
20+ engineers deployed across frontend, backend, and data — delivering roadmap commitments and building the data infrastructure for AI-driven procurement.
Shipsta (now operating as Freightos) is a B2B freight procurement platform serving enterprise shippers and carriers including McDonald's, Puma, and Roche. It competes in a technically demanding market where rate management, eProcurement workflows, and logistics analytics must function at multinational scale. The platform's commercial trajectory at the time of engagement required an engineering operation that could match its sales pipeline.
Shipsta faced a structural gap between what the roadmap required and what the team could build. A per-customer data architecture had accumulated over time, creating a fragmented environment that was difficult to scale and expensive to extend.
Technical debt had built up at a rate that was beginning to limit what the product could do next. Core data engineering skills were absent internally, which meant the procurement automation roadmap the business had committed to was not executable with the team as constituted.
Primero Group deployed a team across frontend, backend, and data engineering, embedded directly into Shipsta's product organisation and operating on the same sprint cadence. The immediate priority was delivering the features enterprise clients were expecting: shipper onboarding tools, carrier-facing pricing visibility, and in-platform market rate data.
Procurement workflow automation followed, removing manual effort from quote requests, spot tenders, and rate selection. In parallel, the data engineering work designed and began building a target-state architecture: a standardized data model, centralised analytics layer, and the lakehouse and knowledge graph infrastructure that Shipsta's AI-driven autonomous procurement roadmap would ultimately require.
This engagement demonstrates the Group's capacity to operate as a sustained engineering partner at enterprise software scale. The combination of product feature delivery and long-horizon data architecture work in a single engagement reflects the depth of capability the Group can deploy.