Launch HN: Shaped (YC W22) – AI-Powered Recommendations and Search
Tullie and Dan from Shaped are developing a semantic recommendation platform for marketplaces, enhancing user experiences by integrating data sources and optimizing real-time data management, showing success with various clients.
Tullie and Dan from Shaped are developing a semantic recommendation and search platform aimed at enhancing user experiences for marketplaces and content companies. They have created a sandbox for users to explore demo models and evaluate results interactively. The platform addresses the challenges posed by the overwhelming amount of online content, which complicates users' ability to find relevant information. Shaped aims to empower technical teams to build advanced recommendation systems by integrating directly with various data sources, managing real-time streaming, and ensuring data quality. The platform leverages cutting-edge models for language, image, and tabular data, facilitating the extraction of value from unstructured data. Real-time optimization is a core feature, essential for the performance of recommendation systems. Shaped has already demonstrated success with clients like Outdoorsy, DribbleUp, and Overlap, reporting significant increases in conversions and user engagement. Tullie and Dan bring extensive experience from their previous roles in AI research and product development, and they are eager to receive feedback on their platform.
- Shaped is a semantic recommendation and search platform for marketplaces and content companies.
- The platform integrates with various data sources and simplifies real-time data management.
- It utilizes advanced models to enhance the extraction of value from unstructured data.
- Shaped has reported significant improvements in user engagement and conversions for its clients.
- The founders have strong backgrounds in AI research and product development.
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- Many commenters are interested in the pricing structure and suggest providing a pricing calculator to facilitate decision-making.
- Questions arise regarding the personalization capabilities of the platform and how it handles data ingestion and model monitoring.
- There is a focus on the quality measurement of recommendations and the potential for users to manipulate these metrics.
- Comparisons are made to existing solutions like Algolia and Vespa, indicating a competitive landscape.
- Several users express congratulations and interest in the platform's evolution since its previous release.
12 commentsHow are you going to allow folks to influence the system? Or do you see your system integrated behind their pseudo-recommendation engine?
Would highly recommend having at least an estimated pricing calculator so we can determine if its worth our time to install.
These days I'm the founder of a circular economy marketplace for South Asian ethnic clothing and items - PurvX. The current search is terrible (due to the low-code platform it's on), will be keeping Shaped on my radar when we re-platform.
I think that's the hardest thing on any recommendation or search system. It's really hard to do without using money as a neutral measure of value. And, without a good measure of quality - it's unclear that the system is optimizing the right metrics (without cannibalizing others).
> 100M+ Users I assume you mean 100M+ end-users have interacted with a site or product that uses your technology. The way it's phrased sounds like you're saying Shaped itself has 100M+ users which of course it doesn't. Consider replacing that with "100M+ interactions" or something.
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