Production AI systems, and the teams to run them
Lighthouse AI is an AI and MLOps consultancy. We ship machine-learning systems to production. We also help companies set up their own AI function, from the first hires to the MLOps practices their engineers need once we leave.
What we do
From first hire to production system
Whether you are starting from zero or scaling an existing team, this is the work we take on.
Build Your AI Department
We set up an AI/ML function from the ground up: org design, roadmap, tooling and governance. The aim is an AI capability that stays inside your business after the first project ends.
Talent & Hiring
We source ML engineers, data scientists and MLOps specialists, vet them technically and onboard them, so the team fits your stack and your domain.
Process & Procedures
We define the standards that make ML work repeatable and safe. That covers the model lifecycle, experiment tracking, review gates and data governance, plus compliance-ready documentation.
MLOps Enablement
We bring your existing team up to speed on current MLOps practice through hands-on workshops and pairing. We cover CI/CD for models, orchestration, monitoring and continuous training.
End-to-End Delivery
We design and ship the whole pipeline, from raw data through production inference to automated retraining, on Google Cloud or AWS. We build it to scale and to be observable, and we keep it cost-efficient.
Solution Architecture
We design serverless and microservices architectures for AI workloads on Google Cloud and AWS. Scale, reliability and predictable cost are designed in from day one.
Who we are
Senior-led, with specialists on call
Lighthouse AI is a senior-led practice. The engineering is deep and hands-on, and specialists are on call when a project needs to scale up.
Our founder
Founder & Principal AI/ML Engineer
Our founder is an engineer by training, with an MSc, and built a career at large engineering companies in Singapore and Germany. They have worked with Python since 2014, writing research code and numerical solvers for demanding engineering problems: hydrodynamics (wave resistance and vessel response/RAOs), PID control for the dynamic positioning of offshore structures, and Monte Carlo simulations for design operational loads. In 2019 they moved into AI and machine learning professionally.
That engineering background shapes how we work. We approach AI the way serious engineering is done, grounded in the data and the numbers. Formerly a certified Machine Learning Engineer and Data Engineer.
At a glance
- MSc in Engineering
- 10+ years with Python (since 2014)
- AI & ML professionally since 2019
- Former certified ML Engineer & Data Engineer
- Experience across Singapore, Germany & Bulgaria
- Numerical modeling: FEM, Monte Carlo & PID control
- Also fluent in VBA, including a FEM truss solver in Excel
How we scale
Lighthouse AI runs as a lean practice. For larger engagements we bring in AI and data professionals we trust and have worked alongside on past projects. You get experienced specialists matched to your project, without the overhead or hand-offs of a big agency.
Our work
Client work
Work for a client in marketing: what they needed and our part in it.
Creative Optimization Models & MLOps Pipelines
2026 – PresentA US marketing company wanted its ad creatives to perform better without relying on guesswork. We are building the models that predict and optimize creative performance, along with the automated pipelines that keep them accurate as new data arrives, so the system keeps improving in production.
FAQ
Common questions
Short answers about who we are and how we work. No AI background needed.
What does Lighthouse AI do?
We are an AI and MLOps consultancy. We build machine-learning systems that run in production for our clients. We also help companies set up their own AI teams, which covers strategy, hiring, delivery and training the engineers.
Can you build an AI department from scratch?
Yes. We define the roadmap and processes, hire and vet the right people, and put the tooling and governance in place. The goal is an AI capability that stays in-house.
Which cloud platforms do you work with?
Google Cloud and AWS, including their managed ML platforms, Vertex AI and Amazon SageMaker.
Do you help our existing team adopt MLOps?
Yes. We run hands-on workshops and pair with your engineers on modern MLOps: CI/CD for models, orchestration, monitoring and continuous training. The aim is that they can own the systems after we leave.
What kinds of AI problems have you worked on?
Ad-creative optimization. For a US marketing company we are building models that predict and optimize how ad creatives perform, plus the pipelines that keep them accurate as new data arrives.
Where are you based and who do you work with?
We are based in Varna, Bulgaria. Our clients are international, including companies in the United States and Europe.
Get in touch
Tell us what you are working on
Whether you are starting from scratch or scaling an existing team, send us a few lines about it. We will get back to you quickly.