We built Fabrik to give AI apps memory, context, and intelligence — the superintelligence layer developers need
Building an AI Productivity app?
Here is what Fabrik can do as a superintelligence layer for your AI productivity app
Unifies context so your AI sees the full picture instead of fragments.
Gives your app awareness — anticipation, insight, and continuity.
Handles memory and context so your app remembers past interactions naturally.
Lets developers focus on building instead of redoing infrastructure.
Fabrik is designed for builders who want smarter AI without rebuilding memory or context systems from scratch.
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Explore the API / SDK so your AI can access context, memory, and signals.
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Absolutely going to try this out. Agentic coders on their own can maintain a memory but you have to keep constant documentation, constant white papers have it reread them.
I look forward to your feedback Randy P
This framing makes a lot of sense. Most AI apps don’t struggle with models — they struggle with context and memory.
Abstracting that into an infrastructure layer lets builders focus on real product value instead of re-implementing the same state + context logic over and over. Curious to see how developers decide what context is worth keeping vs discarding over time.
this is the exact problem i hit while building.
initially tried to keep everything. then everything became noise. the real breakthrough was learning: context isn't about keeping more - it's about keeping what actually predicts the next thing.
we ended up using signal decay (temporal relevance) + usage patterns (what gets accessed together). but honestly, still learning what works. every use case is different.
the hardest part? users don't know what context they need until they need it. so you can't just ask. you have to observe and adapt.
That’s a great way to put it — “predicts the next thing” is the key.
While building small tools, I noticed most context people think they need is rarely reused. The useful context is usually tied to the immediate task, not long history. Curious how you balance short-term task context vs long-term memory in practice.