Clay Alternatives: Build Waterfall Enrichment With APIs

Find a work email, check it, and try a second provider on a miss, in one prompt. Paste this into your agent:

Set up https://monid.ai/SKILL.md, and then use Monid to find the work email of Patrick Collison at stripe.com with Hunter, verify the address, and if Hunter finds nothing fall back to People Data Labs person enrich. Give me the address, the confidence score and which provider answered.

One prompt runs a two-step waterfall. 1 min setup · 6-14 hrs saved.

You are looking at Clay because you want to enrich a list: a name and a company in, a verified work email out. You want to know if you can get the same result without a platform, through APIs your agent or script calls directly. This guide covers what a waterfall is, the short loop that replaces it, and the traps we hit in the output when we ran the endpoints on 2026-10-16. It runs through Monid, the OpenRouter for agent tools: one key, one balance, every tool priced per call.

What is the easiest way to replace Clay with an API?

Monid. Install it once, add a key, and your agent calls an email-finder endpoint, a verifier and a second provider on the same balance, with no per-vendor contract and no table to maintain.

• Pay per call. The finder costs $0.0245 per address found, and the verifier $0.01225 per verdict (Verified 2026-10-16 on the people enrichment tools page). Buy calls as you need them: no monthly plan and no minimum top-up. Discovery and inspection are free; only a run bills.
• One install, every provider. The same key and balance call Hunter, People Data Labs and every other tool on Monid. A new rung is one more line in your loop.
• Lives inside your agent. Install the CLI, add your key, run the prompt above, and the endpoints are there whenever your agent needs them, with nothing to keep running. Setup is about a minute.

Finding and verifying one address costs $0.03675 (Verified 2026-10-16: $0.0245 plus $0.01225), which is what we paid in our own run.

What is waterfall enrichment, and what is Clay actually selling?

Waterfall enrichment means asking several providers for the same field in sequence and keeping the first answer that comes back. Clay is a spreadsheet-style product that runs those sequences for you. That is two things bundled: a table you work in, and the fall-through logic underneath it.

Why does one provider never cover everyone?

Each provider builds its records from different raw material. One reads public web pages, another reads profile and resume data, a third buys lists. Their gaps are different shapes, so a second provider fills holes the first leaves. We saw the hole in our own run: Hunter returned an address for a real person and returned nothing for an invented name at the same domain.

What makes a waterfall worth running?

A miss has to be free. If every rung charges whether or not it answers, stacking providers is paying twice for one record. We checked it on 2026-10-16. The finder missed on the invented name and the run came back with billedUnits: 0 and a cost of zero. The inspect page says the same: the finder is "charged only when an address is found". With free misses, sequencing providers costs nothing extra on the records the first rung already answered.

What do the alternatives lists compare?

Most "best Clay alternatives" lists compare Clay with data vendors such as Apollo, ZoomInfo and Cognism, as the People Data Labs, Apollo and ZoomInfo breakdown does. Those sell records. Clay sells the table and the sequencing around records bought from others, so the two are different purchases.

How do you build a waterfall enrichment workflow without Clay?

Three steps: find the rungs, verify what they return, and write the fall-through.

Monid fits a waterfall because the work is the same call repeated across providers, and you pay for the calls that return something and nothing between runs.

For agents

Grab an API key at app.monid.ai, then paste this to your agent and hand it the key:

set up https://monid.ai/SKILL.md

It learns the whole discover, inspect, run workflow itself. More in the agent quickstart.

For humans

npm install -g @monid-ai/cli
monid keys add -k <your-api-key> -l main

Step 1. Find the rungs

Discovery lists the providers that answer the same question, with their billing shape, so you can sort them into an order. It is free.

monid discover -q "find a work email address for a person"
monid inspect -p hunterio -e /email-finder

inspect on the finder reports an address with a 0 to 100 confidence score, job title, company, social handles, up to twenty public source URLs and an automatic deliverability check. It also reports a max_duration knob between 3 and 20 seconds that trades latency for accuracy. Inspection never bills.

Step 2. Verify before you believe

Verification separates an address that exists from one that was guessed.

monid run -p hunterio -e /email-verifier -w --query '{"email": "someone@example.com"}'

Each verification is one call at $0.01225 (Verified 2026-10-16). The result carries a status, a score and the reasons behind them as separate booleans, covered in the next section.

Step 3. Write the fall-through

This is the part you were paying a platform for:

RUNGS = [
    ("hunterio", "/email-finder"),
    ("pdl", "/v5/person/enrich"),
]

def find_email(person):
    for provider, endpoint in RUNGS:
        hit = monid_run(provider, endpoint, person)
        if hit.get("email"):
            return hit
    return None

The first answer wins, and the later rungs never run for records that resolved early. Add a rung by appending a tuple. For a list, wrap the function in a loop over your rows, then hand the whole job to an agent:

If you are choosing between buying a dataset and calling an API for this, the B2B data provider comparison lays out the fork, and which LinkedIn scraper returns emails shows a verify-each-rung ladder on a different source.

Can you build the waterfall yourself with Python?

Yes, and the loop itself is the easy part. The twenty lines above are all the sequencing there is. For one provider and a few hundred rows a script with requests is an afternoon.

What takes the time is the vendors underneath. Each one is a signup, a contract or plan, an API key, a billing model and its own error format. You normalise every response into the same shape, decide what counts as a miss for each, handle rate limits and timeouts, and re-do the work when a vendor changes a field. Open source workflow runners cover the scheduling and retries half, and you still bring the vendors.

The Monid route removes the vendor half. One key calls the finder, the verifier and People Data Labs, each priced per call and inspectable for free before it bills, so the code you write is the loop and not the plumbing.

What does the enrichment data look like, and what can you build?

The finder returns one flat record, and the verifier returns the checks behind a verdict. Both shapes below are what came back on 2026-10-16.

The finder response

{ "first_name": "Patrick", "last_name": "Collison",
  "email": "collison@stripe.com", "score": 80,
  "domain": "stripe.com", "accept_all": true,
  "position": null, "twitter": null, "linkedin_url": null, "phone_number": null,
  "company": "Stripe", "source_type": "generated", "sources": [],
  "verification": { "date": "2026-10-17", "status": "valid" } }

For a name and a domain, the finder returned the address, a score of 80, the company name and its own verification status. Position, social handles and phone came back null, and sources was empty.

The verifier response

{ "status": "valid", "score": 90, "email": "collison@stripe.com",
  "regexp": true, "gibberish": false, "disposable": false, "webmail": false,
  "mx_records": true, "smtp_server": true, "smtp_check": true,
  "accept_all": false, "block": false, "sources": [],
  "result": "deliverable",
  "_deprecation_notice": "Using result is deprecated, use status instead" }

The verdict arrives with the reasons as separate booleans. mx_records says the domain can receive mail, smtp_check says this mailbox answered, and accept_all says whether the server accepts everything. The run answered RUNNING first and completed after one poll, about two seconds later.

What you can build with it

• A prospect list with verified emails. Names and companies in, a CSV with address, score and provider out. Verify before you send, as in the email verification API comparison.
• A cheaper-first ladder. Put the lowest-priced rung first and the dearest last, so the dear one only sees records the cheap one missed. The finder at $0.0245 per hit, then People Data Labs enrich at $0.28 per call (Verified 2026-10-16), is that shape.
• An account map. Once you have a domain, hunterio/domain-search lists the addresses published on it, and the company side comes from pdl/v5/company/enrich. How the two Hunter endpoints split the job is in domain search versus email finder.

What goes wrong when you run a waterfall at scale?

Four things show up in the output once you read more than one record. The first three are from our 2026-10-16 runs.

Why is a "valid" from the finder not proof?

Because the finder's own check can disagree with the verifier. For the same address, the finder reported accept_all: true with source_type: "generated" and an empty sources array: no public page behind it. The separate verifier reported accept_all: false with smtp_check: true. Treat the finder's verification field as a first pass and run the verifier on anything you will send to. The second call costs $0.01225 (Verified 2026-10-16).

Why does a miss look different from a failure?

Because it comes back as a normal, successful run. The invented name returned a complete record with email: null and every other field null, billedUnits: 0, and the call took about eleven seconds on the wall clock, much longer than the two seconds of the hit. Your loop must test for the null email, not for an error, and your timeout must allow for slow misses. The max_duration input, between 3 and 20 seconds, trades that wait for accuracy.

Why do two endpoints that read alike bill so differently?

Because enrich bills per call and search bills per record. pdl/v5/person/enrich is $0.28 per call, and pdl/v5/person/search is $0.28 per record retrieved, with up to 100 records in one request (Verified 2026-10-16). A waterfall built on search endpoints can bill a hundred records for what you meant as one lookup. Use enrich when you know who you mean.

Which complaint do you actually have about data quality?

Three different ones get called "bad data". Coverage means you looked up a hundred people and got sixty back, and a second provider fixes it. Accuracy means the addresses came back and some bounce, and stacking more providers does not fix it, since a verification step does. Freshness means the person changed jobs, and only re-running on a schedule helps. Sorting your complaint saves more money than switching vendors, and the Apollo take on the same finder-and-verify split is in Apollo's email finder API.

Which endpoint should I use for which job?

Prices Verified 2026-10-16 with monid inspect. The first two rows are the ones to start a waterfall with, and the finder and verifier together cost $0.03675 for a found and checked address. The People Data Labs rows are priced higher per call, which is why they sit behind the cheaper rung. For the company side, see the company enrichment tools on the same key and balance, and the full tools catalog for current prices.

When is another route a better fit?

Nobody on the team writes code. Clay's table is built for people who work in spreadsheets, and the twenty lines above are twenty lines somebody has to own, deploy and fix. If a person who works in a sheet runs enrichment, buy the sheet.

You want one contract and a compliance answer. A single-source platform such as ZoomInfo or Cognism gives you one support line and one document for procurement. Per-call access does not.

And the disclosure: we resell these endpoints. The most useful thing in this post is the free miss and the separate verifier, which hold whoever you buy the data from.

Conclusion

The direct answer: there is no single best Clay alternative, because the ranked lists compare Clay with data vendors and Clay is an orchestration layer with a table on top. If you need the table, no API replaces it. If you need the orchestration, the fall-through is a loop through Monid: $0.0245 per found address and $0.01225 per verification (Verified 2026-10-16), one key, about a minute to set up, ready inside your agent.

Two things matter more than the choice. Read the billing note on every rung before you design the order, because a waterfall only helps when a miss is free, and the finder's is. And verify with a separate call, because the finder and the verifier disagreed about the same address in our run.

How we estimated the time saved: wiring two vendors yourself is roughly 1 to 3 hours each for the account, key and billing setup, so 2 to 6 hours. The loop, response normalising and retries take another 3 to 6, and the first month of upkeep 1 to 2. That is 6 to 14 hours. The 1 minute is the install, key and first call once you already have a Monid key.

Free next step: run monid discover -q "find a work email address for a person", then monid inspect -p hunterio -e /email-finder, and make one lookup on a person whose address you know.

FAQ

Published August 2026.