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Wednesday, May 27, 2026
Solving Resource Management Challenges with AI
By
Riyaelza Pappachen
Solving Resource Management Challenges with AI

Solving Resource Management Challenges with AI

Diving into a small yet impactful problem in the tech industry – Guess what? The resource management problem! A good team creates its own path to the best deliverables. But the problem lies at the root –creating a good team.
At CCTech Hackathon 2025, Team Xstack (Tenstack) came out with a genius solution to this issue. Team Xstack, comprising Lavish Tyagi (Researcher, AI & Full-Stack Developer), Prateek Singh (Researcher, AI & Backend Developer), and Vedant Vedpathak (AI Developer), made their way through with this intelligent solution to tackle the problem of resource management. They set out with the goal of improving planning, allocation, and scalability in the management of engineering teams.
The Bigger Picture of the Broken Resource Management System
Today, many engineering organizations face the bottleneck of the manual resource management process. Owing to the greater inconveniences, it also adds up to higher costs and lower efficiency. Key observations made by team Xstack are:
  • Slow progress of SRS to Team Assembly:
    Understanding a team’s requirements, identifying the right skill set, conducting lengthy manual analysis, and finally reaching out to the right resources consume more time.
  • Lack of a Single Source of Truth for Workforce Data:
    Nonexistence of a single source for understanding and evaluating the resource availability, their updated skillset, or how well they are being utilized now. Managers heavily rely on endless spreadsheets, emails, and manual tracking. Which, of course, expires soon, making the info stale.
  • Incorrect resource alignment discovery:
    Often, true gaps are identified only after the project delivery begins. That means the clock has already started ticking, and any major changes need to be aligned with resources or skillset. This often sounds like a bizarre idea.
  • High Bench Costs from Poor Allocation:
    The most common issue witnessed today is that more engineers are on the bench, while project teams suffer from resource shortages.
Team Xstack’s Solution
Team Xstack emerged with an outstanding solution – CCTech Intelligent Resource Hub, an AI-powered command center designed to completely transform workforce management.
Deep Dive into the Intelligent Resource Hub
  • Strategic Consultant
    Think of it as a smart assistant you can actually talk to. Instead of manually analyzing data, you can ask questions and get clear, actionable insights instantly.
  • Real-Time Dashboard
    Everything you need is visible in one place—who’s working on what, how resources are being used, and where time or cost is being wasted. No more juggling spreadsheets.
  • Team Architect
    Building the right team doesn’t have to be a guessing game. The system generates well-balanced teams based on skills, depending on your efficiency or cost-saving, or growth requirements
  • Strategic Forecasting
    Our solution provides you with a clear picture of the requirements that your team might need over the next few years.
  • Workforce Planning
    The system identifies skill gaps early, and team members are suggested to upskill or recruit in time before it impacts the project.
from-srs-to-team-assembly
The Solution Tech Stack
The frontend has been created with Streamlit to provide an interactive UI that displays results in real time. The GPT-4o-mini model with custom prompt engineering for CCTech is used for the AI engine. A data layer was used to normalize and standardize diverse skill sets for advanced normalization. Plotly was used to visualize it. And a smart deployment logic for intelligent bench management.
platform-architecture
The Challenges & the uniqueness of the solution
Real-world data is unstructured and messy. There is a huge multi-talented pool of resources with a wide range of skills (C++, Python, AI/ML, domain engineering). This led to a necessity - data normalization. The team builds a data normalization layer capable of:
  • Handling inconsistent data formats
  • Standardizing skills across the organization
  • Enabling accurate AI reasoning
Prompt engineering was tailored to CCTech’s requirements, resulting in ~95% accuracy in skill matching and ensuring context-aware, reliable recommendations.
tangible-business-impact
What’s down the line?
Currently, our solution eliminates delays in team assembly and helps us achieve a significant reduction in bench costs through improved utilization. It also reduces recruitment expenses by suggesting proactive upskilling. The leadership gets the real-time visualization of ‘n’ right talented employees.
The platform is not just limited to CCTech. Its architecture is flexible enough to be extended to other engineering organizations facing similar challenges, making it a strong candidate for a scalable SaaS product.
Conclusion
The CCTech Intelligent Resource Hub is more than a hackathon project. It's a rethinking of the paradigm for how engineering companies manage talent.
Team Xstack's integration of AI, real-time data, and intelligent forecasting has proven to be a transformative solution for companies seeking to shift from reactive to proactive, optimized workforce planning.
About author
Riyaelza Pappachen
Riyaelza Pappachen is a dedicated Software Development Engineer in Test (SDET) at CCTech, where she works in the AEC (Architecture, Engineering, and Construction) domain with a strong focus on Autodesk ReCap. She plays a key role in ensuring the quality, performance, and reliability of the ReCap product through comprehensive manual and automated testing. She has expertise in identifying and resolving defects in ReCap workflows and development cycles
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