We do not design black boxes to charge you expensive maintenance fees. We will make sure that you understand our solutions and get the know-how you need to maintain and improve yourself, with or without us.
Simple is better. AI is full of over-engineered and obscure solutions that slow down the adoption of artificial intelligence. Keeping things simple is hard and require actual knowledge and previous thinking, research and planning.
We will never compromise quality. A single carefully made solution which successfully add value is better than a thousand botched, half-made systems.
1. AI planning and strategy
Get the right assessment before jumping into the AI race. Avoid common mistakes which will cause your AI strategy to derail and underdeliver. Let us help you to make things right from the beginning, from Data Engineering to Machine Learning deployment.
2. Data Engineering
Lots of Data? We are used to work with Big Data workloads using frameworks like Hadoop or Spark, and successfully built and deployed AI at scale.
3. AI model designing
We are excellent modelers with business experience in many sectors and real world use cases using a broad range of technologies, from classic Machine Learning to Deep Learning. And the best of all, we have principles crystal clear independently of technology.
4. AI deployment
Most companies fail while deploying their models from prototype to production. Did your company spend a fortune hiring a horde of PhDs and only got a bunch of serialized R models with no actual value in return? We can help you.
Data for Equity
We offer Data services as equity investment in ideas and companies who need experienced Data
Scientists and Engineers to achieve their goals. It means we can work for you for a % of your company.
At this moment and depending on your company needs, we offer investment in Seed stage with tickets of:
Our work consist in developing Data solutions, advising on AI adoption and more. We also work for top
companies worldwide as independent consultants.
In case you are interested: