Kala AI (Startup)

Bringing AI-Powered Answers to Internal Communications: The Development of Kala AI

Context:
As organizations grow, managing internal information and answering routine employee questions becomes a growing challenge—especially for small and mid-sized companies without large HR or IT support teams.

Recognizing this gap, Dink was tasked with developing an AI-powered internal knowledge assistant that could help employees quickly find relevant answers within company documents—without adding more workload to HR and administrative teams.

The project resulted in Kala AI, an internal communications tool designed to make company knowledge easily accessible through conversational search.

Challenge:
Building an AI solution for internal document search presents unique challenges:

• Ensuring that answers are accurate, context-aware, and traceable to source documents

• Respecting user-specific access permissions, making sure employees only receive answers they’re authorized to see

• Creating a fast and intuitive user experience that integrates seamlessly into existing company workflows

• Managing document ingestion and version control to ensure answers are always based on the latest content

• Ensuring data privacy and security—especially critical for HR documents and company policies

Unlike public AI chatbots, this solution needed to operate strictly within the boundaries of internal, HR-approved content.

Objectives:
The core objective was to build an AI-driven internal knowledge assistant that could:

• Allow employees to ask questions in natural language via a simple search bar

• Return relevant answers that cite the exact source document, page, and paragraph where the information is found

• Respect user permission levels, showing different content based on user roles

• Support document updates and version control without requiring complex reconfiguration

• Be deployable for small and mid-sized companies, offering value without requiring enterprise-level infrastructure

The Dink team worked closely with the product stakeholders to balance AI capabilities, user experience design, and enterprise-level privacy standards.

Development Approach:

To meet these goals, Dink’s Brazilian engineering team implemented:

• A Retrieval-Augmented Generation (RAG) architecture, ensuring the AI could generate helpful answers while anchoring them in specific source documents

• A document ingestion pipeline capable of parsing PDFs, DOCs, and other formats for structured retrieval

• Role-based access controls, integrated with company user management systems

• A web-based admin dashboard for HR teams to upload and manage internal documents

• Front-end interfaces that made the AI accessible from both desktop and mobile browsers

Agile delivery cycles allowed for constant user testing and feature validation throughout the build.

Results Achieved:

• Substantial reduction in repetitive HR and IT queries, freeing up internal teams for more strategic work

• Positive user feedback on speed and accuracy of answers

• Successful deployment in small and medium-sized companies with lean administrative teams

• Ongoing user adoption and satisfaction, thanks to a simple interface and search accuracy tied to source documents

• Full alignment with internal data privacy and access control policies

Conclusion:
The development of Kala AI reflects Dink’s expertise in combining cutting-edge AI technologies with real business needs.

By understanding both the technical and operational challenges of internal communications, the Dink team delivered a solution that makes accessing company knowledge faster, easier, and more secure for growing organizations.

For companies looking to integrate AI in meaningful, business-focused ways, Dink offers the expertise to turn ideas into scalable, real-world solutions.