Enterprise AI · Supply Chain Intelligence

Five AI Agents.
One Intelligent Planning Platform.

Each agent is purpose-built for a distinct supply chain decision layer — deployable as standalone modules or as an integrated suite running inside your existing SAP environment.

10K+
Simulations per run
360°
Supply chain visibility
15–25%
Inventory reduction
5
Purpose-built AI agents

Intelligent Supply Chain.
Built on SAP. Powered by AI.

Cognto AI embeds autonomous AI agents directly into your SAP landscape — transforming static planning cycles into a continuously self-optimizing supply network.

Autonomous AI Agents
Five specialized agents handle demand, supply, inventory, scenario planning, and simulation — each with its own reasoning engine and SAP data access.
5 Agents
Digital Twin Simulation
Full-fidelity digital twin of your supply network runs thousands of Monte Carlo simulations — testing strategies before you commit a single dollar.
10K+ Scenarios/run
Real-Time Signal Detection
Continuously monitors demand spikes, supplier failures, cost shocks, and lead time changes — triggering automated scenario analysis instantly.
< 60s detection
SAP-Native Architecture
Runs inside SAP BTP, connected to IBP, S/4HANA, MM, EWM, and APO master data. No separate data warehouse. No manual model building.
Zero ETL
Joule-Powered Analytics
Generative AI via SAP Joule provides natural-language explanations of forecasts, inventory recommendations, and plan deviations in plain English.
GenAI Native
Sense → Reason → Act
Every agent follows the full agentic loop: detect signals, reason over options with confidence intervals, then execute approved actions or surface ranked recommendations.
Full Agentic Loop

Every Supply Chain Problem.
One AI Platform.

Cognto AI addresses the full breadth of supply chain planning challenges — from demand sensing to supplier risk, transportation to sustainability — all running inside SAP.

Demand Planning & Forecasting
AI-powered demand sensing and statistical ML models generate SKU-level forecasts with confidence intervals — continuously updated as market signals change.
SAP IBP DPSAP APOML Algorithms
30% better forecast accuracy
Supply Planning & Optimization
Multilevel supply planning balances capacity constraints, lead times, and prioritized demand — generating feasible plans without manual planner intervention.
SAP IBP SNPSAP MMCapacity Modeling
20% lower expedite costs
Multi-Echelon Inventory Optimization
Global multi-stage IO models calculate optimal safety stock at every location-product node simultaneously — dynamically adjusting as demand variability changes.
SAP IBP InventorySAP EWMDDMRP
15–25% inventory reduction
Sales & Operations Planning (S&OP / xP&A)
Cross-functional alignment of demand, supply, inventory, and finance in one unified IBP process — with real-time simulation and scenario comparison.
SAP IBP S&OPSAP BTPxP&A
40% faster planning cycles
Supply Chain Risk Assessment
Continuously monitors Tier 1/2/3 supplier risk signals — geopolitical exposure, financial health, lead time volatility — triggering scenario analysis before disruption cascades.
SAP Supply Chain CTSAP BTPReal-Time Signals
60% faster risk detection
Supplier Risk Assessment
Scores each supplier on financial stability, delivery performance, and geopolitical exposure — automatically surfacing alternative sourcing recommendations when risk thresholds are breached.
SAP AribaSAP Business NetworkRisk Scoring
35% fewer supply disruptions
Supply Chain Visibility & Control Tower
End-to-end real-time visibility across the entire network — automated exception management, deviation alerts, and drill-down root-cause analysis in SAP Supply Chain Control Tower.
SAP SCCTSAP S/4HANAAlerting
360° network visibility
Transportation & Distribution Planning
Route optimization, carrier selection, and shipment consolidation — integrated with SAP TM to reduce freight cost while maintaining delivery commitments.
SAP TMSAP EWMRoute Optimization
12% transport cost reduction
Trading Partner Collaboration
Shares demand plans, POs, and inventory levels with suppliers on SAP Business Network — enabling real-time commitments, VMI, and quality collaboration.
SAP Business NetworkVMIPO Collaboration
25% shorter PO cycle time
Sustainability & Carbon Planning
Tracks Scope 1, 2, and 3 emissions per order, route, and supplier — integrating with SAP Sustainability Footprint Management to score sourcing decisions against carbon reduction targets.
SAP SFMScope 3Green Sourcing
Target 30%
Scope 3 reduction

Five AI Agents. One Intelligent Planning Platform.

Purpose-built for every supply chain decision layer — deployable standalone or as an integrated suite inside your SAP environment.

Demand Planning Agent
Generates statistically robust, SKU-level demand forecasts using real-time market signals, historical SAP data, and machine learning — updated continuously.
SAP IBP DPSAP APO
Learn more →
Supply Planning Agent
Balances confirmed demand, supplier lead times, and capacity constraints to build and continuously update feasible supply plans — reducing expedite spend.
SAP IBP SNPSAP MM
Learn more →
Inventory Planning Agent
Optimizes safety stock, reorder points, and inventory positioning across multi-echelon networks — dynamically adjusting targets as conditions change.
SAP EWMSAP MM
Learn more →
What-If Scenario Agent
Monitors supply chain signals in real time — demand spikes, supplier failures, cost shocks — and autonomously runs scenario simulations, surfacing ranked recommendations.
SAP IBPSAP BTP
Learn more →
Supply Chain Simulator
Builds a full-fidelity digital twin of your SAP-connected supply network and runs thousands of Monte Carlo simulations — testing sourcing strategies before committing resources.
SAP BTPSAP Gen AI
Learn more →

Demand Planning Agent

SAP IBP DPSAP APOSAP JouleMachine Learning

Generates statistically robust, SKU-level demand forecasts using real-time market signals, historical SAP data, and ML — updated continuously.

SAP IBP's Demand Planning Agent combines historical transaction data from SAP APO and IBP with real-time market signals to generate SKU-location-level forecasts with confidence intervals — not single-point guesses.

Rather than running on a monthly batch cycle, the agent continuously updates forecasts as new POS data, market events, or supplier changes occur — giving planners a living forecast.

SAP Joule provides natural-language explanations: "Demand for SKU-4821 is projected up 18% in Q3 due to seasonal lift and a new distribution channel. Confidence: high."

30%
Forecast accuracy improvement
60%
Reduction in manual overrides
Real-time
Continuous model updates
SKU-level
Granularity with CI bands
  • ML Forecasting Engine
    Combines statistical models (ARIMA, exponential smoothing) with ML algorithms trained on your historical SAP data — automatically selecting the best model per SKU.
  • Demand Sensing
    Predicts short-horizon demand (1–4 weeks) based on real-time signals: POS data, web traffic, promotions, and weather overlays — via SAP IBP demand sensing.
  • Collaborative Forecasting
    Enables Sales, Marketing, and Finance to contribute demand inputs in a single SAP workspace — with automatic consensus building and override tracking.
  • Anomaly Detection
    Automatically flags master data anomalies and unusual demand patterns — surfacing them to planners with root-cause explanations via Joule.
  • SAP IBP for Demand
    Native integration with SAP IBP DP — reads historical shipment, sales order, and inventory data. Writes forecasts back to IBP for downstream supply planning.
  • SAP APO Migration Path
    Supports customers migrating from SAP APO DP/SNP — maps APO planning books and key figures to IBP equivalents with automated data migration tooling.
  • SAP Joule (GenAI)
    Joule integration provides natural-language forecast explanations, "what changed and why" summaries, and model improvement recommendations in plain English.
SAP Data Flows

📥 Reads from: SAP IBP Harmonized Planning Area, S/4HANA sales orders, MM goods movements, APO Livecache

📤 Writes to: IBP Demand Key Figures, S&OP consensus demand, supply planning inputs

🔌 Connectors: SAP Integration Suite, OData APIs, BTP Data Pipelines

30%
Avg. forecast error reduction (MAPE)
3–5%
Inventory reduction from better forecasts
40%
Planner time saved on consensus cycles
18%
Reduction in lost sales from stockouts

Supply Planning Agent

SAP IBP SNPSAP MMSAP JouleProduction Planning

Balances confirmed demand, supplier lead times, and capacity constraints to build feasible supply plans — continuously updated.

The Supply Planning Agent takes confirmed demand and translates it into feasible, capacity-constrained supply plans across multi-tier supplier networks — running inside SAP IBP SNP.

SAP's 2026 Joule Agents for Supply Planning automate prerequisite checks for production order release — validating material availability, capacity, and scheduling before committing, dramatically shortening order-to-delivery cycles.

The agent continuously rebalances supply plans as demand signals shift, supplier lead times change, or capacity constraints emerge.

20%
Reduction in expedite spend
+8%
Fill rate improvement
Hourly
Plan refresh frequency
Multi-tier
Supplier network visibility
  • Production Planning & Operations Agent (Joule)
    Automates prerequisite checks for releasing production orders — validates material, capacity, and scheduling, and can recommend workarounds or release orders instantly.
  • Response & Supply Planning
    Balances supply and demand across the network in real time, supporting both time-series and order-based planning via the Harmonized Planning Area.
  • Capacity Constraint Optimization
    Models production line capacities, supplier MOQs, and transportation constraints — automatically generating feasible plans without manual planner intervention.
  • Telescopic Planning Horizons
    Supports strategic, tactical, and operational planning horizons in a single model — enabling planners to move smoothly between short-term execution and long-term planning.
  • SAP IBP SNP
    Core supply planning engine — models multi-echelon supply networks, applies heuristics or optimization to generate supply plans across all nodes.
  • SAP MM (Materials Management)
    Reads purchase orders, goods receipts, and vendor master data. Writes purchase requisitions and planned orders back to S/4HANA for execution.
  • SAP Business Network
    Connects to SAP Business Network for supplier collaboration — enabling real-time supplier capacity confirmations and delivery updates.
2026 Joule Agents (GA Q2 2026)

🤖 Production Planning Agent: Autonomous production order release with prerequisite validation

🤖 Change Record Agent: Reasons over engineering change requests, recommends actions

🤖 Supplier Onboarding Agent: End-to-end automated supplier qualification on SAP Business Network

20%
Reduction in expedite freight costs
8%
Fill rate improvement
35%
Faster production order release
50%
Reduction in planner manual effort

Inventory Planning Agent

SAP EWMSAP MMSAP IBP InventoryMulti-Echelon Optimization

Optimizes safety stock, reorder points, and inventory positioning across multi-echelon networks — dynamically adjusting targets as conditions change.

The Inventory Planning Agent uses SAP IBP's Global Multi-Stage Inventory Optimization to calculate optimal safety stock levels at every location-product combination — accounting for demand variability, lead time uncertainty, and service level targets simultaneously.

AI-assisted analysis highlights the drivers behind every recommendation — "safety stock for SKU-4821 at DC-Chicago increased 12% due to supplier lead time variability rising from 3 to 5 days."

Minimum and maximum safety stock constraints prevent both stockouts and excess accumulation — the agent dynamically adjusts within these bounds as conditions evolve.

15–25%
Inventory reduction
99.2%
Target service level
Multi-echelon
Network-wide optimization
Dynamic
Continuous target adjustment
  • Global Multi-Stage Inventory Optimization
    Models the entire supply network simultaneously — DC, regional warehouses, retail locations — determining optimal stocking levels at every node.
  • AI-Assisted Safety Stock Analysis
    Highlights demand variability, lead time changes, and planner adjustments that drive safety stock recommendations — with plain-English explanations.
  • Min/Max Constraint Management
    Defines absolute minimum and maximum safety stock quantities per location-product — ensuring optimization respects business rules.
  • SAP EWM Physical Execution
    Translates optimized inventory targets into warehouse management directives inside SAP EWM — automating replenishment triggers and slotting recommendations.
  • SAP EWM
    Reads real-time warehouse stock positions, putaway strategies, and pick performance. Writes optimized safety stock targets and replenishment triggers back to EWM.
  • SAP MM
    Reads MRP parameters, vendor lead times, and goods movement history. Updates safety stock and reorder point fields directly in material master records.
  • SAP IBP Inventory Optimization
    Core optimization engine — runs global multi-stage inventory optimization using probability-weighted demand and lead time distributions.
Inventory Optimization Flow

📥 Reads: MM safety stock fields, EWM stock positions, IBP demand variability, vendor lead time data

🧮 Optimizes: Multi-stage IO model with min/max constraints and service level targets

📤 Writes: Updated safety stock to MM material master, EWM replenishment triggers, IBP supply plan inputs

15–25%
Total inventory reduction
12%
Working capital freed
99.2%
Service level maintained
60%
Reduction in manual safety-stock reviews

What-If Scenario Agent

Monitors supply chain signals in real time and autonomously runs scenario simulations — surfacing ranked recommendations before disruptions cascade.

  • Real-Time Signal Monitoring
    Continuously ingests demand spikes, supplier failure reports, lead time changes, and raw material cost shocks from SAP IBP control tower feeds.
  • Autonomous Scenario Generation
    When a signal is detected, the agent automatically generates 3–5 response scenarios — each with projected cost, service level, and lead time impact.
  • Ranked Recommendations
    Scenarios ranked by expected value with confidence intervals — planners choose, the agent executes the approved action in SAP.
  • Sense → Reason → Act Loop
    Full agentic loop: detect signal, reason over options, surface recommendations, execute approved action — all within minutes of the triggering event.
What-If Scenario
● Agent Active
Semi-Autonomous Mode
Command Center
Signal Monitor
Scenario Engine
Alert Center
Agent Config

Agent Command Center

Real-time supply chain monitoring and autonomous scenario management

Active Signals
4
5 total detected
Scenarios
4
2 completed
Agent Actions
11
Sense → Reason → Act
Pending Alerts
1
Awaiting review

Live Signal Feed

View All →
Demand Spike Detected - Wi...
3/26/2026
high
Supply Shortage - Sensor-C f...
3/26/2026
critical
Lead Time Increase - Module...
3/25/2026
medium
Raw Material Cost Increase...
3/24/2026
medium

Active Scenarios

View All →
SC-2026-041: Demand Spike...
Demand Spike
completedAgent
SC-2026-042: Supply Shorta...
Supply Constraint
completedAgent
SC-2026-043: Lead Time Buf...
Lead Time
simulatingAgent
SC-2026-044: Cost Impact A...
Cost Analysis
draftPlanner

Digital Twin & Supply Chain Simulator

Builds a full-fidelity digital twin of your supply network and runs thousands of Monte Carlo simulations — testing strategies before you commit a single dollar.

Full Network Modeling
Models every node: Tier-1/2/3 suppliers, DCs, production lines, customer segments. Multi-echelon, multi-currency, full visibility.
Monte Carlo Simulation Engine
Runs thousands of probability-weighted scenarios simultaneously, delivering confidence intervals across KPIs — not single-point forecasts.
Strategy Comparison Dashboard
Side-by-side comparison of up to 5 strategic options — cost, service level, resilience — with Pareto-optimal frontier visualization.
SAP Master Data Ingestion
Seeds the digital twin from your live SAP master data: BOMs, routes, lead times, capacities. No manual model building.
10K+
Simulations per run
360°
Network visibility
15–25%
Inventory reduction
IBP Simulator
Dashboard
New Scenario
Compare
Planning Data
SAP Connection
Supply Chain Overview
SAP IBP What-If Scenario Simulator
Consensus Demand
8.4K
Period: 2027-03
Production Plan
8.5K
Ratio: 1.01x
Inventory Level
1.2K
4.2 days supply
Avg Lead Time
16.1d
3 active scenarios
Demand vs Production
Demand
Production
Inventory Trend

Scenarios

View all →
Q2 2026 Demand Spike - Sports Event
Demand Spike
completed
Plant Dallas Capacity Reduction
Supply Constraint
completed
Demand spike during the sports event
Demand Spike
completed

Your Return on Intelligence

Quantified ROI from deploying Cognto AI agents — benchmarked against SAP IBP customer outcomes, ESG Research, and independent analyst studies.

30–35%
Demand Planning
  • forecast error reduction
  • 60% fewer manual overrides
  • 18% reduction in lost sales
15–25%
Inventory Management
  • inventory reduction
  • 10–12% working capital freed
  • 99%+ service level maintained
20–30%
Supply Operations
  • expedite cost reduction
  • 35% faster order release
  • 50% planner effort saved
35%
Supply Network
  • fewer supply disruptions
  • 30% faster supplier onboarding
  • 25% shorter PO cycle time
Step 1 — Sense
Sense
AI agents continuously ingest SAP live data streams: demand signals, supplier alerts, cost changes, and inventory deviations in real time.
Step 2 — Reason
Reason
Agents reason over 10,000+ scenario combinations, ranking options by expected value, cost, and service level impact — with confidence intervals.
Step 3 — Act
Act
Approved recommendations execute autonomously inside SAP — updating supply plans, triggering POs, adjusting safety stock targets, releasing production orders.

Benchmark Improvements vs. Pre-AI Baseline

Metric Before Cognto AI After Cognto AI Improvement Unit
Forecast Accuracy (MAPE)25–35% error15–20% error30–35% better% accuracy
Inventory Days on Hand45–60 days32–45 days20–25% reductionDays
On-Time In-Full (OTIF)88–92%94–98%+5–8 pts%
Planning Cycle Time5–10 days1–2 days70–80% fasterDays
Expedite Freight SpendBaseline–20–30%$2–8M annual savingsUSD
Planner Productivity1x1.5–2x+40–60% capacityMultiplier
"Improved data precision and transparency enabled accurate demand planning across our global network, significantly reducing forecast errors and excess inventory."
Head of Supply Chain
BYK
"By harnessing big data, machine learning, and IoT, we built a connected, predictive digital supply chain that responds in real time to demand shifts."
Digital Supply Chain Team
Microsoft
"Transitioning to AI-powered integrated planning delivered end-to-end visibility, predictive analytics, and real-time insights — validating measurable ROI."
Research Validation
ESG Research

Built Inside Your SAP Environment

Cognto AI runs natively on SAP BTP — connected to your existing SAP landscape. No separate data warehouse. No integration tax.

SAP IBPSAP S/4HANASAP BTPSAP EWMSAP MMSAP APOSAP JouleSAP Gen AI
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