Managing operational knowledge in large agribusiness organizations

One of Latin America's leading integrated agribusiness companies manages a vast amount of operational procedures, templates, and administrative documentation that support daily activities.

However, critical knowledge was distributed across static documents. Employees needing to confirm rates, find templates, or validate procedures often relied on internal administrative support.

This process created operational friction, delays, and the risk of using outdated documentation.

The Challenge: Administrative dependency and operational risk from fragmented information

Each internal query required contacting administrative teams to locate the correct document or confirm information.

This resulted in:

• A high volume of repetitive queries

• Operational dependency on support teams

• Risk of using outdated procedures

• Time lost on low-value administrative tasks

The cumulative impact was substantial:

• 150 queries per employee

• 7,500 hours lost annually in internal consultations

• 15 minutes average resolution time per request

This fragmented knowledge environment reduced productivity and increased operational risk.

The Solution: A conversational assistant that turns documents into living knowledge

To address this challenge, we developed TONY, an intelligent conversational assistant designed to transform static administrative documentation into accessible, real-time knowledge.

Instead of manually searching through documents, employees can simply ask questions in natural language and receive immediate answers sourced from official documentation.

TONY centralizes operational knowledge and makes it accessible through a conversational interface.

How It Works: LLM + RAG architecture for reliable, verifiable answers

The solution is built on an LLM architecture with Retrieval-Augmented Generation (RAG).

This approach ensures the assistant:

• Retrieves information directly from official documents

• Provides contextual responses in real time

• Generates answers grounded in verified sources

• References original documentation for accuracy

As a result, the system does not generate speculative answers, but instead acts as an intelligent interface to the organization’s internal knowledge base.

Expected Impact

Reducing administrative workload and unlocking productivity

Knowledge assistants like TONY have the potential to dramatically transform internal operations.

Industry examples demonstrate the potential impact. IBM’s AskHR achieved 94% automated resolution of administrative queries using generative AI.

Inspired by these results, the initial goal for TONY is to reach 80% query containment, enabling most internal questions to be resolved automatically within seconds.

This translates into:

• Faster response times

• Reduced administrative dependency

• Lower operational error rates

• Increased organizational productivity

From PoC to Product: Building the foundation for intelligent knowledge management

This initiative represents the first step toward a new generation of organizational knowledge platforms.

As the solution evolves into an MVP, the assistant could expand to include:

• Continuous learning from internal queries

• Integration with operational systems

• Automation of administrative workflows

• Context-aware recommendations

The long-term vision is to transform internal knowledge into a living strategic asset for the organization.