Huld takes a business-driven approach to AI & Data. We tailor domain expertise with computer science excellence to drive high impact with higher feasibility.
Huld takes a business-driven approach to AI & Data. We tailor domain expertise with computer science excellence to drive high impact with higher feasibility.
Huld takes a business-driven approach to AI & Data. We tailor domain expertise with computer science excellence to drive high impact with higher feasibility.
Data is readily available amongst any modern-day organization. Subsets of the ‘correct’ data are fuel for industrial AI solutions. Sufficient understanding of business domain and operations can create feasible solutions. Whether it being analytics, computer vision or A/B testing etc. The right set of domain expertise, computer science and mathematical knowledge are paramount. Initiatives come with a plethora of data wrangling solutions; however, it takes the right team to extract the ‘correct’ impact.
Data science is the art of extracting meaningful insights from data. While AI is any application that appears to emulate human performance. In practice, an AI can be trained on an organization’s own data or can be deployed pre-trained and tailored for the organization (transfer learning). While data science provides life blood to the AI applications. An AI trained with excellent data science techniques saves time and produces value.
We use Data Thinking to explore productive ideas that generate new business. Data Thinking is an agile, customer tested process as a solution for fuzzy or challenging starting points. The purpose is to convert experimental projects into a successful journey. Data Thinking activities are performed in conjunction with your team and tailored to your needs.
Results and benefits
Deliverables
Being data driven is not about adopting tools but nourishing data thinking culture. Everything starts with the growth of the teams.
The purpose of digital products and services is to bring concrete benefit to users, owners, and stakeholders. For example, a system that reads and analyzes the sensor data of a physical object can help anticipate needs for maintenance, or a digital diary that monitors the nutritional values of a diet enables optimizing the diet to meet the needs and goals of an individual user.
Security is often approached from a technical angle in software development. It’s the people who make the difference in security.