The context engine that makes AI personal

Connect my Shelf with ShelfAPI — give AI my context, on my terms.

The Context Problem AI is incredibly smart but completely blind to who it's serving.

AI generates everything in real time, tailored in theory, yet treats every user like a blank slate. Every conversation starts from zero.

Current personalization works backwards:

Wait for the user to act, then try to guess what they want next. Preferences are inferred slowly and often inaccurately from shallow interaction data. Most users drop off long before the AI “figures them out.”

What if your AI knew your users from day one — and every day after?

ShelfAPI Automated context engineering for AI applications

We start upstream, with the signals users have already created: their digital patterns, the media they’ve consumed, the purchases they’ve made. Decades of authentic digital behavior become structured insights from day one, all while preserving privacy.

How it works:

1. Derive preferences directly from activity and consumption.
2. Refine with live usage to keep context current.
3. Power every tool and model with a shared context layer that travels with the user.

Today, every app has its own memory. With ShelfAPI, every user brings their own.

AI Companions & Assistants

Instead of generic responses, your AI references actual user interests and adapts to their communication style. The context engine provides conversation starters, mood awareness, and personality-matched responses.

The difference: Instead of "How are you today?" your AI can say "I see you've been listening to more melancholy music lately—what's on your mind?"

Dating & Social Applications

Access base demographic information immediately and gauge lifestyle compatibility to power matching algorithms that go far beyond self-reported interests.

The difference: Match people who both love indie documentaries and literary fiction, not just people who both selected "movies" as an interest.

Recommendation Systems

Generate recommendations that consider the full spectrum of user taste, not just single-platform behavior. The context engine reveals hidden connections between music, books, films, and lifestyle choices.

The difference: Suggest a mindfulness podcast because someone reads philosophy AND listens to ambient music AND watches slow cinema—not just because they clicked "wellness."

Deploy personalized AI in hours, not months

The context engine handles the complex infrastructure of multi-platform data ingestion, privacy management, and deep inference — all delivered through Shelf, the trust interface and brand trusted by millions — so you can focus on building great AI experiences.

Multi-platform intelligence.

Ingests from 10+ platforms to build rich personalities uniquely.

Privacy-preserving processing.

Data is user-permissioned—users are always in control.

Continuous adaptive learning.

Profiles stay current as interests and styles evolve over time.

10+

Platforms Integrated

Real-Time

Personality Inference

Context-as-a-Service.

Fast API-first integration delivers powerful context where you want it.

No cold start period.

ShelfAPI personalizes every experience from the first message.

How does ShelfAPI keep user data private?

ShelfAPI only ingests user-permitted data and includes built-in, user-controlled permissions.

Is ShelfAPI compatible with any AI model?

Yes, it delivers context in developer-optimized formats for all popular AI frameworks.

How fast can I integrate ShelfAPI?

Most developers deploy a full integration in under a day using our SDK and docs.

Get started with ShelfAPI

Deploy personalized AI in hours, not months.