AI systems, built inside your business.
We become the AI team you don't have.
Our engineers work alongside your people, learn how the business actually runs, and build AI into it. First system running in 30 days. Then we keep going.
Built for founder-led companies without an in-house AI team.
We start with one job, so you can see how we work before anything bigger is on the table. Those first 30 days work when the job is clear, the systems are accessible, and one person can make decisions.
The problem
Most AI projects never make it into the work.
You have probably seen a demo that looked great. Maybe someone on your team stood up a chatbot. Then it sat there.
The demo is the easy part. The hard part comes after: connecting the tools, teaching the system how your business actually runs, deciding what it is allowed to do, and giving your team a reason to trust it. That work does not happen in a sandbox.
01
It never touches your systems.
The demo runs on sample data. Your data sits in six places, behind logins, with permissions someone has to approve.
02
It does not know how you work.
Your rules, exceptions, and the way you handle the weird cases live in people's heads. None of that is in a prompt.
03
Nobody set the limits.
Until it is clear what the system may do on its own and what needs a person, no one wants it near a customer or an invoice.
04
It has no owner.
A tool changes, the system breaks quietly, and within a month everyone is back to doing it the old way.
How we work
We work inside the problem.
Our engineers work with the people doing the job. We watch how work moves through your business, build the system around what we find, put it into use, and fix what fails.
That is different from writing a spec and coming back in three months with something nobody asked for. It is also different from handing you a tool and wishing you luck.
We work like part of your team, because that is the only way this works. You cannot learn a business from a requirements doc.
Some people call this forward-deployed engineering. We call it staying close enough to build the right thing.
We sit with the people doing the job.
Not a stakeholder interview. We watch a week of real work and write down who touches it, where it waits, and what gets decided.
We build in your systems, not a sandbox.
Your email, your records, your documents, your permissions. If we cannot get access to it, it is not part of the first job.
We put it in front of people early.
The first version goes to a small group while we are still there to see it fail. That is when the useful problems show up.
We stay for the part after launch.
Systems drift. A vendor changes an API, a form gets a new field, a rule changes. Someone has to notice and fix it.
Where to start
We start with one job.
You pick one job. Something that wastes hours every week, gets dropped when things get busy, or pulls someone away from work only they can do.
We spend the first 30 days on it: learning how it is done, building the system, and putting it to work. One job done properly beats a plan to fix everything — and it means you see how we work before either of us commits to more.
It rarely stops there. Once the first system is running, we take the next job, then the one after.
What the first 30 days include
- One clearly defined job
- One measurable result
- Required system connections
- Rules for what the system may do
- Human approval where needed
- A working deployment
- Monitoring and a written operating plan
What we build
Three kinds of jobs we take on.
Every business describes these differently. The shape is usually the same: work arrives, someone has to read it, decide something, and move it along.
Example one
Keep up with the day
Example two
Find and follow up with the right prospects
Example three
Move work between your tools
The first month
Four weeks. One working system.
Same shape every time. What changes is the job.
Week 1
Learn the job
We sit with the people who do the work and map every step, including the ones nobody writes down. We get access to the systems involved and agree on what the system will be allowed to touch.
By Friday: a written description of the job, the one result we are aiming at, and the access we need.
Week 2
Build the first version
We connect the tools, set the permissions, and build the first working version. It runs on your real data with nothing pointed at the outside world yet.
By Friday: a version you can try, running on your data, with everything it produces still under review.
Week 3
Use it on real work
A small group starts using it on live work, with a person approving anything that leaves the building. We watch where it is wrong, where it is slow, and where people quietly work around it.
By Friday: a week of real use, an honest list of what it got wrong, and fixes for most of it.
Week 4
Make it dependable
We widen the rollout, turn on monitoring and alerts, and write the operating plan. Then you decide who runs it from here.
By Friday: monitoring, a written operating plan, and a decision about what happens next.
After the first system
Then we keep going.
The first 30 days are how we start, not what we sell. Most of the value shows up in month four, when the system has been running long enough to be load-bearing and something in your business changes underneath it.
So we stay. We keep the first system working, and we take on the next job with everything we learned from the last one.
We run what we built.
A vendor changes an API on a Tuesday. A form gets a new field. A rule changes and nobody tells the system. We watch for it and we fix it, because we are the ones who will hear about it.
We take the next job.
The second system is faster than the first. We already have access, we already know how your business talks about its own work, and we already know which exceptions actually matter.
You get a team, not a ticket queue.
A channel with the engineers who built it. Ask a question, get an engineer. Nobody is going to route you to an account manager who has to go find out.
We tell you when AI is not the answer.
Plenty of stuck work is a broken handoff, a missing field, or a report nobody reads. Sometimes the fix is a script and a rule. We would rather say that than sell you a model.
Why Vextras
We have been responsible for production software since 2007.
Billions
in transactions processed by systems we built
Millions
of connected accounts kept in sync
10+ years
maintaining the same production integrations
Senior engineers
working directly with clients, start to finish
These numbers are not AI case studies. They are proof that we know what it means to build software people depend on.
You talk to the engineers.
No account managers. No game of telephone. The people who design and build your system are the people you talk to.
We maintain what we build.
If we built it, we keep it running. Systems that touch email, documents, records, and money need someone watching them after launch.
Production systems we built and still maintain for teams using
What work keeps getting stuck?
Tell us what the job is, who does it today, and what keeps going wrong. We will tell you whether it is a good place to start — and say so plainly if it is not.