Building an enterprise-grade internal platform with AI
Overview
Industry
Location
Software and IT services
Poland
Technology Used
Azure Active Directory
Bitbucket Pipelines
CASL
D3.js
Docker
Express.js
Kubernetes
Material UI
Node JS
PostgreSQL
Prisma ORM
React
React Context
Vite
Zustand
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Project overview
As our company grew, there was a need to centralize tools such as employee data, time tracking, absence tracking and performance evaluations in a single, coherent platform.
The lack of a single, reliable source of information resulted in tangible costs; delays in decision-making, duplication of effort, inconsistent data quality and limited visibility for management. Available market solutions either covered only one area or required heavy customization and recurring license fees.
A decision was made to use an AI-augmented development team to build a platform that would solve internal tooling needs with a unified, extensible platform designed to grow with the business.
Client background
Software Mind is a global technology partner that provides companies with technical expertise and domain consultancy to accelerate digital transformations and drive strategic growth.
Goals
To design a scalable platform with modular extensibility so that we could easily add new modules without having to rework the core architecture. At the same time, we needed to deliver multi-layered security (authentication, authorization, input sanitization, audit trails) that protects sensitive organizational data and ensures privacy. In terms of process, the goal was to use AI tools and agents to reduce development costs by 70-80%, while maintaining full control over the product roadmap – without having to engage in vendor negotiations or being hampered by API limitations. Overall, we aimed to create a live organizational intelligence tool that shares real-time data about employees and projects for company leadership, project managers, the recruitment team and human resources.
Results
Reduced costs
Replacing a traditional 5–7-person team with one architect supported by AI agents.
Faster development
Delivering an MVP in 3-4 months, as opposed to 6-9 months.
Increased test coverage
Achieving over 90% coverage across units and integrations, including CI automation.
Greater transparency
Full documentation generated in parallel with code.
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