Ergobyte keeps step with the rapid evolution of information technology, especially what concerns application platforms, development tools and database servers. The scope of tools and languages that we can use for development is unlimited. Our talented team is always open to new researches and approaches in the IT world.
Ergobyte's developers know how to adopt and ramp up emerging programming technologies quickly to execute the most ambitious projects and deliver the right results in terms of efficiency, performance, interoperability and user experience. With tools for collaborative development, functional testing, performance testing and performance monitoring across APIs, mobile, web and desktop, they create great applications by ensuring quality throughout every step of the lifecycle.
- Expert Systems
- Semantic Modeling
- Machine Learning
- 500.000 Lines of Code
- Continuous Integration
- Vendor Neutral
- Digital Health
- Smart Farming
- Management SaaS
Over the last ten years, Ergobyte has devoted its research efforts to design and develop intelligent systems that imitate human thinking. Our expert systems employ two crucial components: the knowledge base and the inference engine. We focus on the digital health and smart agriculture domains by addressing human medication therapy and cultivation pest management, respectively.
Semantic Knowledge Base
It is the repository where all domain-specific data and association rules are collected, organized and stored. Both factual (scientifically proven) and heuristic (experience based) knowledge is collected to achieve accurate reasoning. Data is being collected, aggregated, cleansed and stored in a multitude of automated ways. Association rules, on the other hand, are curated and validated by field experts.
It collects the users input and interprets the facts contained in the semantic knowledge base to reach appropriate answers. Reasoning is done either by using if-then rules, or by balancing bayesian networks.
Thanks to its technical superiority, the reasoner's logic and inner workings are structured in a way that each result can be formally proven by tracing logical steps back up to the authoritative material. This interpretable reasoning allows the user to verify and understand the produced outcome.