Internal concept · not for distribution

The Partnerships API

A headless access graph: define your ICP, get back everyone who has access to it — ranked, by partner type, with receipts.

100.partners · concept + worked sample against our own ICP · hand-built proof-of-concept (illustrative, not a live data pull)

The core idea

Every existing B2B database answers "who IS my ICP." This answers "who has ACCESS to my ICP."

That's not a firmographic lookup — it's a distribution graph. A partner leader (or a founder, or Hundo) describes their ideal customer, and the API returns every entity whose audience overlaps that ICP: complementary tools, agencies, communities, media, marketplaces — grouped by partner type, ranked by how strong and how warm the access is. Nobody sells this cleanly. AffiliateFinder-type tools force everyone through their UI; we expose the primitive itself, and Hundo becomes consumer #1.

Where it lives: this is Hundo's brain, exposed as an API. Find (access graph) → activate (Hundo). One loop, two surfaces — not a separate company.

The trick that makes it buildable

"Who has access to my ICP" collapses into set math, so it's engineering, not magic:

The entire product reduces to one hard problem: for any entity, estimate the set of companies it has access to. Nail that and the query is intersect-and-rank.

warmth = overlap (0–5) × mechanism strength (0–5) × fit (0–5) → 🔥 tier

overlap = how much of your ICP they reach · mechanism = how directly/credibly they hand you a customer (a warm advisor intro beats a banner) · fit = non-competitive, aligned incentive to refer.

Build partner types in order of precision

Partner typeHow we estimate their audience A(P)Precision
Complementary SaaSReverse tech-stack index — every company running tool P (BuiltWith/Wappalyzer). Exact, named companies.Highest
Integration / marketplacePublished — scrape app marketplaces (Shopify, HubSpot, Salesforce…). Literal access maps.Highest
Agencies / consultantsClient lists — case studies, "we work with," Clutch / partner directories.Medium
CommunitiesMembers / topic — inferred from who participates and what stack they discuss.Fuzzy
Newsletters / mediaAudience estimate by topic + subscriber demographics.Fuzziest

Start at the top and only the top. Tech-stack overlap gives an exact, verifiable set of named companies — a "holy shit" result with zero fuzziness and no trust problem, because you can show the receipts.

Worked sample — the access graph for the 100.partners ICP

ICP (from our own scoring model & playbook): a B2B founder doing ~$500K–$10M who knows partnerships should be a channel, has nobody who owns it, and sits in one of three states — greenfield (no program), tool-no-operator (installed an affiliate tool, nobody runs it), or stalled/dying. Signal-defined and finite.

Run "who has access to that buyer" and it resolves unusually sharply:

🔥🔥🔥 Tier 1 — highest warmth (build first)

The affiliate / PRM tool vendors themselves

Rewardful, Tolt, FirstPromoter, Refersion, Tapfiliate, Dub, PartnerStack.

Almost absurdly perfect: their entire customer base is our "tool, no operator" ICP — by definition. Rewardful's ~9,100 live sites are the enumerable market. The overlap isn't high, it's near-total.

And the incentive is aligned, not competitive: a Rewardful program that's a graveyard is churn for Rewardful. Hundo makes their tool sticky. They have a retention reason to hand us their under-activated accounts. Mechanism: co-sell / integration referral.

🔥🔥 Tier 2 — strong

Service providers in the room when CAC cracks

Fractional CMO/RevOps & growth agencies serving $500K–$10M B2B SaaS, and HubSpot Solutions Partners. When a client's paid CAC climbs (our exact "why now"), they get asked "what else?" Mechanism: referral / white-label. Medium precision — named via directories, not full client rosters.

Greenfield-founder reach (the part partnership communities MISS)

Key nuance: partnership communities (Partnership Leaders, Nearbound, Pavilion) only reach our stalled buyers — people who already care about partnerships. Our greenfield founders (highest-intent slice) aren't there yet. They're in founder / bootstrapped-SaaS spaces — MicroConf, SaaStock, indie SaaS communities, the Medellin AI meetup. Different access surface entirely.

🔥 Adjacent — diluted, second-degree

The ICP's GTM stack — Clay, Apollo, Instantly, Stripe, HubSpot. Huge reach, weak precision (not every Apollo user has a channel gap). This is where the co-occurrence math earns its keep by filtering down.

What the sample already proves

1. The access graph converges on our own signal-campaign playbook

Our Dub/Tolt/Rewardful signal campaigns already target these exact tool vendors' customers. The hand-built access graph independently landed on the same place. That's a validation event: the product, once built, would automatically reproduce the best GTM instinct we reached by hand — the "it found what I already know is right" test, passing on our own data.

2. There's a live 100.partners move here today — no product required

We should be building actual distribution partnerships with Rewardful, Tolt, Dub, and FirstPromoter now. Their churning "graveyard program" accounts are the perfect Hundo wedge, and saving those accounts is the vendor's retention win. A co-sell partnership pitchable this month. The product systematizes it later; the partnership is worth doing regardless.

v2 product implication — a signal layer. Our ICP is finite and signal-defined, so the graph gets far stronger fused with "who is showing a buying signal right now" — who can reach the slice of the ICP that just installed a tool / posted a partner role / raised a round. That's the difference between a static list and a live feed, and a moat pure audience-overlap competitors won't have. Don't build first; know it's where this goes.

Recommended first build

Not the full API. The tech-stack co-occurrence engine for one vertical, exposed as a minimal API, with us as user zero. One partner type (complementary SaaS), done with exact evidence, beats five done fuzzily. Prove "found 20 real partners with access to the 100.partners ICP, with receipts." Then widen partner types → let Hundo drive it → add the signal layer.

  1. Resolve ICP → T (rented firmographics).
  2. Precompute the co-occurrence index — the graph. Refresh monthly.
  3. Score & rank: overlap × mechanism × fit, grouped by partner type.
  4. Every result carries why ("overlaps on N accounts") + a last-verified date. This is the trust layer.
  5. Expose as API. Hundo is consumer #1.

The moat isn't the firmographics (commodity) — it's the partner-signal layer, the ranker, and the evidence loop: every partnership Hundo actually lands writes back a verified access edge. Over time the graph stops being inferred and becomes validated-by-outcome. AffiliateFinder can't copy that; they don't run the activation layer. We do.