The diagram below gives a high-level overview of the structure of the Skill Engine and its interactions:
The Skill Engine has a layered design, deployed within a virtual private cloud. This way, only the Skill Engine API itself can be interfaced with from the outside world, and even this communication can be tightly regulated with measures such as IP whitelisting. Security measures can be controlled per individual customer.
The Skill Engine has a concurrency limiter that limits the number of
requests that are active at any given time to 10 per customer. Excessive
requests will result in an error response with status code
Central in the system, you can find the Skill Engine Core - this is the AI brain behind the skills intelligence in the Skill Engine API. The Core is entirely stateless and can therefore be leveraged across tenants, making the system more scalable and robust. The Skill Engine Core communicates with the Vacancy Data Lake, as well as using the Google Vision API to convert PDF documents into text.
The Core communicates with the Vacancy Data Lake, which aggregates and analyses vacancies scraped from public sources. For example, this allows the Engine to learn about skill trends, upcoming functions... Importantly, this data lake is used exclusively on public data and does not get into contact with customer information.
The next layer up, still inside the TechWolf VPC, is the Skill Engine API. This API is responsible for translating the domain-driven language offered by the API into the technical one used for interfacing with the core efficiently. In addition, the Skill Engine API is where customer data lives: it connects to a database that stores the skill profiles for this customer. The only way to interface with the Skill Engine from the outside is through the Skill Engine API, typically done with connectors that plug into your existing HR and knowledge systems. To offer maximal data control, data is pushed to the Skill Engine API (using triggers inside these connectors), rather than being pulled at the Skill Engine's initiative.
Data for different customers is stored with logical data separation. All data is encrypted both at rest (AES-256) and in transit (SSL/TLS 1.2 or higher), with the database only being accessible from within the TechWolf virtual private cloud.
Our API is built on open standards: we use a RESTful API design, described with detail through an OpenAPI specification. Each of these aspects enables you to build a connector between your system and the Skill Engine with ease.
On top of this well-documented interface, we assist our customers in building connectors that bridge the gap between the Skill Engine and any popular HR, knowledge sharing, and communication systems. While these are currently in their early access stage, they will be open-sourced in the future.
The following services form the backbone of the Skill Engine:
AWS as the underlying cloud platform, primarily with the following services:
- EC2 for compute instances.
- RDS for managed databases.
- S3, Glue, Athena, and Sagemaker for the Data Lake.
- Auth0 as our identity and authentication provider.
- Google Vision to get the text from documents. This is optional as we have our own in-house solution, but can improve performance. Google Vision can be turned off on request.
Each of these services only processes information for TechWolf inside the European Union.