Product updates across the platform.
Get ready for launch.
Get ready for launch.
SupplyBoard is preparing to launch as a manufacturing intelligence platform for SMEs, connecting supplier discovery, workflows, analytics, and industrial intelligence in one place.
Companies that claim their profile on SupplyBoard can access a business dashboard to track analytics, monitor performance, and make data-driven decisions.
This update introduced the analytics layer needed to make SupplyBoard more than a listing database, turning supplier and manufacturing data into clearer signals for users.
Vega was introduced as a machine intelligence layer to help machine shops address alarm floods, unplanned downtime, slow root-cause analysis, expert dependency, fragmented systems, and a lack of contextual intelligence across operations.
Vega represents the industrial data layer of SupplyBoard. It is intended to help manufacturers move from disconnected machine signals toward practical intelligence for maintenance, operations, and process-level insight.
You can now order a custom part by uploading your file and configuring the order.
This update moves SupplyBoard closer to a full manufacturing workflow layer. Instead of only helping users find suppliers, the platform begins supporting how buyers express what they need and how suppliers can respond.
SupplyBoard Studio was created to help users structure manufacturing requirements, upload design context, and prepare production-ready requests.
SupplyBoard Studio introduced a structured workspace to help users move from loose manufacturing ideas or design files toward clearer production requirements.
Across Canada, SupplyBoard began as a manufacturing supplier directory to help buyers discover industrial capabilities, processes, services, and suppliers.
The first version of SupplyBoard focused on supplier discovery across Canada, giving the platform its first structured dataset of manufacturing capabilities, processes, and supplier information.
After experiencing manufacturing procurement pain points firsthand, we began investigating the problem in depth and studying solutions that already exist in other parts of the world. We also began developing our own solutions.
Before writing product code, the team spent a year understanding how manufacturing SMEs search for suppliers, express requirements, and make production decisions — shaping the roadmap that followed.
Find manufacturing suppliers by capabilities, services, processes, and location.
Structure manufacturing requirements, design context, materials, and production parameters.
Move from discovery to manufacturing requests and supplier-side workflows.
Turn supplier, workflow, and operational data into useful business and manufacturing insights.
Connect CNC activity, controller data, sensor signals, and machine-health indicators.
Support operation-level energy and CO₂e estimates using machine behavior and production context.
Directions we are developing and exploring — not promises.
Developing project workspaces to organize manufacturing requests, track progress, and coordinate buyers and suppliers.
Working toward stronger anomaly detection, baseline comparison, and failure-risk indicators.
Exploring more structured operation-level energy and CO₂e estimation.
Developing better supplier profiles, visibility, and workflow support.
Improving the journey from requirement capture to supplier matching.
Preparing more structured pilots around CNC machine data and manufacturing intelligence.
