Sensei vs. Perplexity

Perplexity answers with sources. Sensei answers with your receipts.

The sharpest citation isn't a link to the web. It's the revenue number from your Stripe, the traffic from your Plausible, the deploy from your Vercel — and a dated prediction Sensei grades itself on next week.

Where they split

Three honest differences. Not one of them is a feature.

  • What the citation points to

    Perplexity

    A web source the model found while researching your question.

    Sensei

    Your own numbers, pulled live from the systems you already run. The reading cites $X MRR, not a blog post.

  • Whether it holds itself accountable

    Perplexity

    Each answer stands alone. There's no ledger of what it told you last week.

    Sensei

    Predictions with Receipts — every call Sensei makes is dated and graded against reality the next week.

  • Whether it knows your field

    Perplexity

    A generalist researcher. Your competitors are whatever the web surfaces today.

    Sensei

    A tracked rival set. Sensei watches the same ten competitors every week and names who moved.

The stack

Four things stacked.

Any AI can be brilliant when you bring the evidence. These four are what change when the evidence comes to you.

Live integrations

Stripe, Plausible, Vercel connect by OAuth. The reading cites your actual revenue, traffic, and ship log — inline, by number.

Pushed cadence

Monday 7am local, every week. The reading lands in the inbox before the first meeting. The ritual is the product.

Cohort aggregation

Thresholds and framing come from a cohort of founders at your stage, your ACV, your motion. Not a global average.

Proactive scraping

A tracked rival set scanned every week. Sensei names who moved and what it means for your lane, without being asked.

Any one of these is nice. Stacked, it’s the product.

The close

Still chatting with Perplexity?

Paste your URL. Sensei reads. You decide.