Marqo

What it does

Rapidly prototype, speed up iteration and seamlessly deploy 150+ embedding models. Build powerful AI applications and transform your retrieval stack.

AI-native search, recommendations, and merchandising trained on your catalog. Marqo delivers $130M+ in proven revenue for enterprise retailers.

Turn every interaction into measurable revenue. Your catalog. Your shoppers. Your AI model. Marqo goes beyond keyword search with instant indexing, semantic relevance, typo tolerance, and multilingual comprehension, delivering accurate and meaningful results for every query. Marqo adapts in real time to shopper intent, context, and behavior, shifting fluidly between results, carousels, guided discovery, or conversational search to support any type of shopping experience. Marqo automates ranking, boosts, filters, and collections through AI, reducing manual merchandising work and enabling your team to focus on strategy while improving relevance, conversion, and revenue. Marqo's pixel can be…from marqo.ai

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  Hi HN, I’m a co‑founder of Embeddable AI. After struggling to add interactive AI experiences to Wix, Shopify, Webflow, WordPress sites, I built this tool to let marketers build chatbots, quizzes or assistants and embed them anywhere with a snippet. Built in React/TypeScript front end and Node.js logic engine. It loads fast and works across CMS platforms. I’d love feedback from builders and marketers on use cases, missing features, or integration ideas.

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  ViberiaMay 2026 · getviberia.com · ▲146

  Hey HN, This is my take on the agent harness. Everything on an isometric map. Agents are grouped into "buildings" that run in a sequence or a loop; e.g., the CodeForge has an agent that writes a PRD, another one that implements, and a third that reviews. Everything is customizable, you build your own buildings/teams however you want. It's a Tauri app, really light (about 8x less energy than the closest competitor I benchmarked, so it actually runs from a coffee shop on battery). It's macOS only for now, but ping me if you are willing to test the Windows or Linux version. I've been…

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  Marqo – Vectorless Vector Search2023 · github.com · ▲62

  Marqo is an end-to-end vector search engine. It contains everything required to integrate vector search into an application in a single API. Here is a code snippet for a minimal example of vector search with Marqo: mq = marqo.Client() mq.create_index("my-first-index") mq.index("my-first-index").add_documents([{"title": "The Travels of Marco Polo"}]) results = mq.index("my-first-index").search(q="Marqo Polo") Why Marqo? Vector similarity alone is not enough for vector search. Vector search requires more than a vector database - it also requires machine learning (ML) deployment and management,…

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