{"id":97225,"title":"ShapedQL: The SQL engine for search, feeds, and AI agents","tagline":"Connect your data. Train your models. Query text, user or session context and retrieve relevant results in milliseconds.","body":"Hi everyone 👋\\\n\\\nI'm Tullie, the founder of [Shaped](https://www.shaped.ai/).\\\n\\\n**TL;DR**\\\n\\\nToday we’re launching ShapedQL, a new language purpose built for agents, feeds and search. We built ShapedQL because we realized that while retrieval has become easier (thanks to Vector DBs), ranking and relevance are still incredibly hard.\\\n\\\nLaunch video: \u003chttps://www.youtube.com/watch?v=Owj_uSUPNaU\u003e\\\n\\\n**Problem ❌**\\\n\\\nMost engineering teams we talk to are stuck maintaining a \"Frankenstein\" stack. To build a \"For You\" feed or give an AI Agent personalized memory, they have to glue together a vector database, a feature store (like Redis), a reranking service, and thousands of lines of Python spaghetti code.\\\n\\\n**Solution ✅**\\\n\\\nWe built ShapedQL to turn that \"house of cards\" into a single interface.\n\n![uploaded image](/media/?type=post\u0026id=97225\u0026key=user_uploads/812951/eed67b43-7c3b-4b0f-819a-5bbd31db2732)\n\nShapedQL is a domain-specific SQL dialect that compiles down to a high-performance, multi-stage ranking pipeline. With a single query, you can define the four stages of modern relevance:\\\n**1. Retrieve:** Fetch candidates from multiple sources (Hybrid Search, Collaborative Filtering, Trending).\\\n**2. Filter:** Apply hard constraints (e.g., \"in stock\" or \"within 50 miles\").\\\n**3. Score:** Rank results using real-time ML models (optimizing for clicks, purchases, or watch time).\\\n**4. Reorder:** Enforce diversity so your users (or Agents) don't see the same 5 items repeatedly.\n\nWe're seeing teams reduce 2,000+ lines of maintenance code down to \\~30 lines of ShapedQL, while shipping features like \"Cart Upsell\" or \"Conversational Recommendations\" in days instead of months.\n\nIf you're not a fan of SQL we also have Python or Typescript SDKs, perfect for a real-time production integration.\n\n![uploaded image](/media/?type=post\u0026id=97225\u0026key=user_uploads/812951/d3cc12cc-3c74-448b-adf0-ae65d9359b79)\n\n**Ask 💬**\\\n\\\n**1.** We have a Product Hunt launch at this link: \u003chttps://www.producthunt.com/products/shaped\u003e. Any support or and upvote would be greatly appreciated!\\\n\\\n**2.** Please try out our interactive demo at [playground.shaped.ai](https://playground.shaped.ai), we’d love to hear any feedback on the new language. Were you able to easily make a query? Do the docs make sense? What is it missing?\\\n\\\n**3.** If the problems above resonates and you’re struggling to get true relevance from your vector store or current retrieval system, please get in touch! Book on this calendar here: \u003chttps://www.shaped.ai/contact\u003e and mention you’re from YC. I’ll make sure to jump on the call to help you out myself.\n\n![uploaded image](/media/?type=post\u0026id=97225\u0026key=user_uploads/812951/bb70b2b7-780a-4da6-a13f-511015e09776)\n\n","slug":"PI9-shapedql-the-sql-engine-for-search-feeds-and-ai-agents","created_at":"2026-01-28T00:44:48.253Z","updated_at":"2026-05-25T01:17:05.481Z","total_vote_count":15,"url":"https://www.ycombinator.com/launches/PI9-shapedql-the-sql-engine-for-search-feeds-and-ai-agents","share_image_url":"https://www.ycombinator.com/media/?type=post\u0026id=97225\u0026key=user_uploads/812951/bb70b2b7-780a-4da6-a13f-511015e09776","company":{"id":25969,"name":"Shaped","slug":"shaped","url":"https://shaped.ai","logo":"https://bookface-images.s3.amazonaws.com/small_logos/241b1f1931647920258ef5ae6571461ada0b62f1.png","batch":"Winter 2022","industry":"B2B","tags":["Search","AI","Recommendation System"],"search_path":"https://bookface.ycombinator.com/company/25969"}}