Build agents and applications that prepare
analysis, evidence, and alternatives for action.
We combine business knowledge and data with forecasting, simulation, and optimization models where appropriate. The resulting application helps users review signals, likely causes, business impact, assumptions, and options, then carry the approved decision into the next workflow step.
Move from status reporting to cause, outlook, and options
BI and dashboards are effective for understanding current performance. Investigating likely causes, assessing the outlook, and comparing options require additional analytical steps that apply business rules and data consistently.
Signal & Exception Detection
Compare plans with actuals and assess defined ranges and trends to identify changes and exceptions that require attention.
Cause & Impact Analysis
Analyze related metrics and business conditions step by step to investigate likely drivers and broader business impact.
Forecasting & Scenario Analysis
Compare forecast ranges and what-if scenarios based on current trends and changes in key variables.
Options & Next Steps
Apply business constraints and rules to prepare feasible options, expected impacts, and next steps for review.
Build the analytical capabilities, decision interface, and system connections required for the workflow
The analytical task and existing system environment determine which functions, review procedures, and downstream integrations belong in the build scope.
Analysis & Diagnosis
Identify signals against defined business metrics and criteria, then examine the related data, conditions, and possible causes.
Forecasting & Risk
Forecast business performance and key variables, and present forecast ranges, risk indicators, and contributing factors.
Simulation & Optimization
Compare what-if scenarios under stated assumptions and constraints, using statistical or machine-learning models and linear or mixed-integer programming where appropriate.
Evidence & Decision Brief
Organize supporting evidence, assumptions, constraints, and the expected impact of each option in reviewable briefs and application interfaces.
Workflow & Governance
Embed review, approval, deferral, and exception handling in the workflow and define decision authority and responsibility.
Integration & Feedback
Connect ERP, CRM, MES, and other existing systems, and feed recorded decision and execution outcomes into subsequent analysis.
Combine governed data, business knowledge, analytical models, agents, and applications in one design
An LLM is not treated as the sole analytical engine. We organize the required data and business knowledge, integrate the appropriate analytical and optimization models, and design the agent to invoke approved tools under defined conditions, checkpoints, and approval requirements.
AI-Ready Data
Organize business objects, history, metrics, and calculation criteria for the analytical purpose, with the required quality and access controls.
Enterprise Knowledge
Structure business concepts and relationships, rules and exceptions, sources, and evidence so the agent can use them in analysis.
Analytics & Decision Models
Use SQL, statistical and machine-learning models, simulation and optimization methods, and business calculation logic as fit-for-purpose analytical tools.
Agent Skills & Orchestration
Define repeatable analysis procedures, tool-use conditions, validation rules, execution order, checkpoints, and stop conditions.
Decision Support Application
Present signals, possible causes, scenarios, options, evidence, and open questions, and provide the interface for review and follow-up work.
AgentOps & Integration
Provide the controls and records needed for evaluation, permissions, execution history, cost, and change management, and connect the solution to existing systems and workflows.
Frame the decision first, then design the data, models, agent, and application around it
Apply a shared analytical foundation to specific business decisions
The applications can share business knowledge, data, analytical models, and agent capabilities while supporting different decisions and workflows.
Profitability & Portfolio Analytics
Analyze profitability, cost-to-serve, and operating complexity by product, SKU, customer, and channel, then compare options to retain, improve, scale back, or discontinue.
View the Application →SCM Applications
Analyze exceptions and possible causes across demand, inventory, supply, production, and logistics, then compare planning options using forecasts and simulations.
View the Application →Make evidence, uncertainty, and decision authority visible
Evidence & Traceability
Record the data and business knowledge used, tool execution, assumptions, and results so the analysis can be reviewed.
Uncertainty & Open Questions
Present unverified inputs, conflicting criteria, and model uncertainty as explicit items for review.
Decision Governance
Define which actions require review or approval and which, if any, may be automated under agreed conditions, with clear decision authority and responsibility.
Operational Readiness
Define operating criteria for evaluation, permissions, cost control, incident handling, and change management during solution design.
Start with the recurring analysis or decision the application must support
Tell us about the metrics and data in use today, the current analysis process, whether forecasting or simulation is required, and the review and approval structure. We will help define the initial scope and priorities.
Discuss Agentic Analytics & Applications →