AI Import Management for B2B SaaS
WeTransform is the embeddable AI file importer for B2B SaaS. Dropped into the host product in a few lines of code, it lets end customers upload any file format and delivers clean validated data via REST API or webhook.
The format multiplication problem
Every B2B SaaS importing client data faces a hidden cost: CSVs with different delimiters, Excels with merged cells, PDFs with tables, legacy XML, JSON with custom schemas. Each new format means new parsing code, edge cases, stalled onboarding.
How it works
The SaaS defines a target format once (columns, types, constraints). End customers upload through the embedded interface. AI Mapping matches source columns to the target. Validation rules run. Clean data lands in the SaaS backend via REST API or webhook. Integration uses the @wetransform/core npm package (React, Vue, vanilla JS) or iframe embed.
Key capabilities
Customers and outcomes
Used by Cargoo (logistics), Sellermania (e-commerce), Autocab (transportation), ING (banking), 23 Prod, Veloris, Senef, and Armรฉe du Salut. Onboarding drops from weeks to minutes, engineering reclaims around 15% of time previously spent on parsers, support stops reshaping files manually. 4.9/5 on G2.
A startup from BRUXELLES, Belgique that is founded by Stephane Jauffret, Alain Tiemblo, Valรฉrie Legrand.
AI-Powered Automation
Create transformation workflows with AI
AI-Powered Assistance
Prompt what you need
Autoclean
Use AI to normalize unstructured files
Mapping
Value mapping, column mapping with AI
The product is a cloud-native SaaS hosted on AWS. The embedded SDK is published as the @wetransform/core npm package, TypeScript-first, with bindings for React, Vue, and vanilla JavaScript. The backend exposes a REST API and webhook system. AI capabilities (AI Mapping, Autoclean, Fill the Gaps, natural language rules) combine purpose-built models and large language models orchestrated on demand. Authentication uses API keys for server-to-server and HMAC signing for iframe embeds. Infrastructure runs in European data centers (GDPR by default).
WeTransform was founded in 2024 by Squadra Software. The team had built a file mapping engine for marketplace operations called SmartMap. After observing that every B2B SaaS faces the same hidden cost, namely format multiplication that silently eats engineering and onboarding time, the team rebuilt SmartMap as an AI-native embeddable importer, productized so any B2B SaaS could drop it into their product in a few lines of code.
WeTransform is built for B2B SaaS products that need to import data from customers, partners, or suppliers. Primary buyers are CTOs, CPOs, and Heads of Product who see the cost of maintaining custom parsers, plus the friction in client onboarding. The end users of the embedded importer are operations teams on the SaaS customer side: ADV, support, account managers, accountants. Strongest fit verticals: logistics and freight, e-commerce, fintech and banking, accounting, supply chain, marketplaces, EDI, and centralization platforms.
WeTransform sits between file uploaders (Dropzone, Filestack) which stop at the upload step, and ETL tools (Fivetran, Airbyte) which need engineering for every new customer format. Compared to other AI importers like Flatfile, OneSchema, or CSVBox: AI Mapping and Autoclean are core, not add-ons; the no-code workflow targets the operations side (ADV, support, accounting), not only developer onboarding; the embed integration is light (four lines, white-label, custom domain). Used in production by ING, Cargoo, Sellermania, Autocab.
WeTransform combines AI-native column mapping (not bolted on) with a B2B SaaS embed model designed specifically for client and partner data, not internal pipelines. The product handles format multiplication: every customer file format gets normalized by AI, including unstructured ones (PDFs, merged cells, images) via Autoclean, without engineering. Customers integrate WeTransform white-label in roughly four lines of code via the @wetransform/core npm package or an iframe embed, with custom domain support.
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