Dulce™—Batch Inference Platform
Windows® batch image classification for manufacturing
Batch-classify manufacturing images locally using CPU, DirectML, or optional NVIDIA CUDA acceleration.
Beta 1 — 60-day evaluation for Windows® 11
PRODUCT
Batch inference without the usual deployment stack
Dulce™ gives manufacturing and engineering teams a straightforward way to run batch image classification on Windows® workstations. Use supported ONNX models with CPU, DirectML, or optional NVIDIA® CUDA acceleration without introducing Linux servers, cloud infrastructure, containers, or Python environments solely to run batch inference.
Keep inspection images under your control
Run supported batch inference locally on Windows® hardware without a required cloud path
Put your workstation to work
Use compatible CPU, DirectML, and optional NVIDIA® CUDA devices already available in the workstation
Review results after the run
Retain structured batch inference results and run evidence for comparison, investigation, and later analysis
USE CASES
Where Dulce™ fits
You already have images and a supported model — Use Dulce™ when you already have a captured image set and a supported discrete-class ONNX model and need a controlled Windows® batch inference workflow.
You want to keep inference local — Run image classification on customer-controlled Windows® hardware without requiring a cloud inference path or Internet-connected runtime.
You want to replace ad hoc batch tooling — Move from scripts or manually assembled inference workflows to a structured application that records per-image results, run-level information, and execution evidence.
You want reviewable results after the run — Use Dulce™ when classification results need to remain available for later review, documentation, investigation, or downstream analysis rather than existing only as transient runtime output.
Dulce™ is not a camera system, PLC integration layer, or real-time reject controller. It is the offline batch inference layer around captured image sets.
An offline evidence layer, not an inline replacement
Dulce™ works with images that have already been captured. It can complement existing machine-vision systems with batch replay, model validation, sampled QA, retrospective analysis, and reviewable run evidence without replacing line-speed inspection or production control.
WINDOWS® + LOCAL
Batch inference without a separate AI infrastructure stack
Stay local
Images and inference workloads remain on the workstation rather than requiring a cloud inference service.Runtime operation does not require Internet or cloud connectivity.
Use existing hardware
CPU, DirectML, and optional NVIDIA CUDA execution allow Dulce™ to use hardware already available in the workstation.
Use Windows® directly
Dulce™ runs as a Windows® desktop application without requiring operators to work with Linux, containers, or Python environments.
Keep the workflow simple
Models, image sets, execution settings, and batch results are managed through the application rather than assembled from command-line tools and scripts.
RESULTS
Reviewable batch inference output
Dulce™ records classification results and run-level information so completed batch runs can be reviewed, documented, and analyzed after processing.
Per-image results
Review classification results for the images processed during the run instead of relying only on transient runtime output.
Run-level summary
See run-level information including image counts, timestamps, throughput, and the locations of generated result artifacts.
Execution evidence
Dulce™ records per-device execution telemetry together with the model SHA-256 and, when applicable, the label-file SHA-256.
Results that remain useful after the run
Generated results can support later review, investigation, documentation, or downstream analysis using the artifacts produced by Dulce™.
Examples from a completed run:
Completed run summary
Per-image classification results
Machine-readable run summary
System requirements
Dulce™ Beta 1 is designed for 64-bit Windows® 11 workstations
Windows® 11
64-bit Windows® 11 desktop or workstation
Execution hardware
CPU, DirectML, and optional NVIDIA® CUDA acceleration
Storage and memory
About 1.01 GB installed, with approximately 1.5–1.6 GB typically observed during batch inference
OPTIONAL NVIDIA® CUDA
CUDA acceleration
CUDA acceleration is optional. Dulce™ can run using CPU or DirectML without NVIDIA® CUDA dependencies.*
| CUDA 12 | cuDNN 9 |
|---|---|
| A compatible NVIDIA® GPU, NVIDIA driver, and CUDA 12 runtime are required | cuDNN 9 runtime required and configured in Dulce Settings |
| CUDA downloads | cuDNN downloads |
* Dulce™ does not install or update NVIDIA CUDA dependencies
CUDA optional setup
DOCUMENTATION
User Guide
The Dulce™ Beta 1 User Guide covers installation, supported models and image inputs, CPU/DirectML/CUDA execution, CUDA requirements, batch operation, persistent data, and uninstall behavior
Beta 1
Apply for the Dulce™ Beta
Dulce™ Beta 1 is intended for U.S. businesses evaluating Windows®-based batch image classification for manufacturing or related technical workflows.
Before applying:
You already capture inspection images suitable for Dulce™ Beta 1
You have a supported discrete-class ONNX model, or an integrator/model provider who can supply oneYou must use a business email address
You must have access to a Windows® 11 x64 workstation
You must have a Microsoft account that can access the Microsoft Store
Beta 1 is a 60-day evaluation
CUDA is optional; CPU and DirectML can be used without NVIDIA CUDA dependencies
Beta 1 is not intended for teams seeking model development, camera integration, or a turnkey inline inspection system.
Support
Contact Dulce™
Questions about Dulce™ Beta 1, installation, CUDA configuration, or application behavior can be submitted using the contact form.See Privacy for information about how submitted information is handled
PRIVACY
Privacy and data practices
Dulce™ application
Dulce™ is designed for local, on-premises operation. The Dulce™ application does not collect, track, store, or transmit user data or application telemetry.
Website
This website may process limited technical information needed to deliver and secure the site, such as IP address, browser or device information, and server log data. Service providers used to operate the website may process this information on our behalf.If you contact Sweet Software Practices Corporation through this website, we receive the information you choose to provide, such as your name, company name, email address, and message. We use that information only to respond to your inquiry and provide requested support or information.
Beta feedback
Information voluntarily provided as Beta feedback may be retained and used to evaluate and improve Dulce™.
Privacy questions
Use the Support contact form
SWEET SOFTWARE PRACTICES CORPORATION
Dulce™
Windows batch inference for manufacturing
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