Peliqan.io is an all-in-one AI-first data integration and automation platform designed for business teams, scale-ups and consultants. Unlike traditional data tools that demand heavy engineering effort, Peliqan enables both business users and technical teams to connect, manage, and activate their data in one collaborative environment - without requiring a dedicated data engineer.
With 300+ built-in connectors, Peliqan connects to databases, SaaS business applications (ERP, CRM, Accounting, HRM/ATS etc.), cloud storage, files and APIs as well as on-prem data sources. New connectors are available on demand within 5 business days.
Peliqan offers one-click ELT pipelines to the built-in data warehouse, or you can bring your own data warehouse. Peliqan supports all major data warehouses.
Thanks to Peliqan’s Excel add-in, business users and consultants can work with real-time data in Excel.
Analysts and power users can use Peliqan’s advanced SQL editor with the support of an AI assistant to transform data and prepare business-ready data sets, which can be used in any BI tool such as Microsoft Power BI, Metabase, Tableau, Qlik, Looker etc. Users can also set up Reverse ETL flows.
Developers can go even further with Peliqan’s low-code environment, with a built-in virtual AI Data Engineer, where they can:
- Build & Publish interactive data apps
- Automate writebacks into source systems
- Publish API endpoints for data sharing
- Implement custom pipelines
- Build out internal AI Agents
By empowering business users, analysts, consultants and developers, Peliqan dramatically reduces reliance on IT support and speeds up decision-making.
Peliqan is not just an ELT data pipeline tool, it’s a complete solution for data orchestration, automation, and activation. Peliqan also acts as the data foundation for Agentic AI, ensuring that AI agents work with trusted, up-to-date 360° views of customers, products, orders, and more - at the speed of a cloud data warehouse.
Peliqan’s data warehouse provides an AI-ready data layer out-of-the-box including:
- Automatic vectorizing of structured and non-structured data for RAG (Retrieval-Augmented Generation)
- Text-to-SQL
- MCP Gateway
In today’s landscape, a data warehouse is no longer just for BI - it’s the foundation for both BI and AI. With Peliqan.io, organizations can integrate, analyze, and activate their data seamlessly, empowering both humans and AI agents to make smarter, faster decisions.
Average Rating: 4.8/5.0
Total Reviews: 86
How Do G2 Users Rate Peliqan?
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Has the product been a good partner in doing business?: 9.0/10 (Category avg: 9.1/10)
Who Is the Company Behind Peliqan?
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Seller: Peliqan
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Company Website:
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Year Founded: 2022
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HQ Location: Gent
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Twitter: @Peliqan_io
9 Twitter followers
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LinkedIn® Page: www.linkedin.com
32 employees on LinkedIn®
Who Uses This Product?
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Top Industries: Computer Software, Information Technology and Services
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Company Size: 48% Small, 41% Medium
What Do G2 Reviewers Say About Peliqan?
AI-generated summary from verified user reviews
Pros
- Users value the ease of use of Peliqan, enjoying seamless integration and effortless data management processes.
- Users value the effortless integrations of Peliqan, enhancing data accessibility and automation in their workflows.
- Users value the easy integrations of Peliqan, which streamline workflows and enhance operational efficiency across various platforms.
- Users value the extensive pre-built connectors of Peliqan, enabling efficient data integration and faster client onboarding.
- Users value the real-time data access and smooth integration capabilities of Peliqan for effective data management.
Cons
- Users find the learning difficulty of Peliqan challenging, requiring technical expertise for setup and usage.
- Users find Peliqan requires significant technical skills for setup and data transformation, limiting accessibility for non-tech users.
- Users highlight feature limitations of Peliqan, requiring external tools for complete BI functionality and custom report creation.
- Users find that Peliqan's steep learning curve requires expertise for optimal use and initial setup can be time-consuming.
- Users find a steep learning curve for non-tech individuals due to required Python, SQL, and machine learning knowledge.
