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.
Challenges
- Multi-level access. The software contains an enormous amount of data, and access to this information has to be moderated.
- 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.
- 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.
Our input
Technologies
we used
.NET
MongoDB
Elastic Search
Kafka
Redis
Kubernetes
AWS S3
AWS CloudFront
AWS Cloudwatch
React
AWS LambdaOur 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.
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.
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.
The cooperation is still ongoing with further plans on the team expansion and growth.
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