From diagnosis to deployment
Artificial intelligence consulting
At HitOcean we work with operations, IT and business teams to turn an automation idea into a system that delivers real value. We detect what fails, what fits your processes and what should be built first.
- They chose us to drive their growth
From opportunity to a system in production
We structure the consulting around three pillars that work together: one strategic, one technical and one operational.
Strategy and prioritization
We identify where AI can generate value, cross that information with technical feasibility and agree on what to build first.
Architecture and implementation
We define the architecture, integrate data and systems, train or adjust models and deploy to production.
Measurement and continuous improvement
We establish indicators, monitor performance and operate an iterative improvement cycle with your team.
Technology applied to real operations
Every project starts from a concrete management, logistics or support problem, and ends with a product that your team uses daily. Our credentials are based on products that operate in production.
What does an artificial intelligence consulting do?
Strategy
We analyze a process, identify where AI can intervene and define success metrics with you. We prioritize use cases that have economic potential and available data to train.
Architecture and MVP
We design the architecture, choose the technology and build an MVP in weeks. Then we sign an evolution roadmap and a data governance and compliance plan.
Professional approach
We don't sell projects just because they include modern technology. We propose AI when the context of your data and processes justifies it. If it doesn't apply, we say so.
Process by stages
A methodology with deliverables and advancement criteria
A technical partner to decide and execute
A single vision connects strategy, development, design and infrastructure. We don't delegate the result to a third party: we take responsibility for the product end to end.
Experience to take AI to production
+45 digital products launched
+50 projects delivered
+10 different industries
Own presence in 3 countries and experience with clients from different markets
Results that connect technology and operations
«Thanks to HitOcean, our clients can access critical information instantly. The experience is smoother, more efficient and closer.»
—Seidor
«With HitOcean, we achieved a solid integration between technology and business processes. Today, we have a more agile, robust system aligned with our objectives.»
—PAE
«The implementation with HitOcean improved our ability to anticipate critical events and prioritize with real data.»
—Geopark
Dig deeper before defining the scope
HitAI
AI for process automation
Criteria, examples and steps to identify processes worth automating with AI.
Read articleHitAI
Cybersecurity in your AI process
We accompany the process with data protection and security experts from the start.
Learn moreConsulting designed by those who also build
The team that advises you is the same one that designs, develops and operates software daily. When the consulting ends, you don't stay with a document: you stay with a working product.
We work with startups and companies with complex operations. We know when a lightweight solution is best, when a trained model is needed and when the best project is to do nothing.
Frequently asked questions about AI consulting
What is the difference between AI consulting and an implementation project?
Consulting begins with a diagnosis: we analyze processes, data and technical feasibility before writing code. Implementation builds the solution and takes it to production. We do both in stages, with verifiable deliverables.
How long does a typical AI consulting engagement take?
A comprehensive diagnosis takes between two and six weeks. If we then move forward with an implementation, an MVP is usually ready between six and ten weeks. Each stage has defined deliverables so the decision to continue is simple.
What do we need to provide as a company to get started?
Access to the documentation of the process you want to improve, to reference systems or data, and availability of the area managers. You don't need prior technical experience or an internal data science team.
What happens if the data is not ready to train a model?
We don't move forward with a model that has no foundation. We identify the gaps, define a plan to close them, and propose the most appropriate solution for the actual state of your data, even if it's simpler.
Do you work with mid-sized company budgets?
Yes. We adjust the scope of the consulting to a limited budget and prioritize use cases with fast returns. We start with a verifiable pilot and then decide how to scale.