Consumer Packaged Goods
From tight margins to competitive advantage
CPG companies face volatile demand, complex supply networks, and relentless retailer pressure. AI promises relief, but most organizations experience it as isolated pilots that never reach full impact.
CPG organizations aren't short on data. AI initiatives still stall at pilots because the data is fragmented, definitions vary by team, and policies limit self-service.
Context Gaps
LLMs and analytics tools are only as good as the business context they access. When "net revenue," "baseline," or "incremental volume" mean different things across teams, AI outputs become hard to trust.
Workflow Gaps
Even when AI produces a smart recommendation, it stops short of execution. Teams still spend hours pulling data, validating assumptions, formatting presentations, and manually coordinating actions.
Control Gaps
Leaders want AI in higher-stakes analytical roles, automating decisions and coordinating actions. But that requires governance, observability, and policy-driven control to operate safely inside the enterprise.
The Operating System
An operating system that turns AI from tool to capability
A vertically integrated data and AI stack that provides trusted context, safe autonomy, and a natural interface employees actually adopt.
3 layers
Unified Stack
Data ecosystem, enterprise policies, and user experience, connected
100% governed
By Design
Role-based controls, audit trails, and policy enforcement built in
1 context
Shared Truth
Consistent metrics and definitions across every team and agent
∞ scale
Enterprise Ready
From pilot to enterprise-wide adoption without rebuilding
Use Cases
Autonomous agents for high-impact CPG functions
AI agents that operate across functions: monitoring, diagnosing, recommending, and taking action with full business context.
Inventory Optimization
Balance service levels with working capital
AI agents analyze demand variability, lead times, and shelf-life constraints to recommend reorder points and proactively flag risks before they become out-of-stocks or write-offs.
Demand variability and promotional spike analysis
Lead time and pack-change tracking
Promo events and shelf-life constraint modeling
SKU-level excess and obsolescence identification
Trade Promotion
Maximize commercial effectiveness
Trade spend is one of the largest and most complex investments in CPG. Agents support promotion planning by simulating scenarios, identifying likely lifts, and evaluating post-event performance with consistent definitions.
Simulating promotion scenarios and expected lifts
Post-event performance with baseline and incremental volume
Compliance spotting and deductions/claims workflows
Exception surfacing with suggested resolution paths
Supply Chain & S&OP
Respond faster when disruptions hit
When supplier delays, transportation constraints, or demand shifts happen, agents run rapid scenario analyses and propose response plans aligned to service and margin goals.
Rapid disruption scenario analyses
Response plans aligned to service and margin goals
Faster S&OP cycles and better allocation decisions
Reduced last-minute expediting costs
Manufacturing Performance
Turn operational data into actionable guidance
AI agents analyze downtime patterns, quality deviations, yield loss, and maintenance data to identify root causes and recommend interventions for teams on the floor.
Downtime pattern analysis and root cause identification
Quality deviation and yield loss monitoring
Preventive maintenance prioritization
Process drift detection and intervention recommendations
Enterprise Benefits
A unified data experience and workflow efficiency for every employee
When sales, supply chain, finance, and marketing use different numbers and different assumptions, decisions become slower and riskier.
A unified data experience makes it easier to find, trust, and use the same business logic everywhere, reducing friction across the entire decision cycle.
Consistent Metrics
Shared definitions and business logic across every team
Self-Service Discovery
Reduce dependence on technical teams for routine analytics
Automated Reporting
Eliminate recurring manual reporting and exception monitoring
From Insight to Action
Move from analysis to execution without switching between tools
The Platform
A complete stack purpose-built for CPG
Every layer of the Datafi platform serves a role in turning AI from isolated experiments into enterprise capability.
Outcomes
Speed, consistency, and repeatability
Transformative outcomes don't come from having better answers. They come from actioning data, turning intelligence into operational capability.
Lower Costs
Reduce glue-task hours across sales ops, demand planning, category management, and finance. Less time reconciling spreadsheets, more time improving outcomes.
Faster Decisions
Agents run scenario analyses in minutes, not days. S&OP cycles accelerate, allocation decisions improve, and teams respond to disruptions before they escalate.
Stronger Execution
AI that learns business context, reasons across messy constraints, and executes workflows that produce measurable results, consistently and at scale.
Turn AI from experiments into CPG outcomes
A practical, scalable path to lower costs, faster decisions, stronger execution, and a more resilient business powered by AI designed to do more than talk.