2 Integrations with Ansible Lightspeed
View a list of Ansible Lightspeed integrations and software that integrates with Ansible Lightspeed below. Compare the best Ansible Lightspeed integrations as well as features, ratings, user reviews, and pricing of software that integrates with Ansible Lightspeed. Here are the current Ansible Lightspeed integrations in 2026:
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Supy
Supy
Supy is a cloud-based, data-driven restaurant inventory and operations platform designed to give multi-branch F&B businesses real-time control over procurement, stock, cost, and analytics so teams can cut waste, reduce food cost, streamline workflows, and make faster, smarter decisions across every kitchen and location. It combines end-to-end procurement tools that support requisitions, approvals, supplier management, and central kitchen ordering with live inventory tracking, stock counting, wastage recording, recipe and prep management, and ingredient/allergen oversight to ensure accurate visibility of stock levels and food cost performance at scale. Supy also incorporates interactive dashboards, spreadsheet-style reports, audit logs, anomaly detection, and open API connectivity so operational data becomes actionable insight for growth and consistency, while integrations with existing POS, accounting, ERP, and aggregator systems eliminate silos and manual reconciliation.Starting Price: $200 per month -
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Enable hybrid cloud developers of all experience levels to write code with AI-generated recommendations. What if you could translate plain English to code? IBM watsonx Code Assistant allows you to do just that. Powered by IBM watsonx.ai foundation models (FM), IBM watsonx Code Assistant makes it easier for anyone to write code with AI-generated recommendations, bringing the power of IT automation to your entire organization as a strategic, accessible asset for more users—not just the subject-matter experts. This means automatically suggesting code for developers based on natural language inputs. IBM watsonx Code Assistant is infused with watsonx.ai FMs that are purpose-built, created with deployment efficiency in mind, and which enable organizations to customize the models, while also applying enterprise standards and best practices.
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