Embedding Studio

Embedding Studio is a self hosted AI search kit for unstructured and multimedia data. It gives products semantic search that understands the meaning of a query rather than matching keywords, and it improves from real query behavior over time. The core is open source, and the team also delivers it as a packaged search solution configured on a customer's own content and infrastructure. It is aimed at content and media rich products, marketplaces and multi sided platforms, and data heavy SaaS platforms where search drives discovery and retention. It handles multimodal and tabular data, runs in the customer's cloud or on site, and carries no ongoing SaaS fees. The delivery model has three steps: a setup review that audits the stack and data, a build phase of a few weeks using the customer's real content and queries, and a handoff in which the team receives the complete codebase and training so it can run and evolve the system independently. Optional matching logic covers cases such as job to CV matching and ticket routing. Pricing is published as fixed engagements. Starter Launchpad starts from $20,000 with a fixed scope for teams that need core semantic search, and Advanced Navigator starts from $50,000 with an expandable scope for teams investing in longer term search capability. A live demo is available, and other arrangements are handled through the contact form. Because the customer owns the resulting code, Embedding Studio competes less with hosted search APIs than with building an in house search team, which is the comparison the vendor makes itself.