orbis://why-orbis/algorithm
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$ orbis --our-algorithm
[boot]algorithm=proprietary · database=275M individuals · pairing=the productok
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The Orbis algorithm
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A database on its own is just a list. The Orbis algorithm is what turns 275 million individuals into the handful of people who actually matter to your business — reading what you do, deciding who is relevant, and verifying every match before a single email is sent.
inputyour business contextdatabase275M individualsoutputverified, relevant contacts
SEC.01
What the algorithm does
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When you give Orbis your business URL, the algorithm reads what your company actually is — what you sell, who buys it, and the signals that separate a real prospect from a name on a list. It then maps that understanding against the database and selects the individuals most likely to matter to you.
-Reads your business — your site, your offer, your market.
-Maps it against the database — matching your context to the right individuals.
-Decides relevance — not just industry, but the signals that indicate a genuine fit.
SEC.02
Paired with the database
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An algorithm is only as good as the data underneath it. Orbis's matching runs against a proprietary database of 275 million individuals, sourced through our own discovery pipeline and continuously refreshed — not a shared, recycled list that every competitor is already burning through.
pairing.md
- algorithm
- proprietary matching + verification
- database
- 275,000,000 individuals
- sourcing
- proprietary discovery pipeline
- freshness
- continuously refreshed
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The pairing is the product. The same algorithm pointed at a stale public list would produce the same burned-out results everyone else gets; the same database without the algorithm would be an unusable haystack. Orbis is both, developed together.
SEC.03
Verification built in
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Matching decides who to contact; verification decides whether the contact holds up. Every match is challenged through multi-stage verification — layered checks run together, not in isolation — so accuracy holds at database scale, not just on a curated sample.
why it matters
Every bounce trains inbox providers to distrust your domain. Verification built into the matching pipeline — not bolted on after — keeps your sender reputation clean while the algorithm works at full scale.
SEC.04
It learns
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Every campaign run through Orbis feeds the system: matching gets sharper, verification gets stricter, the data stays current. Accuracy at this level comes from sustained iteration against real sends — and it compounds, because each campaign makes the next one better.
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This is why the algorithm can't be scaffolded in a sprint. It's the product of continuous development against a proprietary dataset at live volume.
SEC.05
What this means for you
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You don't need to build any of this. From your first campaign, you get the output of the algorithm and the database working together — fresh, verified, relevant contacts matched to your business.
Put the algorithm to work on your business.
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