Specification data management platform for supply chain digitization
Specright builds a specification data management platform targeting supply-chain-heavy industries like food & beverage, automotive, and manufacturing. The tech stack reveals a full-stack, Salesforce-centric architecture (Node.js, React, Next.js, PostgreSQL on AWS/Azure/GCP paired with Salesforce Apex and Lightning Web Components), and the project list signals a strategic pivot toward AI: agentic applications, chat interfaces, and internal copilots are all active, suggesting the company is embedding AI agents into supply-chain decision workflows while scaling Salesforce integration and services delivery.
Specright is a specification data management platform founded in 2014 that helps companies in regulated and supply-chain-dependent industries (agriculture, automotive, cosmetics, food & beverage, manufacturing, medical) digitize, map, and operationalize specification data across packaging, raw materials, formulas, products, and machines. The company operates a hybrid sales and services model: engineering teams build both customer-facing platform features and customized Salesforce solutions, while smaller sales capacity signals either a land-expand motion or partner-driven distribution. Headquartered in Tustin, California with a 51–200-person team, Specright is privately held.
Specright uses Node.js, React, Next.js, and PostgreSQL on AWS, Azure, and GCP for the core platform. On the enterprise side, it integrates deeply with Salesforce (Apex, Lightning Web Components, Visualforce, Salesforce DX). Observability relies on Datadog, Honeycomb, and OpenTelemetry.
Active projects include agentic applications, chat-based interfaces, and internal copilots for supply-chain AI decisions. The company is also scaling Salesforce customization, third-party system integrations, and deployment automation alongside forward-deployed engineering services.
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Specright's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.