The challenge

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Connectis has been connecting the most suitable IT experts to its clients' projects as part of its IT Outsourcing service. We are well aware of the importance of skilfully matching candidates to the specifics of a project. The high quality of this process was the result of years of experience and know-how developed by a specialised in-house team.

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The increase in the number of projects and candidates required a transformation of processes. A solution was needed to support the work of the Connectis team, ensuring that the high quality of the matching was maintained while making it more scalable. This led to the creation of a dedicated internal system that would streamline the process of sourcing and matching experts to project bids.

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The solution

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The first challenges of the Matcher project were to create a unified data object - a digital candidate profile - which included:

• Integrating the data:
  • Combining data from different systems (CRM, ATS, internal systems)
  • Unification of data format
  • Creating a central repository for candidate and project data
• Automating the process of matching candidates to projects:
  • Development of algorithms to match candidates to projects
  • Using AI to analyse CVs and offer descriptions
  • Creating a system to automatically notify candidates and clients of matches
• Creating a user interface:
  • Creating an intuitive interface for candidates and clients
  • Enabling the Connectis_ team to easily manage candidate profiles and applications
  • Enabling clients to easily search and view candidate profiles
• Integration with back-office systems:
  • Automating the flow of information between the Matcher system and other internal systems (including CRM)
  • Real-time updating of candidate and project data

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The implementation project was multifaceted and highly complex. At Connectis_, we were well-versed in the challenges of implementing complex implementations, as our experts had been facing such challenges for years as part of our IT outsourcing service. 

We engaged our experienced experts from various areas to execute the planned tasks: 

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Data:

• Collection and integration of candidate data from various sources (CVs, LinkedIn, company profiles)
• Building a database of candidate profiles
• Standardisation of data format and construction of a unified candidate profile with full history and preferences
• Analysing data to identify trends and patterns in candidate profiles to validate their degree of fit with projects and to predict the degree of interest in other projects undertaken by Connectis_ clients

AI:

• Development of an algorithm to match candidates to projects based on candidate profiles and project requirements
• Refinement of the algorithm based on matching performance data
• Use of ML to predict the suitability of candidates for specific projects and the likelihood of success in a project 
• Algorithms to support the process of recommending candidates to the most matched projects

Cloud:

• Scalable infrastructure for storing and processing large amounts of data
• Ensuring data security and availability
• Ability to easily access the system from any location and device - for both the Connectis_ team and clients

Application Engineering:

• Automation of back-end processes such as integration with CRM systems
• Development of an intuitive user interface - for the Connectis_ team and customers
• Continuous improvement and development of the platform based on data and feedback

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Technologies used:

• Programming languages: Python, Java
• Frameworks: Django, React
• Cloud: AWS
• Database: MongoDB
• AI tools: TensorFlow, spaCy

The result

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The implementation of the Matcher project has delivered a number of benefits for Connectis_ and clients, including:

• Automating the matching process has resulted in a significant reduction in the time required to identify the most suitable candidate, leading to enhanced customer satisfaction. On average, this time has been reduced by 20-40%, with some roles experiencing a reduction of up to one hour!
• The use of AI to analyse candidate profiles and job descriptions has enhanced the quality of matching candidates to projects, thereby reducing the risk of errors in matching candidates to projects
• Increased satisfaction - both the Connectis_ team and clients were pleased with the system's ease of use and speed, which led to an increase in NPS
• Streamlining the process of matching candidates to projects strengthened the company's position in the market, which contributed to the attraction of new clients and candidates