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We’ve spent over a decade building and deploying production AI systems.
Our team augmentation service places those same engineers directly inside your team
Professional, deep technical knowledge, innovative solutions, always available to answer any questions, and ultimately delivered strong results on time.
Marko Velić, Director of Engineering @ Photomath (Google)This is the honest list of situations where we add the most value.
If none of these fit, we’ll tell you on the first call.
Can’t hire senior AI engineers fast enough to hit product deadlines
Have strong tech teams but lack deep ML or AI expertise
Want execution power, not just advisory – engineers who build and deploy
Need to scale AI output without adding permanent headcount
Started an AI project only to find it’s more complex than expected
Every engineer at Velebit AI has worked on live production systems. They’ve seen what breaks,
what scales, and what wastes six months. You get that knowledge from day one.
Turns business questions into rigorous experiements – forecasting, anomaly detection, A/B testing, and actionable insight generation.
Builds the infrastructure that makes AI reliable – model serving, pipelines, monitoring, retraining and cloud-native deployment.
Designs, trains and deploys custom ML model. Owns the full experiment lifecycle from data to production API.
Builds production-grade LLM applications – agents, RAG pipelines, tool-use systems and evaluation frameworks.
Specialized in image classification, object detection, segmentation, and OCR for real-world product and industrial use.
Deep expertise in text classification, sentiment analysis, semantic search, content moderation, and multilingual NLP.
Most augmentation services match you to a profile.
We introduce you to a colleague.
One is for teams starting from scratch. One is for teams that need reinforcement.
Both come with the same engineers.
For teams with no AI capability yet or one that needs to scale fast.
We staff a full AI team (ML engineers, MLOps, and AI research) where needed.
You get a team that owns AI delivery end-to-end, from problem framing and data work through
to a model running in production.
Best fit when:
You don’t have an in-house AI team
You’re starting or scaling AI initiatives
You need end-to-end execution
For teams that already have AI in-house but need additional senior AI execution.
We include senior AI engineers into your existing team to extend capacity
and bring specific expertise.
Best fit when:
You have an AI or data team in place
You’re hitting complexity or delivery bottlenecks
You need specific AI expertise
AI development company first.
AI consulting on top.
Retail, media, automotive, e-commerce, manufacturing, pharma. Each one shaped by the constraints of real data, real timelines and real users. What we recommend, we’ve built before, usually more than once.
Most consultants give you the strategy. Most engineers give you the build. We do both, which means the strategy is shaped by what’s actually buildable, and the build is shaped by what actually moves the business.
Discovery, strategy, education, build, deployment, maintenance. We’ve done all of it, sometimes in sequence, sometimes in combination. You don’t need to work with a different partner for each phase.
We’re not a company where the senior partner sells the work and juniors deliver it. The people in your first conversation are the people in your codebase. That keeps the quality consistent and the communication honest.
What happens after you book a call
We understand your team structure, current stack, the AI challenge you’re solving, and the skills gap you need to fill.
We propose the right profile – or combination of profiles – with specific experience relevant to your domain and problem.
Engineers onboard to your tech stack, meet the team, and align on norms. We aim to have them contributing meaningful work within a week.
Engineers operate as true team members – building, reviewing, and iterating. Scale up, scale down, or extend as your needs evolve.
What teams around the world say about working with us
Velebit AI has developed our whole data engineering infrastructure and deployed the AI models needed on a large scale for our classified ads business. The team excels at timeline and budget management, and they offer great communication. Velebit AI’s accuracy is impressive; they deliver what they promise.
Igor Sobota, CEO @ Njuškalo
Photomath worked with Velebit AI to support our computer vision domain, and they provided us with a lot of value along the way. Professional, deep technical knowledge, innovative solutions, always available to answer any questions, and ultimately delivered strong results on time. It was a pleasure to work with their team.
Marko Velić, Director of Engineering @ Photomath (now Google)
I was impressed by how enthusiastic Velebit AI was about data science. They read scientific papers because they were so eager to learn. I’d recommend them for any advanced task related to NLP, deep learning, and similar data science models and AI in general.
Ana Meštrović, Professor @ University of RijekaA dedicated AI team is a full team (ML engineers, MLOps, and AI research as needed) that owns AI delivery end-to-end for companies with no in-house AI capability. Senior AI augmentation includes one or more senior AI engineers directly into a team you already have, to add capacity or fill a specific skills gap.
Yes. In both models, our engineers work inside your existing tools, infrastructure, and sprint process rather than asking you to adopt new systems. For dedicated teams, we integrate alongside your frontend and backend teams; for augmentation, we join the team and workflow you already run.
We staff senior AI/ML engineers with hands-on production experience. Augmentation specifically exists to bring senior-level expertise (e.g. production ML systems, computer vision, MLOps, etc) into teams that are short on it.
Every case study below started with the same thing:
a team that needed more AI depth than they had
