Tico

Level-based Scalable CRM Platform That automates retail workers workflow

Tico is a private automotive CRM and CMS platform that enables the retail workers of automotive industry manage the warehouse and create reports on completed retail offers. The platform unites different branches for tenants that use the software, enabling filters based on location or other different factors. It creates a vast network of thousands of stores that belong to different auto parts and vehicles retail chains such as Stellanis.
  • Location Europe
  • Industry Automotive
  • Team Size 4 people
  • Duration 2+ years
  • Budget $350K
Case mobile app interface

Challenges

tico app mockup
  1. Multi-level access. The software contains an enormous amount of data, and access to this information has to be moderated.

  2. Fast decision-making. The software was already on the market when we decided to update from SQS, which was used in the software previously, to Kafka. The software needed to be modernises quickly, as it already was widely distributed on the market.

  3. Synchronisation. Dense volumes of data combined with quick and parallel data uploading made it complex to synchronise the development.

Solution

For Tico, our objective was to aid our customer in creation of the seamless platform with user-friendly AI, flexible infrastructure, and powerful data management.

To ensure that our customer’s data is secure, we had to implement level-based data access and enable the system’s users to add their own roles with access distribution.

We used Kafka, which is predominantly used for streaming platforms, as it is ideal for quickly changing and updating Tico in real-time.

These solutions among others enabled Tico to achieve a soaring number of over 3,6K stores registered in the platform.

tico app mockup

Our input

  • Back-End Development

  • Front-End Development

  • UI/UX Design

  • Consulting

  • Project 
 management

App functionality

tico functionality
  • Dashboards

  • Data Analytics

  • Data Processing

  • Data-Based Access

  • Employee Profile

  • Order Reporting

  • Data-Based Search

  • Contact Management

  • Sales Process Automation

  • Inventory Management Automation

how we did it

  • Of uploaded data

    6+GB of data connected to the order processing was uploaded to the server during our cooperation.
  • years of partnership

    Of stable and ongoing partnership and potential team expansion.
  • Modern Technologies

    Our team enabled modernisation for the software to keep it streamlined and updated.
  • Branch-based level access

    Each store added to the CMS can create their own branches with users separated by level- based access for extreme data protection.
  • Constant growth

    The customers’ business and their software is under the path of the constant expansion. Now, we’re working on new functionality and upscaling the team.
  • Stores are using the Platform

    Over 3,6K stores are currently using this CRM/CMS solution to manage their warehouse, automate the sales’ team workflow, and improve the data security. Among platforms’ clients are stores established by the headliners of automotive industry such as Stellantis and Smart Europe.

Technologies
we used

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    .NET

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    MongoDB

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    Elastic Search

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    Kafka

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    Redis

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    Kubernetes

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    AWS S3

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    AWS CloudFront

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    AWS Cloudwatch

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    React

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    AWS Lambda

Creation Process

  • Discovery phase

    Our team conducted research and detailed consultation, based on which we decided on the appropriate team configuration. DashDevs also proposed the functionality we can add to the application based on business needs and requirements of the client.

    1
  • Team composition

    We created a team to assist our customer in a joint work on the project. The flexibility of the cooperation model allows the customer to add new specialists to the team now, when the company is set of the path of expansion.

    2
  • development

    Mostly, our team was in charge of the back-end development. Our team enhanced the functionality by working on creating advanced data-processing mechanisms. We connected the software to cloud servers. We also united with the customer’s team to migrate the software to Kafka from SQS.

    3
  • Support and Further Development

    The cooperation is still ongoing with further plans on the team expansion and growth.

    4

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