cost
- A delivery plan and an estimate we will defend in front of your board
- A second opinion on an estimate or a proposal you have been given
- Due diligence on a platform, a vendor or an acquisition target
- An independent technical assessment of an initiative already in trouble
When people call us
- The estimate came back at five years and eight figures and it feels wrong
- Two internal factions want different architectures and someone has to decide
- A vendor has delivered something that works but nobody can maintain
- You are about to commit a year of engineering and want one more set of eyes
In one case the standing estimate was five years and $25M. The project finished in eighteen months for under $2M — decided in the strategy phase, not in the build. In another, a lender about to hire more collection agents found that half the queue never needed a person at all.
Software engineering & delivery
Designing, building, replacing and rescuing high-stakes systems — enterprise platforms, marketplaces, catalogs, data pipelines and production AI. Usually the hard ones: live systems that cannot be taken down, data that cannot be lost, deadlines that have already slipped.
Small and senior, by design
Three or four people who have done it before beat fifteen who have not, and cost less. With good AI tooling that gap has widened — which is why we have stayed at around twenty people while the size of the projects went up.
The same team, project after project
The company exists because delivery kept failing for preventable reasons, nearly all of them about lost context. So senior leadership owns the decisions, the engineering group around it is one we have worked with for over a decade, and there is no hand-off where the context disappears.
Rescue is normal here
Most of our best-known work started as somebody else’s stalled initiative. We are comfortable arriving mid-flight, reading an unfamiliar codebase quickly, and being straight about what has to be thrown away.
Domains
- Retail and commerce — catalogs, marketplaces, sourcing, supply chain
- Financial services — lending, wealth, KYC and compliance automation
- Data and analytics platforms, including cloud migration
- AI and machine learning in production, not in pilots
How we work in your environment
We work in your stack, not ours — across modern .NET, Java, Python and JavaScript environments, on AWS, Azure or GCP, and on data platforms at real volume. Continuous delivery and automated testing throughout, and agile practices only where they earn their keep.
The case studies answer this question better than a list of logos would.
And we built everTest
AI test automation: plain-English test cases become production Playwright or Selenium code in bulk, with human QA in the loop, at roughly a quarter of the cost of authoring the same suite by hand. You can buy it on its own, or we fold it into a wider engagement.
Why it exists
At scale, test automation economics usually fail on maintenance rather than on initial authoring. The first hundred tests are cheap; the two hundredth selector change is not. everTest attacks the maintenance cost directly, which is the only thing that makes large suites survive.
You keep the code. Standard Playwright or Selenium in your repository, no platform for your team to learn, nothing to be locked into.
Ten years in the making
We built a record-and-playback automation product called ZenVerify about a decade ago and licensed it to a Big 4 firm, who ran 800+ KYC bots on it. It still did not make test automation mainstream. Generative AI is what finally closed that gap.
How we engage
Three shapes, and we will tell you which one you actually need.
A free hour
Bring the architecture, the roadmap or the stuck sprint. We spend an hour with your team and tell you what we would do. No deck, no obligation, and we will say so if you do not need us.
A six-week proof
You name the problem, we build the context, and within six weeks there is something you can judge — a working proof of concept, an architecture, or a plan we will defend. By then you know how we work and what we are worth.
A full delivery engagement
A full team under our technical leadership, or our people embedded alongside yours. Our typical client stays three to five years and comes back with the next thing.
Not sure which you need?
Tell us what is happening and we will say which of the three fits — or that none of them does. That conversation is free and it is the fastest way to find out.