Kitor connects brands and creators through one AI layer: plain-English creator discovery, brand-fit scoring, predictive campaign planning, and an autonomous agent that sources, drafts, and negotiates deals.
Brands pick creators on gut feel and vanity metrics — follower counts that may be inflated, engagement that may be bought, and no way to predict what a campaign will actually return. Creators, on the other side, juggle analytics, inbound deals, rate-setting, and negotiation across a dozen disconnected tools.
Kitor puts both sides on one AI platform. Brands describe a campaign in plain English and get a ranked shortlist of best-fit creators, each scored for brand fit and audience authenticity, with predicted reach, engagement, and conversions before a cent is spent. A campaign planner simulates ROAS across budget scenarios and allocates spend across creator tiers.
Creators get the mirror image: a live analytics dashboard, an AI-matched brand-deals inbox, a share-ready media kit with AI-suggested rates, earnings forecasting — and an autonomous agent that sources deals, drafts outreach, and negotiates rates overnight, flagging anything that needs a human call.
Live performance, audience demographics, and AI-predicted reach, with an AI summary of what's working.
Brands describe a campaign in natural language; AI returns ranked, filterable creators sorted by brand fit.
Brands choose creators on follower counts, not fit — and can't tell a real audience from a bought one.
Campaigns are committed blind, with no way to simulate reach, conversions, or return beforehand.
Content risk and fake-follower flags surface after the deal, not before.
Creators run analytics, deals, rates, and negotiation across scattered tools, by hand.
One platform, two experiences (Client / Creator), designed around a shared creator data model.
Plain-English brief → ranked creators, with brand-fit and authenticity scoring.
Campaign simulation — reach, conversions, ROAS, and tiered budget allocation.
Analytics, deals inbox, AI media kit & rate card, earnings forecasting.
An AI manager that sources, drafts, and negotiates deals with human-in-the-loop flags.
Describe a campaign in plain English; AI finds and ranks best-fit creators from the pool.
A 0–100 match with reasons — audience overlap, content tone, brand-safe history, save/share behaviour.
Real-vs-fake audience analysis, engagement authenticity, and content-risk scanning before commitment.
Simulate reach, conversions, and ROAS across budget scenarios with AI tier allocation.
An agent that sources deals, drafts outreach, and negotiates rates while flagging human decisions.
AI-generated, share-ready media kit with suggested rates and rate-health benchmarking.
Brands and creators work off the same AI-vetted creator data. The brand side turns a plain-English brief into a ranked, brand-safe shortlist with predicted outcomes; the creator side turns the same signals into matched deals, suggested rates, and an autonomous agent — so both sides negotiate from the same source of truth.
A 0–100 match with the reasons behind it, authenticity score, and AI-forecast reach, engagement, and conversions.
Simulated reach, conversions, and ROAS across conservative/balanced/aggressive scenarios, with AI budget allocation by tier.
An agent that sources deals, drafts outreach, and negotiates overnight — with a live queue and human-in-the-loop flags.
Brand-safety score, authenticity, audience-quality breakdown, content scan, and anomaly checks before committing.
Incoming offers ranked by AI fit and payout, with deliverables, deadlines, and total estimated value.
A share-ready kit with audience breakdown and AI-suggested rates, plus a rate-health benchmark vs market.
Deals pipeline by stage, monthly earnings, recent payouts, and an AI revenue forecast.
