// marketplace.jsx — Workforce Catalog as a personalized AI advisor (category-based) const { useState: useStateM } = React; // Each category: insight + KPIs + agents ranked by match (first = Recommended For You, with reasons) const CATS = [ { id:"saledev", name:"Sales Development", icon:"builder", insight:"Based on your profile, London recommends focusing on outbound account discovery and ICP scoring.", kpis:{ rev:"$3.2M", cost:"$1.2K/mo", deploy:"~1 wk", conf:"96%" }, agents:[ {code:"PRX",match:98,reasons:["Salesforce detected","North America ICP","Pipeline growth objective","Budget compatible"]},{code:"OUT",match:91},{code:"BRF",match:84} ] }, { id:"leadgen", name:"Lead Generation", icon:"target", insight:"Your inbound + outbound mix favors continuous ICP scoring with real-time enrichment.", kpis:{ rev:"$2.6M", cost:"$1.2K/mo", deploy:"~1 wk", conf:"94%" }, agents:[ {code:"PRX",match:95,reasons:["ICP scoring matches goal","Inbound + outbound coverage","Clay + Apollo connected","Budget compatible"]},{code:"QAL",match:93},{code:"ENR",match:88} ] }, { id:"intel", name:"Intelligence", icon:"signal", insight:"With Bright Data connected, London recommends maximizing buying-signal detection.", kpis:{ rev:"$2.9M", cost:"$2.1K/mo", deploy:"~3 days", conf:"95%" }, agents:[ {code:"SIG",match:97,reasons:["Bright Data connected","Buying-signal objective","Real-time enrichment","North America coverage"]},{code:"ENR",match:90},{code:"CMP",match:85} ] }, { id:"outbound", name:"Outbound", icon:"mail", insight:"Executive-grade sequencing with human approval fits your guardrails and growth goal.", kpis:{ rev:"$2.4M", cost:"$1.7K/mo", deploy:"~1 wk", conf:"92%" }, agents:[ {code:"OUT",match:96,reasons:["Gmail connected","Executive-grade sequencing","Pipeline growth objective","Approval guardrails set"]},{code:"PRX",match:90},{code:"BRF",match:82} ] }, { id:"sales", name:"Sales", icon:"briefcase", insight:"Fast inbound routing gets AEs to the right accounts first — high ROI, low setup.", kpis:{ rev:"$2.1M", cost:"$760/mo", deploy:"~3 days", conf:"96%" }, agents:[ {code:"QAL",match:96,reasons:["Inbound routing need","HubSpot connected","Fast time-to-value","Budget compatible"]},{code:"BRF",match:90},{code:"NEG",match:84} ] }, { id:"strategy", name:"Strategy", icon:"globe", insight:"Your EMEA expansion plans call for living TAM maps and balanced territory planning.", kpis:{ rev:"$1.6M", cost:"$1.1K/mo", deploy:"~2 wks", conf:"90%" }, agents:[ {code:"MKT",match:92,reasons:["EMEA expansion plans","Territory planning need","Firmographic data ready","Budget compatible"]},{code:"CMP",match:88} ] }, { id:"cs", name:"Customer Success", icon:"heart", insight:"Protecting installed-base revenue: predict churn early and surface expansion windows.", kpis:{ rev:"$1.9M", cost:"$1.3K/mo", deploy:"~1 wk", conf:"91%" }, agents:[ {code:"RNW",match:94,reasons:["Product usage connected","Churn-risk priority","Expansion signals","Salesforce connected"]},{code:"ADV",match:86} ] }, { id:"revops", name:"Revenue Operations", icon:"analytics", insight:"Tighten forecasting and routing across your CRM stack with deal-level risk scoring.", kpis:{ rev:"$2.2M", cost:"$1.45K/mo", deploy:"~1 wk", conf:"93%" }, agents:[ {code:"FCT",match:95,reasons:["Pipeline forecasting need","Salesforce + HubSpot connected","Deal-level risk scoring","Budget compatible"]},{code:"QAL",match:88} ] }, { id:"forecast", name:"Forecasting", icon:"trendUp", insight:"Scenario modeling on connected CRM data improves forecast accuracy quarter over quarter.", kpis:{ rev:"$2.0M", cost:"$1.45K/mo", deploy:"~1 wk", conf:"93%" }, agents:[ {code:"FCT",match:97,reasons:["Forecast accuracy goal","Scenario modeling","CRM connected","Budget compatible"]},{code:"SIG",match:84} ] }, { id:"compete", name:"Competitive Intelligence", icon:"zap", insight:"Win more competitive deals with always-on pricing tracking and auto-generated battlecards.", kpis:{ rev:"$1.4M", cost:"$940/mo", deploy:"~3 days", conf:"94%" }, agents:[ {code:"CMP",match:96,reasons:["Competitive deals priority","Bright Data connected","Auto-generated battlecards","Budget compatible"]},{code:"SIG",match:89} ] }, ]; function agentByCode(code){ return window.LondonData.CATALOG.find(c=>c.code===code); } function MatchRing({ value, size=58 }) { const r=(size-8)/2, c=2*Math.PI*r, len=(value/100)*c, cx=size/2; return (
{value}
); } function RecommendedCard({ entry }) { const a = agentByCode(entry.code); if(!a) return null; return (
RECOMMENDED FOR YOU {entry.match}% Match {a.installed && Deployed}
{a.code}
{a.name}
{a.fn}

{a.desc}

Cost
{a.cost}
Performance
{a.perf}/100
Department
{a.dept}
Why it matches
{entry.reasons.map((r,i)=>(
{r}
))}
); } function OtherRow({ entry, rank }) { const a = agentByCode(entry.code); if(!a) return null; const tag = entry.match>=90 ? ["violet","Strong match"] : ["gray","Alternative"]; return (
#{rank} {a.code}
{a.name}{a.installed && Deployed}
{a.fn}
{tag[1]}
{entry.match}%
{a.cost}
); } function CategoryView({ cat }) { const rec = cat.agents[0]; const others = cat.agents.slice(1); const kpis = [ { l:"Est. revenue impact", v:cat.kpis.rev, c:"var(--green)" }, { l:"Recommended cost", v:cat.kpis.cost }, { l:"Deployment time", v:cat.kpis.deploy }, { l:"Confidence score", v:cat.kpis.conf, c:"var(--violet)" }, ]; return (

{cat.name}

{cat.insight}

{kpis.map(k=>(
{k.l}
{k.v}
))}
{others.length>0 && (
Other agents in this category ranked by match
{others.map((e,i)=> )}
)}
); } function MarketplacePage() { const [active, setActive] = useStateM(CATS[0].id); const cat = CATS.find(c=>c.id===active); const deployed = window.LondonData.CATALOG.filter(a=>a.installed).length; return (

AI Workforce Recommendations

Curated for you

London curates the right agents for each GTM function — ranked by fit to your company profile, not an A–Z list.

{/* profile bar */}
Personalized for Acme Inc · {["Salesforce","North America","Mid-market SaaS","Series B+"].map(t=>( {t} ))} {deployed}/12 deployed
{/* category pills */}
{CATS.map(c=>( ))}
); } window.MarketplacePage = MarketplacePage;