https://rerun.io/_app/immutable/nodes/8.C6whcpuo.js

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2    Designed for multi-rate, multimodal data, from the first recording to
3    massive scale.</p> <div class="mt-7 flex flex-wrap justify-start gap-2 md:justify-center"><!> <!></div></section> <section class="md:mx-auto max-w-3xl px-4 sm:px-6 pt-24 pb-0 sm:py-10"><!></section> <section class="md:mx-auto max-w-page px-4 sm:px-6 pt-24 md:pt-20"><header class="md:mx-auto max-w-3xl text-left md:text-center"><h2 class="heading-2 md:mx-auto"><span class="text-[color:var(--color-muted)]">End-to-end learning</span><br/>

3needs end-to-end data</h2> <p class="md:mx-auto mt-5 large">End-to-end models learn from multi-rate, multimodal sequences. So every
4      stage of the loop works on that same data: collect, refine, train, deploy.
5      Rerun is one layer underneath all of it.</p></header> <div class="mt-6"><!></div></section> <section class="md:mx-auto max-w-page px-4 sm:px-6 pt-24 md:pt-32"><header class="md:mx-auto max-w-3xl text-left md:text-center"><h2 class="heading-2 md:mx-auto"><span class="text-[color:var(--color-muted)]">Two parts.</span> One data layer.</h2> <p class="md:mx-auto mt-5 large">The Rerun SDK is the open-source toolchain physical AI teams build on.
6      Rerun Hub is the production backend that connects it to your data at
7      scale.</p></header> <div class="md:mx-auto mt-12 grid max-w-4xl gap-6 md:grid-cols-2 md:gap-0"><article class="flex h-full flex-col justify-center rounded-3xl border border-[var(--color-border)] bg-[var(--color-bg)] p-8 md:p-10"><p class="caption text-[color:var(--color-muted)]">Open source</p> <h3 class="heading-3 mt-1">Rerun SDK</h3> <p class="mt-4 text-[color:var(--color-muted)]">Open-source SDK for logging, storing, querying, visualizing, and
8        training on multi-rate, multimodal data. Includes viewer, query library,
9        visualization framework, CLI, and the file format the data layer is

10        built on.</p> <div class="mt-2"><!></div> <ul class="mt-2 space-y-2 text-[color:var(--color-fg)]"></ul> <div class="mt-8 flex flex-wrap gap-2"><!> <!></div></article> <article class="flex flex-col self-center rounded-3xl border border-[var(--color-border)] bg-[var(--color-bg)] p-8 md:rounded-l-none md:p-10 md:[border-left:none]"><p class="caption text-[color:var(--color-muted)]">Commercial</p> <h3 class="heading-3 mt-1">Rerun Hub</h3> <p class="mt-4 text-[color:var(--color-muted)]">The production backend for the Rerun data layer. Catalog, byte-range
11        indexing, and retrieval that turns your object stores into a queryable,
12        streamable foundation. Run transforms on the edge or close to the data.</p> <ul class="mt-6 space-y-2 text-[color:var(--color-fg)]"></ul> <div class="mt-8 flex flex-wrap gap-2"><!> <!></div></article></div></section> <section class="md:mx-auto max-w-page px-4 sm:px-6 pt-24 md:pt-32"><header class="md:mx-auto max-w-3xl text-left md:text-center"><h2 class="heading-3 md:mx-auto">How they fit together</h2> <p class="md:mx-auto mt-3 large">You log, query, visualize, transform, and train with the same open-source
13      SDK and the same APIs either way. Hub doesn't change what you do. It
14      changes what runs underneath.</p></header> <div class="mt-10 overflow-hidden border border-[var(--color-border)]"><div class="hidden text-[color:var(--color-muted)] md:grid md:grid-cols-[0.7fr_1fr_1.4fr]"><div class="px-5 py-4"></div> <div class="px-5 py-4"><span class="block text-[color:var(--color-fg)] heading-6">Rerun SDK</span> <span class="caption mt-1 inline-block">Open source</span></div> <div class="px-5 py-4"><span class="block text-[color:var(--color-fg)] heading-6">Rerun Hub</span> <span class="caption mt-1 inline-block">Commercial</span></div></div> <!></div></section> <section class="md:mx-auto max-w-5xl px-4 sm:px-6 pt-24 md:pt-32 pb-24 md:pb-32 text-left md:text-center"><h2 class="heading-2 md:mx-auto">Iterate faster on robot learning data</h2> <p class="md:mx-auto mt-5 max-w-2xl large">Build, understand, and improve your data loop on one set of primitives, from
15    your first recording to massive scale. Start with the SDK, or talk to us
16    about Hub.</p> <div class="mt-8 flex flex-wrap justify-start gap-2 md:justify-center"><!> <!></div></section>`,1);function Wt(Oe){const Ye={sources:{"get-started":{cpp:`# Add this to your CMakeLists.txt:
17include(FetchContent)
18FetchContent_Declare(rerun_sdk URL
19https://github.com/rerun-io/rerun/releases/latest/download/rerun_cpp_sdk.zip)
20FetchContent_MakeAvailable(rerun_sdk)`,python:`pip install rerun-sdk
21rerun`,rust:`cargo install rerun-cli --locked
22rerun`}},rrdUrls:{}},Fe=["pip install rerun-sdk","Interactive viewer + visualization framework","Dataframe query library built in","Multi-rate, multimodal, spatial native","Python, Rust, and C++ APIs","Open source. Start in two minutes."],ve=["Query across multiple object stores","Byte-range indexing for fast lookups","Stream dataset mixes directly to training","Catalog and metadata management","Deployed to your preferred cloud region"];var Te=Pt(),Se=Ke(Te);mt(Se,{title:"Product",ogTitle:"The Data Layer for Physical AI",description:"The data primitives to build, understand, and improve your data loop. Designed for multi-rate, multimodal data, from the first recording to massive scale."});var V=r(Se,2),Ce=i(V);L(Ce,(t,o)=>E?.(t,o),()=>j);var Ae=r(Ce,2);L(Ae,(t,o)=>E?.(t,o),()=>j);var ue=r(Ae,2),Pe=i(ue);W(Pe,{variant:"primary",href:"/docs/getting-started/quick-start",children:(t,o)=>{q();var c=ce("Get started");b(t,c)},$$slots:{default:!0}});var Ge=r(Pe,2);W(Ge,{variant:"secondary",href:"https://5li7zhj98k8.typeform.com/to/a5XDpBkZ",children:(t,o)=>{q();var c=ce("Talk to us");b(t,c)},$$slots:{default:!0}}),s(ue),s(V);var ee=r(V,2),ze=i(ee);ft(ze,{stats:[{value:"__GH_STARS__",label:"GitHub stars"},{value:"__LANG_COLLAGE__",label:"3 supported languages"},{value:"End-to-end",label:"Collection to training"}]}),s(ee);var me=r(ee,2),P=i(me),z=i(P);L(z,(t,o)=>E?.(t,o),()=>j);var te=r(z,2);L(te,(t,o)=>E?.(t,o),()=>j),s(P);var O=r(P,2),U=i(O);Tt(U,{}),s(O),s(me);var Y=r(me,2),ae=i(Y),he=i(ae);L(he,(t,o)=>E?.(t,o),()=>j);var De=r(he,2);L(De,(t,o)=>E?.(t,o),()=>j),s(ae);var J=r(ae,2),re=i(J),F=r(i(re),6),fe=i(F);ht(fe,{id:"product-overview-get-started",name:"get-started",get snippets(){return Ye}}),s(F);var N=r(F,2);A(N,5,()=>Fe,t=>t,(t,o)=>{var c=it(),y=i(c);ot(y,{size:16,"aria-hidden":"true",class:"mt-1 shrink-0 text-[color:var(--color-muted)]"});var R=r(y,2),D=I(R,!0);s(c),H(()=>K(D,d(o))),b(t,c)}),s(N);var ge=r(N,2),oe=i(ge);W(oe,{variant:"primary",href:"/sdk",children:(t,o)=>{q();var c=St(),y=r(Ke(c));rt(y,{size:16,"aria-hidden":"true"}),b(t,c)},$$slots:{default:!0}});var We=r(oe,2);W(We,{variant:"secondary",href:"https://github.com/rerun-io/rerun",target:"_blank",rel:"noopener noreferrer",children:(t,o)=>{q();var c=ce("GitHub");b(t,c)},$$slots:{default:!0}}),s(ge),s(re);var se=r(re,2),le=r(i(se),6);A(le,5,()=>ve,t=>t,(t,o)=>{var c=it(),y=i(c);ot(y,{size:16,"aria-hidden":"true",class:"mt-1 shrink-0 text-[color:var(--color-muted)]"});var R=r(y,2),D=I(R,!0);s(c),H(()=>K(D,d(o))),b(t,c)}),s(le);var xe=r(le,2),be=i(xe);W(be,{variant:"primary",href:"/hub",children:(t,o)=>{q();var c=Ct(),y=r(Ke(c));rt(y,{size:16,"aria-hidden":"true"}),b(t,c)},$$slots:{default:!0}});var Me=r(be,2);W(Me,{variant:"secondary",href:"https://5li7zhj98k8.typeform.com/to/a5XDpBkZ",children:(t,o)=>{q();var c=ce("Book a meeting");b(t,c)},$$slots:{default:!0}}),s(xe),s(se),s(J),s(Y);var Q=r(Y,2),ne=i(Q),ye=i(ne);L(ye,(t,o)=>E?.(t,o),()=>j);var ie=r(ye,2);L(ie,(t,o)=>E?.(t,o),()=>j),s(ne);var e=r(ne,2),M=r(i(e),2);A(M,2,()=>[{label:"Your data",sdk:"Local .rrd files on one machine",hub:"Your object storage, streamed at petabyte scale"},{label:"The catalog",sdk:"In-process, for local work",hub:"Persistent and managed, indexed across your object stores"},{label:"Access",sdk:"Just you",hub:"Your team, with SSO and authenticated share links"},{label:"Running it",sdk:"pip install, self-hosted",hub:"Run for you, single-tenant, in your cloud region of choice"}],t=>t.label,(t,o,c)=>{var y=At();let R;var D=i(y),Ue=I(D,!0),de=r(D,2),_e=r(i(de),2),$=i(_e);st($,{size:16,"aria-hidden":"true",class:"shrink-0 text-[color:var(--color-muted)]"});var Be=r($,2),Je=I(Be,!0);s(_e),s(de);var Le=r(de,2),je=r(i(Le),2),we=i(je);st(we,{size:16,"aria-hidden":"true",class:"shrink-0 text-[color:var(--color-muted)]"});var Ee=r(we,2),qe=I(Ee,!0);s(je),s(Le),s(y),H(()=>{R=pe(y,1,"grid grid-cols-1 gap-y-3 border-t border-[var(--color-border)] px-5 py-4 md:grid-cols-[0.7fr_1fr_1.4fr] md:gap-y-0",null,R,{"bg-[var(--color-code-bg)]":d(c)%2===0}),K(Ue,o.label),K(Je,o.sdk),K(qe,o.hub)}),b(t,y)}),s(e),s(Q);var n=r(Q,2),v=i(n);L(v,(t,o)=>E?.(t,o),()=>j);var m=r(v,2);L(m,(t,o)=>E?.(t,o),()=>j);var h=r(m,2),f=i(h);W(f,{variant:"primary",href:"/docs/getting-started/quick-start",children:(t,o)=>{q();var c=ce("Install the SDK");b(t,c)},$$slots:{default:!0}});var k=r(f,2);W(k,{variant:"brand",href:"https://5li7zhj98k8.typeform.com/to/a5XDpBkZ",children:(t,o)=>{q();var c=ce("Book a meeting");b(t,c)},$$slots:{default:!0}}),s(h),s(n),b(Oe,Te)}export{Wt as component};