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of AI applications by 2028 will leverage multi-agent systems to drive more autonomous and scalable outcomes.
22%
cost reduction in customer operations achievable through the adoption of agentic AI.
62%
of organizations are experimenting with AI agents
70%
of AI applications by 2028 will leverage multi-agent systems to drive more autonomous and scalable outcomes.
22%
cost reduction in customer operations achievable through the adoption of agentic AI
Offerings
Agentic AI ecosystem
From insight to action across the enterprise
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.
Model Context Protocol (MCP) for Infor M3
Connecting enterprise systems for secure, seamless access
This agent connects directly to ERP and CRM systems, enabling users to securely access and act on data from their own systems.
Signal-based Forecasting
Predict demand with greater accuracy
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.
Inventory Leveling
Balance stock across the retail network
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.
CharlieX (Insights & BI Agent)
Turning business data into actionable insight on demand
A self-service data agent that retrieves relevant data on demand and presents it in a format tailored to user needs.
Charlie-One (RAG intelligence engine)
Powering smarter workflows with enterprise-wide intelligence
A foundational engine that powers enterprise-wide workflows, from HR self-service to IT ticketing, using a Retrieval-Augmented Generation (RAG) framework.
Automated Feedback Synthesis
Turn customer feedback into usable insight
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.
Actionable Brand Intelligence
Track perception and act before issues grow
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.
Agentic AI ecosystem
From insight to action across the enterprise
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.
Model Context Protocol (MCP) for Infor M3
Connecting enterprise systems for secure, seamless access
This agent connects directly to ERP and CRM systems, enabling users to securely access and act on data from their own systems.
CharlieX (Insights & BI Agent)
Turning business data into actionable insight on demand
A self-service data agent that retrieves relevant data on demand and presents it in a format tailored to user needs.
Charlie-One (RAG intelligence engine)
Powering smarter workflows with enterprise-wide intelligence
A foundational engine that powers enterprise-wide workflows, from HR self-service to IT ticketing, using a Retrieval-Augmented Generation (RAG) framework.
Signal-based Forecasting
Predict demand with greater accuracy
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.
Inventory Leveling
Balance stock across the retail network
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.
Automated Feedback Synthesis
Turn customer feedback into usable insight
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.
Actionable Brand Intelligence
Track perception and act before issues grow
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 agentic AI in action across your enterprise
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.
Multi-agent coordination
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.
Secure system integration
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.
Autonomous decision-making
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.
Multi-agent coordination
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.
Secure system integration
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
What to expect
Faster decision-making
Turn days of manual analysis into seconds with AI-driven insights and proactive recommendations.
Reduced operational friction
Eliminate system silos and repetitive tasks with a unified AI interface across business functions.
Proactive risk management
Detect inventory risks, financial exposure, and ERP impacts before they escalate.
Enterprise-grade security
Maintain full data containment with role-based access and secure, compliant AI architecture.
Faster decision-making
Turn days of manual analysis into seconds with AI-driven insights and proactive recommendations.
Reduced operational friction
Eliminate system silos and repetitive tasks with a unified AI interface across business functions.
Proactive risk management
Detect inventory risks, financial exposure, and ERP impacts before they escalate.
Enterprise-grade security
Maintain full data containment with role-based access and secure, compliant AI architecture.
What is agentic AI and how is it different from traditional AI assistants?
Agentic AI goes beyond answering questions. It can make decisions, coordinate workflows, trigger actions, and proactively identify risks or opportunities across enterprise systems.
How does our agentic AI framework integrate with ERP systems like Infor M3?
Charlie uses a secure Model Context Protocol (MCP) layer to interact contextually with ERP APIs, enabling natural language access while maintaining governance and security.
Is our agentic AI framework suitable for large enterprises with complex system landscapes?
Yes, they are designed for enterprise environments, supporting multi-system integrations, structured and unstructured data sources, and role-based access control.
Can non-technical users access insights through our framework ?
Absolutely, oursolution democratizes business intelligence by allowing users to ask complex business questions in natural language without needing technical or BI expertise.