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Your nearest office- Sri Lanka
Fortude (Pvt) Ltd
146 Kynsey Road, Colombo 7, Sri Lanka
Email – talk-to-us@fortude.co
Phone – +94 11 453 1531
Every day, we bring together diverse perspectives, strong leadership and responsible thinking to build a business that creates lasting value for our clients, people and communities.
Your nearest office- Sri Lanka
Fortude (Pvt) Ltd
146 Kynsey Road, Colombo 7, Sri Lanka
Email – talk-to-us@fortude.co
Phone – +94 11 453 1531
of organizations are experimenting with AI agents
of AI applications by 2028 will leverage multi-agent systems to drive more autonomous and scalable outcomes.
cost reduction in customer operations achievable through the adoption of agentic AI.
of organizations are experimenting with AI agents
of AI applications by 2028 will leverage multi-agent systems to drive more autonomous and scalable outcomes.
cost reduction in customer operations achievable through the adoption of agentic AI
Built on a robust AI foundation, these coordinated agents go beyond answering questions to execute tasks, orchestrate workflows, and anticipate business needs across the enterprise.
This agent connects directly to ERP and CRM systems, enabling users to securely access and act on data from their own systems.
This agent integrates internal business data with external market signals, such as weather and emerging trends, to automate SKU-level demand forecasts and provide data-backed purchase order recommendations.
By proactively assessing risks across the entire retail network, this agent identifies stock imbalances and recommends real-time redistribution steps to ensure products are in the right stores at the right time.
A self-service data agent that retrieves relevant data on demand and presents it in a format tailored to user needs.
A foundational engine that powers enterprise-wide workflows, from HR self-service to IT ticketing, using a Retrieval-Augmented Generation (RAG) framework.
The agent continuously monitors and cleans high-volume, unstructured feedback from platforms like Facebook and Google reviews, using AI to classify sentiment and remove non-authentic noise.
It categorizes public perception into specific business areas such as pricing or product quality and uses visual dashboards to flag emerging trends, allowing leadership to move from reactive “firefighting” to proactive brand management.
Built on Microsoft Azure AI Foundry, these coordinated agents go beyond answering questions to execute tasks, orchestrate workflows, and anticipate business needs across the enterprise.
This agent connects directly to ERP and CRM systems, enabling users to securely access and act on data from their own systems.
A self-service data agent that retrieves relevant data on demand and presents it in a format tailored to user needs.
A foundational engine that powers enterprise-wide workflows, from HR self-service to IT ticketing, using a Retrieval-Augmented Generation (RAG) framework.
This agent integrates internal business data with external market signals, such as weather and emerging trends, to automate SKU-level demand forecasts and provide data-backed purchase order recommendations.
By proactively assessing risks across the entire retail network, this agent identifies stock imbalances and recommends real-time redistribution steps to ensure products are in the right stores at the right time.
The agent continuously monitors and cleans high-volume, unstructured feedback from platforms like Facebook and Google reviews, using AI to classify sentiment and remove non-authentic noise.
It categorizes public perception into specific business areas such as pricing or product quality and uses visual dashboards to flag emerging trends, allowing leadership to move from reactive “firefighting” to proactive brand management.
See how our agents unify ERP, CRM, and enterprise data to surface real-time insights, automate decisions, and coordinate actions, empowering every role to move from question to execution instantly.
Unlike reactive tools, these agents use complex decision-making frameworks to perceive their environment, identify issues (such as inventory imbalances), and take proactive actions to achieve specific goals.
They operate within a multi-agent system (MAS), where specialized agents, such as the Signal-Based Forecasting Agent and the Inventory Levelling Agent, collaborate and negotiate to solve complex, multidimensional enterprise problems.
Using a Model Context Protocol (MCP), the agents act as a unified interface that interacts securely and contextually with core enterprise systems like Infor M3 ERP and CRM using natural language.
Unlike reactive tools, these agents use complex decision-making frameworks to perceive their environment, identify issues (such as inventory imbalances), and take proactive actions to achieve specific goals.
They operate within a multi-agent system (MAS), where specialized agents, such as the Signal-Based Forecasting Agent and the Inventory Levelling Agent, collaborate and negotiate to solve complex, multidimensional enterprise problems.
Using a Model Context Protocol (MCP), the agents act as a unified interface that interacts securely and contextually with core enterprise systems like Infor M3 ERP and CRM using natural language
Turn days of manual analysis into seconds with AI-driven insights and proactive recommendations.
Eliminate system silos and repetitive tasks with a unified AI interface across business functions.
Detect inventory risks, financial exposure, and ERP impacts before they escalate.
Maintain full data containment with role-based access and secure, compliant AI architecture.
Turn days of manual analysis into seconds with AI-driven insights and proactive recommendations.
Eliminate system silos and repetitive tasks with a unified AI interface across business functions.
Detect inventory risks, financial exposure, and ERP impacts before they escalate.
Maintain full data containment with role-based access and secure, compliant AI architecture.
Agentic AI goes beyond answering questions. It can make decisions, coordinate workflows, trigger actions, and proactively identify risks or opportunities across enterprise systems.
Charlie uses a secure Model Context Protocol (MCP) layer to interact contextually with ERP APIs, enabling natural language access while maintaining governance and security.
Yes, they are designed for enterprise environments, supporting multi-system integrations, structured and unstructured data sources, and role-based access control.
Transform insights into action with agentic AI
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