Case Study: Peertutor

As part of the partnership between cloudThing and PeerTutor, we were tasked with building a new application and learning platform that would disrupt and democratise the tutoring sector.

 

Who Are Peer Tutor?

PeerTutor was a platform idea based on the research of Dr Wayne Harrison, whose researched focused on using meta-analyses to introduce evidence based practise in schools. Principle to this was the idea that online peer group-based tuition strategies improved learning and results in exams.

PeerTutor’s platform was later successfully acquired by NCFE, an educational charity and leaders in vocational and technical learning, who added it to their portfolio of edutech companies.  They’ve over 170 years of education experience combined  with expert insights, and work with a network of expert collaborators to shape smarter solutions around the greatest learning needs.

Founded in 1848, they were born from the belief that no learner should be left behind

 

The Brief:

PeerTutor came to cloudThing having already built a proof of concept to launch their business; this comprised a peer-to-peer learning platform, based around live-lessons and virtual whiteboards, built with legacy web and database technologies.

However, they found their scalability was being limited by their technology choices and architecture, whilst the UX of the platform needed improvement to be truly consumer ready.  ​

They came to cloudThing because they were looking for a Technology partner who understood edutech and how to build hyperscale-ready, cloud software platforms.

 

What Would Success Look Like?

PeerTutors wanted to build a new highly-scalable cloud platform for the purposes of seed funding.​

​They had a concept for a new question-answer App to add to their business capabilities that was a hybrid of Snapchat and Uber – with Tutors waiting for learners to send their questions typically in the form of images and responding in the same way.

They also wanted to platform for a modern cloud architecture.

 

The Build:

cloudThing first went through a UX discovery process with the client to conceptualise the final application.   This discovery process allows experienced consultants to work with clients to find the match between art-of-possible and practical-to-implement.

 

A number of important design decisions were made:

  • To create a peertutors currency, which they called Gems; with a redeemable value in a tutor’s native currency
  • To distribute processing to a mobile app to reduce the platform operational costs
  • To use data science to help drive tutor and learner question and answer matching

 

cloudThing designed and built a highly scalable multi-cloud architecture with GCP and Azure; with features such as a SQL Server transactions ledger.  At the same time, we developed a React-Native mobile app for the new question and answer​ portal PeerTutor had requested with an integrated virtual learning platform to replace their live-lesson functionality.​

 

We also integrated AI-based live session moderation services to better automate the platform, increase efficiencies and reduces costs​ as well as integrating Azure Cognitive Search to give the platform a bot capability to auto-answer questions it had already seen before.

 

This platform build showcased cloudThing’s ability to build a Software 2.0 platform where the data is as much the solution as the code.

 

Technologies Used: 

  • Azure Cognitive Search,
  • Azure Cognitive Services,
  • Azure Functions,
  • SQL Azure,
  • GCP,
  • Firebase,
  • React
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    Case Study: aprais

    As part of the partnership between cloudThing and aprais, we were asked to rearchitect one of their most important applications,  so that it would provide a modern User Experience,  be more resilient, scalable, secure, as well as more cost efficient to operate.

     

    Who are aprais?

    aprais are the global pioneers in building stronger business relationships between organisations and their clients.

    Since establishing, they’ve advised the world’s leading marketers and agencies on more than 24,000 relationships, across 92 countries, in 13 different languages.

    That’s enabled them to build a large bank of data that allows companies to accurately and efficiently compare their business relationships with those of their peers.​

     

    The Brief:

    The aprais brief came in two parts, with the first involving an overhaul of their proprietary framework.

    aprais use that framework, with the huge amount of data they’ve collected and manage, to analyse organisations and their competitors using Azure as their data warehouse platform.

    cloudThing were asked to modernise this platform whilst also creating a consumer grade, responsive, Questionnaire App for their clients.

     

    What Would Success Look Like?

    At the end of the project aprais needed a consumer-grade Questionnaire App that would offer a responsive, modern web experience.

    The rearchitecture of their platform, from legacy to cloud-native, was to leave them able to leverage the benefits of Azure and Microsoft cloud technologies to incrementally upgrade and improve their platform, whilst keeping operational costs low.

     

    What we did:

    cloudThing’s engagement with aprais kicked off with a Bespoke Software Development project to replace their legacy Questionnaire portal with a modern UX React-based Web application with an Azure PaaS data backend.

    A full data migration was also required during the service transition.​

    ​cloudThings team of data engineers are currently assisting with updates to their Analytics and data processing engine to better optimise the performance of the platform to ensure the platform continues to operate securely, aided by our DevSecOps and security practises.

     

    Technologies Used: 

    • SQL Azure,
    • ADF,
    • SSIS,
    • Azure App Service,
    • Azure Functions,
    • React
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      Case Study: SupplyVue

      As part of the partnership between cloudThing and SupplyVue, we were asked to carry out a full end-to-end build with envisioning, UX design, engineering, on a new next-gen data processing platform with capability of processing billions of datapoints whilst being cost effective to operate and support.

       

      Who are SupplyVue?

      SupplyVue are an analytics and planning solution organisation that empowers their clients to improve services and reduce costs by synchronising their processes right across their supply chain network.

       

      As many companies suffer from poor visibility and understanding of the information across their supply chains, SupplyVue set out to better enable them to achieve a data driven, high performance supply chain that was both synchronised and sustainable.

       

      SupplyVue offers their clients a unique and powerful combination of capabilities including Monte Carlo simulation, genetic algorithms and smart heuristics.

       

      The Brief:

      SupplyVue had successfully developed a highly innovative product for the acceleration and empowerment of Supply Chain analytics, but it had found itself limited in its ability to grow due to legacy solution not being able to scale up to their fast-growing client base, and quickly increasingly data volumes.

       

      What Would Success Look Like?

      SupplyVue required their legacy Supply Chain analytics digital product (on Tableau over SQL) be re-platformed and re-developed to a next-gen platform.

       

      cloudThing agreed with them that the best course of action would be to migrate it to a modern data platform that utilised a React Web app including Synapse Analytics, Azure Data Factory, Data Bricks and Data Lake.

       

      This approach would allow us to offer SupplyVue Azure’s full data science capabilities within an elastically scaling solution; and cost recharge; and a modern DevSecOps development lifecycle that would enable them to build out and scale their product much more quickly and efficiently.

       

      What We Did:

      cloudThing started at the beginning of the journey with the client to carry out envisioning exercises, design User Journeys; to help the product owners visualise the solution.

       

      Once that stage of the project was finished; we moved to a development phase, implementing it with a full team approach comprising: Solution Architects, Data Engineers, Front End Engineers, UX designers, Software Testers, Delivery Manager

       

      To building SupplyVue’s next-gen apps, we used Databricks and Synapse Data Integration and Spark capabilities for quickly modelling and building predictive analytics solutions; allowing them to model millions of supply chain scenarios which would help planners understand the impact of decisions on their businesses supply chains; in time planners work with the platform to improved synchronicity in their supply chains, reducing costs and improving delivery.

       

      Technologies Used:  

      • SQL Azure,
      • ADF,
      • Databricks,
      • Synapse,
      • Azure App Service,
      • Azure Functions,
      • React
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        Case Study: Avery Weigh-Tronix

        As part of the partnership between cloudThing and Avery Weigh-Tronix, we were asked to resolve a host of technical debt issues and stabilise the codebase of an existing solution for future investment.

         

        Who Are Avery Weigh-Tronix?

        Avery Weigh-Tronix is one of the world’s leading suppliers of weighing solutions, with over 200 years of experience in their field.  They design, manufacture, market and service a broad range of high-quality industrial products and weighing systems.

         

        By drawing on the very latest research and cutting edge technology from around the globe, Avery Weigh-Tronix offers a product portfolio that’s second to none: providing business focused products and solutions under several of the industry’s most established brand names, including Avery Weigh-Tronix, Brecknell and Dillon.

         

        The Brief:

        Avery Weigh-Tronix were looking for a Technology Partner for their Exactrak product; to review for technical debt and stabilise their entire codebase for future development projects as well as onboard their application into our DevSecOps service for a more reliable and secure operation.

         

        Exactrak offers real-time vehicle tracking for UK Local Authorities, primarily focused on gritting vehicles. The data collected from each vehicle tracker is streamed live back to their platform to allow users to track vehicles, create new route navigations and perform route management tasks.

        This allows the customer to accurately forecast route journey time and salt deployment along those routes to generate costs savings through salt and fuel optimisation.

         

        What Would Success Look Like?

        When Avery Weigh-Tronix contracted cloudThing, they were running a legacy IoT application built over many years.  The codebase for the application supporting Exactrak needed to be secure, stable, resilient and ready for future investment.

         

        The Build:

        cloudThing first migrated away from Avery Weigh-Tronix’s legacy hosting in Rackspace to Azure where we could use the full data analysis and data engineering capabilities of Azure to create a more supportable, resilient solution.  We​ rebuilt large elements of the platform with Microsoft Well-Architected Framework principles, removing technical debt and updating legacy code libraries.​

         

        We then created a new React portal​ and implemented Irish OSM functionality and several, new geospatial features​ to enhance the product.  Once that was done, we merged several disparate customer codebases to create a unified data model for Avery Weigh-Tronix and ​migrated over 100m records from three databases into two to create a unified-view of Local Authority data for Highways England​.  Again this work ensured a stable foundation for future investment.

         

        Finally, we optimised the performance of the databases by a factor of 10; improving data ingress from hours to merely seconds, giving near real-time capabilities; that allow users of the product to offer significant SLA improvements for any operational issues experienced by their fleet.

         

        Technologies Used: 

        • SQL Azure,
        • ADF,
        • Databricks,
        • Azure App Service,
        • Azure Functions,
        • React
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