About
An engineering studio, not a consultancy with an engineering department.
Invictt AI designs and builds the AI, software and automation systems a business actually runs on. Small and senior by design — the same people who scope an engagement build it, rather than handing you between specialists.
01/Who you'd work with
The people who scope it are the ones who build it.
Invictt AI is an engineering studio, not a consultancy with an engineering department. The engineers who scope your project are the ones who build it — the alternative is a proposal written by people who'll never have to make it work.
The practice spans applied machine learning, computer vision and full-stack software engineering, because most real engagements are both an AI problem and a software problem, plus the integration work between them. Treating that as one discipline is a large part of what makes the delivery honest.
Founder & Principal Engineer
Engineering lead
Focus
- AI and machine learning — models, agents and automation
- Custom software — web applications, backend systems and APIs
- Retrieval and knowledge systems over real, messy data
- Integration with the systems businesses already run
- On-prem, cloud and hybrid deployment, decided per component
02/Principles
How we decide things.
01
You choose where it runs
On-prem, cloud, or a deliberate mix, decided per component. We build all three, so the recommendation isn't just whatever matches our own stack.
02
Boring problems pay better
Invoice entry, inbox triage, internal tooling — high volume, low glamour, measurable within a quarter. We'd rather build that than a demo.
03
Measured, not asserted
A result is a number on your data, or it's marketing. Every engagement ends with a measurement against the baseline — even when the honest answer is that we didn't beat it.
04
Humans on the exceptions
Full automation of an ambiguous task just automates the mistakes. We route genuine ambiguity to a person, with an interface built to make reviewing fast.
05
No lock-in
You own the code, the weights, the datasets and the documentation — built so your team can change a rule without calling us.
06
We will talk you out of things
Some of what gets asked for isn't worth building. Saying so in week one is cheaper for everyone than discovering it in month four.
03/Engagements
What working together looks like.
01
Understand
Week 1
We sit with the people doing the work and measure what it actually costs — before anyone mentions a solution.
02
Design
Week 2
A concrete solution design — what gets built, what stays as it is, and why — grounded in what week one measured.
03
Build
Weeks 3–8, typically
The system is built against your real data and real conditions from day one — never a demo dataset.
04
Integrate
Alongside Build
Connected to the systems you already run — CRM, ERP, databases, internal APIs — rather than becoming another disconnected island.
05
Automate
Alongside Build
The repetitive, rule-shaped parts of the work run themselves, with retries, guardrails and alerting on silent failure.
06
Deploy
1–2 weeks
A supervised ramp, not a switch. Volume moves across gradually while results are watched.
07
Scale
Ongoing, or not
Monitoring, drift review and capacity growth — on a retainer if you want one, or handed over completely if you don't.
What we don't do
- Staff augmentation. We deliver systems, not developers by the month.
- AI strategy decks. We will do an architecture review, but it ends in a costed design and a build, not a slide deck.
- Projects with no measurable baseline. If we cannot measure what the manual process costs today, we cannot tell you whether we improved it.
- Anything requiring us to hold your data indefinitely. Systems are built for you to own and run.
Across 25 offerings, the common thread is that each one has a number attached to it.
Worth a conversation?
The first call is a scoping conversation, not a pitch. Bring the process that is annoying you most.