Services
We build it, monitor it, and hand it over properly.
An experienced team that ships software and then operates it. We take on three partner products a year, we build quickly, we decide the architecture and the access rules like people who will be on call for them, and we finish by handing your team something they can run without us. You own the repository from the first commit, so none of that is a promise you have to trust us on.
What we usually walk into
- “The prototype worked. A real business depends on it now and we are afraid to touch it.”
- “We shipped quickly, and the person who wrote the login code has left the company.”
- “We have an AI feature that demos beautifully and nobody here trusts it.”
- “The last team delivered, invoiced, and disappeared. We cannot maintain what they left us.”
If one of those is your situation, this is the work that gets you out of it.
Zero to launch
A new product, from scratch.
From the first conversation to paying users, with your team in the room for the decisions instead of briefed after they are made.
Most of this work starts before anyone has written a spec. We spend the first couple of weeks inside your problem and your data, then build the smallest version real users can break. You sit in those decisions, because you are the one who has to run the thing afterwards.
What you end up with
- A product real users pay for
- A team that can keep shipping without us
- The repository, from the first commit
Scale what works
Scale what already works.
A platform with real traction that needs more users, more markets, or more channels without downtime.
Software that grew quickly usually has three or four places where ten times the traffic will break it. Sometimes it is a slow query. Sometimes a queue. Often it is one database table that everything else is quietly waiting on. We find those first and fix them while the product stays online.
What you end up with
- Room for ten times the current traffic
- The bottlenecks found and fixed
- Dashboards your team can read without us
AI inside
AI inside what you already run.
Intelligence added to software your team already uses, with the limits written down and human approval on the expensive paths.
This is the work that goes wrong most often. A model gets wired to a button, and then nobody can say whether it helps or how badly it fails. We attach evaluation before the feature ships, so quality is a number you can watch. Where being wrong costs money, a person stays in the loop by design.
What you end up with
- Evaluation in place before launch
- Costs and failure modes written down
- A list of what it refuses to do
What we can build for you.
Software, mobile, AI, integrations, and the reporting that has to sit under all of it. Most engagements use three or four of these at once.
Web platforms
The product your customers log into, and the admin tools your own team needs behind it.
Customer portals / Dashboards / Marketplaces / Admin and back office
Mobile apps
Cross platform or installable web, chosen for what the product has to do rather than what is fashionable.
iOS and Android / Progressive web apps / Offline and sync / Push and notifications
AI features
The useful kind, with accuracy measured before launch and a person kept in the loop where being wrong is expensive.
Assistants and chat / Document extraction / Classification and scoring / Search and recommendations
APIs and integrations
Connecting the systems that never quite agree with each other, without losing data in the gap.
Payments and payroll / CRM and support tools / Public APIs and webhooks / Legacy system bridges
Data and reporting
Getting the numbers out of the product and in front of the people who make decisions on them.
Pipelines and warehousing / Reporting dashboards / Event tracking / Exports and audit trails
Automation and internal tools
The manual process somebody is currently doing in a spreadsheet at the end of every month.
Workflow automation / Approvals and queues / Scheduled jobs / Ops tooling
Industries we have shipped in
Careers and hiring. Marketing and content. HR and payroll. Cross border payments.
Those are the four we have built, launched, and still run day to day. Payroll and payments in particular come with rules you cannot talk your way around, which is where most of our habits about access control and audit logs came from. We take work outside these areas, and when a domain is genuinely new to us we say so before you sign anything.
Built quickly, and built to survive production.
AI writes a good share of the code. It does not get to decide the parts that would hurt you eighteen months from now, when your team is the one supporting it.
Permissions before features
Who can read which record gets designed before the first screen exists. Adding access control to a live product later is how data breaches happen.
Secrets, data separation, audit logs
API keys stay out of the repository, each customer's data stays separated from the next, and sensitive actions are logged so you can see who did what.
The stack is chosen, not defaulted
We pick it for what the product has to survive: the load it will see, the rules it falls under, and the team that inherits it after we go.
A person reviews every line
AI writes plenty of it. It will also add a dependency nobody has checked and write a database query with no index. An engineer who will be on call reviews all of it.
AI is a tool here, not the offer. Not every job needs a model. A good share of what we take on is ordinary software built properly, and if AI would only add cost we will tell you before you sign anything.
Four phases. Each ends in running software.
Not a slide deck about software you might get later. You own the code and the decisions the whole way through.
Phase 01
Find the real problem
Two weeks with your team and your data. We work out where the work genuinely helps and where it would only be expensive.
Ends with: A scoped plan, a data model, and a list of what we would not build.
Phase 02
Prove it works
A working prototype with evaluation attached, so quality is a number you can watch rather than a feeling in the room.
Ends with: A prototype your users touch and a baseline to measure against.
Phase 03
Build it and monitor it
Weekly releases behind feature flags. Logging, cost tracking, access rules, and alerting all go in before the first real user arrives.
Ends with: Production access, dashboards, an operations guide, and a security review.
Phase 04
Hand over the keys
Your team owns the code, the models, and the roadmap. We stay on support for as long as that is genuinely useful to you.
Ends with: Repo transfer, documented architecture, a team that can run it.
We take on three partner products a year. That is how many we can build without the quality of our own products slipping.
Work we take, and work we don't.
Saying this out loud early saves both of us a month of polite meetings. If your work sits in the right column, we will tell you on the first call and point you somewhere better.
Work we do well
- A product that has to exist in months, with a team that will keep running it
- Software where being wrong is expensive and quality has to be measured
- A prototype that got traction and now has to be rebuilt properly
- Existing software that works but nobody enjoys using
- A founding team that wants to be in the build, not briefed on it
Work we turn down
- Staff augmentation, or bodies billed by the month
- Projects where AI is the requirement and the problem comes later
- Fixed scope written before anyone has spoken to a user
- Work that needs a team we would have to go and hire first
Tell us the problem you're trying to solve.
No spec required and no deck to sit through. You will hear back within two working days from someone who would be on the build.