Connected Planning And Operational Intelligence

DynamiPlan X.1

Plan for change with greater clarity. Connect demand, inventory, capacity, and operations to evaluate scenarios and support more informed planning.

Open Dashboard Explore How It Works

— Who We Are

Planning Intelligence For Complex Industrial Industry

Supply-chain and manufacturing teams face changing demand, capacity, and cost pressures. Dynamiqo connects forecasting and scenario analysis to support informed planning decisions.

01 // Forecast

Forecast With Context

Assumptions, ranges, data freshness, and constraint context stay visible — not hidden in a single-number plan.

02 // Constraints

Model Constraints

Represent capacity, inventory, lead times, costs, and business rules before selecting a plan.

03 // Control

Planner Control

Recommendations support human review and approval. Automatic plan changes that disrupt operations are not the goal.

Technical Stack

Core platforms and services that support DynamiPlan X.1 planning workloads.

Python

PyTorch

ONNX Runtime

FastAPI

WebSockets

Apache Spark

PostgreSQL

TimescaleDB

Vector Database

Redis

Apache Kafka

MQTT

Docker

Kubernetes / EKS

MLflow

Prometheus / Grafana

— Compatibility Directions

NVIDIA Integration

Possible technical compatibility directions for high-performance planning and inference workloads. Not product certifications.

NVIDIA RAPIDS — cuDF & cuML

GPU-accelerated analytics and feature workflows for large planning datasets.

Large-scale planning data processing
GPU-accelerated feature engineering
Batch analytics on demand and inventory signals

NVIDIA CUDA

Parallel compute foundations for intensive optimization and simulation runs.

Scenario and optimization compute
High-throughput model evaluation
Accelerated numerical workloads

NVIDIA TensorRT

Production optimization of forecast and decision-support models.

Lower-latency inference paths
FP16 / INT8 optimization options
Higher concurrency for planning services

NVIDIA Triton Inference Server

Scalable model serving for forecast and recommendation workloads.

Multi-model serving
Dynamic batching patterns
Kubernetes-oriented deployment

This list represents possible technical compatibility directions only. Any claim of integration, certification, performance testing, or commercial partnership requires separate validation.

— Data To Decision

How DynamiPlan X.1 Works

Five linked stages from connected data to planner approval. Select a stage to review its role.

— What We Provide

Capabilities

Connected intelligence across forecasting, optimization, and operational planning.

Planning Data Foundation — connect demand, inventory, capacity, lead-time, and cost data.

Forecast Intelligence — develop forecasts using ranges, assumptions, and operational factors.

Dynamic Optimization — evaluate allocations and schedules against objectives and constraints.

Scenario Comparison — compare alternatives, trade-offs, and potential impacts.

Planner Decision Support — present recommendations for human review before changes are applied.

Exception Handling — surface data-quality and feasibility issues early.

Ownership & Approval — track who owns each plan and where it sits in review.

Enterprise System Connectivity — work with ERP and planning system integrations.

System Metrics

Planning and runtime measures used to evaluate DynamiPlan X.1 performance and operational quality.

Metric	Objective
Forecast freshness	Time since last approved forecast refresh
Scenario run latency	Time from scenario start to trade-off view
Concurrent planners	Simultaneous active planning sessions
Constraint coverage	Share of plans evaluated under active constraints
Feasibility exception rate	Share of runs with feasibility issues
Data-quality exceptions	Missing or stale input signals detected
Approval cycle time	Time from recommendation to planner approval
GPU utilization	Accelerator efficiency for optimization runs
Model memory footprint	Runtime memory used by forecast services
API throughput	Planning and optimization requests per second