Company

We built the instrument
no one had.

ResourceAI measures how AI systems see your brand. Not how Google ranks you. Not how humans perceive you. How the machines understand you -- when a real buyer asks them a question at three in the morning, and your brand is either in the answer or it isn't.

The problem we saw

For twenty years, marketing teams optimized for a list of blue links. That era is ending. The next billion product decisions will happen inside an AI-generated sentence. A sentence written by GPT-5 or Claude or Gemini, in private, on a device you'll never see.

When that happens, your brand is either cited or it isn't. And right now, nobody can tell you why. SEO tools measure keywords and backlinks. Brand trackers measure human surveys. Neither measures the thing that actually decides whether an AI includes you in its answer.

We built the instrument that does.

What we actually do

ResourceAI runs a 5-stage mechanistic pipeline on your domain. We crawl your site, classify your brand, measure 182 signals per page (including tokenizer tax, chunk-gap distance, PMI co-occurrence, and retrieval authority), then run nine frontier models as judges on the residue.

The output is a 12-page editorial dossier that tells you exactly how each AI system understands your brand, where you're cited, where you're invisible, and what to change -- down to the specific file and the specific edit.

Cost per audit: approximately $0.003. Time to dossier: 30 seconds for a partial, 3 minutes for the full run.

How we're different

Mechanistic, not vibes

We don't ask an LLM 'what do you think of this brand?' That answer is noise. We parse HTML, extract schema, measure tokenizer tax, score retrieval authority, then let nine models judge the residue.

Multi-model consensus

GPT-5, Claude, Gemini, DeepSeek, Perplexity, Grok, Kimi, Mistral, and You.com. No single-model hallucination. Consensus across the full panel, or it doesn't make the dossier.

15 real capabilities

C1 through C15. Tokenizer tax, entity resolution, retrieval pool, token probability, PMI co-occurrence, seven-source analysis, chunk gaps, aggregator presence, hallucination logging, and more. Each one measured, not guessed.

Fix queue, not just findings

Every row in the dossier pairs a problem with a fix, an owner, a severity, and an estimated time to ship. Your team knows what to do Monday morning.

The team

We're a small, technical team split between Bangalore and New York. Engineers who ship, not a marketing department that hired engineers. The stack is Next.js, BullMQ, Supabase, and five LLM providers wired through a unified dispatch layer.

We built ResourceAI because we wanted to know the answer ourselves -- for our own brands, our own clients, our own curiosity about what happens when you type a question into an AI and it decides, in 200 milliseconds, which brands exist and which don't.

If that question matters to you, we should talk.

Contact

General inquiries: hello@resourceai.in

Press: press@resourceai.in

Enterprise & agencies: enterprise@resourceai.in