Background in Rails
Experience in Elixir
Working on a platform that has been reviewed by Jose Valim (the creator of Elixir) and is retained as a consultant for code optimisation.
The chance to be in charge of a production launched platform engineered fully on Elixir.
To creatively optimise and build new products.
To take a lead role in a business which has already been valued at over $10m in only a year of operation.
Co-founder: Jordan Shlosberg
Senior Python Developer: Eugene Yalanskyi
Developing new features and maintaining existing features
Bringing our codebase in house
Develop using TDD
Collaborate with other members of the team
Taking a proactive part in improving productivity and efficiency of the team as himself/herself
Take part in architecture decisions
Technologies we use:
CRM — Elixir / HTML / CSS
Conference call microservice — Django / Python / Twilio
Expert Messenger — Elixir / HTML/ CSS
Recommendation engine — Django / Python / React
Transcription — Django / Python / Google speech
Payments — Django / Python / Transferwise
Booking Engine — Django / Python / Outlook API
Dashboard — Django / Python / React
Back End: Elixir
Front End: basic, SCC, HTML, CSS
Microservices: Django, Python, some React
The proSapient platform allows our clients to seamlessly connect to Industry Experts around the globe whether you need a 3 hour consultation or simply to ask one question.
Our platform is built to solve all current issues inherent in old fashioned Expert Networks delivering a fully automated service including free transcripts, automated booking and a machine learning sourcing process providing the right experts at the right time with minimal effort.
Our clients are typically Private Equity, Asset Management and Management Consultancy
For example, our client Apollo Private Equity is buying a stake in Adidas. As part of their due diligence, they would like to speak with former executives from Adidas and current executives. The proSapient platform would locate and connect Apollo to those experts via conference calls (Twilio Microservice) and an inbuilt messenger (Elixir). IT also provides transcripts (Google Speech) and recordings (Twilio).
We heavily use AI and ML in order to find experts with a recommendation engine that matches the keywords from a project to keywords in our database of experts (Python).