How to Use Nqzai With Clay for AI Lead Generation

How to Use Nqzai With Clay for AI Lead Generation

Nqzai and Clay both show up in "AI lead generation" searches, and they get lumped together often enough that it's worth being precise about what each one actually does before describing how to use them together. They are not competitors and there is no native connector between them today. What follows is grounded in nqzai's actual tool behavior and in Clay's own documentation — not in a hypothetical integration.

What nqzai does

Direct answer: Nqzai's lead workflow is chat-driven: you describe an audience in a sentence, and a conversational agent turns that into a structured search, then carries the resulting contacts through verification, drafting, and sending — all inside one conversation.

Finding people. The search_leads tool covers two search types: people (roles at companies) and local_business (brick-and-mortar businesses located by locality or postcode). You describe the audience — titles, industry, company location, company size, revenue band, specific company domains, even technologies the target company runs — and the agent translates that into structured filters rather than a single free-text query. It checks your own saved contacts and nqzai's own contact database first, at no extra cost, and only reaches into a paid outside data provider when you explicitly opt in — the tool will not silently spend on a paid source. When it does, the cost is billed in nqzai's own token currency, not disclosed by provider name. Free-tier accounts are capped at 10 leads per search regardless of the number requested.

Enriching contacts. enrich_contacts adds a company homepage summary and recent news to contacts you've already saved. It's explicitly scoped: it adds research, it does not tell you whether a list is any good. It's capped at 10 contacts per call and skips already-enriched contacts by default, so re-running it doesn't re-spend on people you've already researched unless you ask it to.

Checking deliverability. verify_contacts is nqzai's actual quality check for a list — it confirms whether saved email addresses are real and deliverable and stores the verdict per address, priced per address checked. This is the tool to reach for before a first send to a freshly-sourced list, not enrich_contacts — enrichment tells you nothing about whether an address will bounce.

Drafting and sending. generate_emails drafts cold outreach copy against a product brief you've set up (via scan_product), either as one common message with varied subject lines or a slower "personalized" mode that researches each contact individually before writing an opener. send_emails requires a separate, explicit confirmation message after previewing exactly what will go out — sends are treated as irreversible, so nqzai doesn't let a single instruction both draft and fire.

What's notably absent from nqzai's own tool set, based on the current code: there is no bulk CSV import or export specifically for contact lists, and no formal connector to any third-party enrichment or GTM platform, Clay included. Contact records live inside nqzai's own database and are worked with entirely through the chat interface and its dashboard views.

What Clay does

Direct answer: Clay (clay.com) describes itself as go-to-market infrastructure — a spreadsheet-like "tables" interface layered over data enrichment, AI research agents, and outbound orchestration, built for revenue teams rather than individual marketers.

Waterfall enrichment across a large provider marketplace. Clay's core mechanic is the "waterfall" — a single enrichment request cascades through Clay's data marketplace, described on its site as spanning more than 150 data providers, trying each in sequence until one returns a match. This is the piece that gives Clay unusually broad coverage for emails, phone numbers, firmographics and technographics compared with any single data source.

Claygent — AI research agents. Claygent is Clay's own term for AI agents that run row-by-row inside a table: you write a natural-language research prompt, the agent browses the web and reads documents to answer it, and the output populates a column for every row. Clay's documentation emphasizes a visible reasoning trace for each run rather than an opaque answer, and lists account research, meeting prep, lead qualification and personalized-outreach research as the primary use cases.

Signals, TAM sourcing, and CRM enrichment. Beyond one-off enrichment, Clay tracks intent signals such as job changes, keeps CRM records "accurate, complete, and continuously refreshed," and offers TAM-sourcing workflows for mapping a total addressable market and finding target accounts at scale — plus a native "Sequencer" for outbound messaging and syncs into ad platforms.

Pricing. Clay runs a two-currency credit system: "data credits" pay for the actual third-party data pulled through the marketplace (roughly $0.05 each, cheaper at volume, free when an enrichment finds nothing), and "actions" (under $0.01 each) meter Clay's own orchestration work — running a table, calling an AI model, syncing a system. Plans range from a Free tier (500 actions/100 data credits per month) through Launch and Growth to custom Enterprise pricing.

The combined workflow

Direct answer: There is no product integration between nqzai and Clay — no shared login, no button that pushes a list from one into the other. The realistic way to combine them is a manual, complementary workflow that plays to each tool's actual strength: nqzai for fast, chat-driven sourcing and the outbound "last mile," Clay for depth of enrichment and AI-agent research that nqzai doesn't attempt to replicate.

Step 1 — Source a first-pass list in nqzai. In chat, describe the audience: roles, industry, location, company size. search_leads checks your saved contacts and nqzai's own contact database first, at no extra token cost, before touching anything paid. This is the fastest, cheapest way to get an initial working list saved into a contact list inside nqzai.

Step 2 — Hand the identifying fields to Clay for deeper enrichment. Nqzai doesn't have a bulk export tool for contacts, so this step is manual: pull the names, companies and domains for the contacts you want to go deeper on from the nqzai dashboard, and add them as rows in a new Clay table. This is where Clay earns its keep — running its waterfall across its data marketplace for firmographic and technographic depth, and using Claygent to do the kind of open-ended web research (recent funding, org-chart guesses, specific pain-point signals) that goes well beyond what nqzai's own enrich_contacts (a homepage summary and recent news) is built to do.

Step 3 — Bring the results back into nqzai. There's no import tool either, so this is the second manual hop. The practical bridge is search_leads' company_domains field: if Clay's research surfaced a sharper set of target companies, feed those domains back into a fresh nqzai search so it resolves the right people at those companies through its own contact database and provider search. If you're working with contacts already saved in nqzai, the enrichment notes from Clay become raw material you paste into the instruction field when drafting.

Step 4 — Verify before you send. Run verify_contacts on the list before any first send — regardless of which tool sourced or enriched the contact, deliverability has to be checked in nqzai before nqzai sends anything, since that's the platform doing the sending.

Step 5 — Draft and send from nqzai. Use generate_emails in personalized mode, feeding in the specific angle from your own research (including anything pulled from Clay), then review and explicitly confirm before send_emails fires. Sending, tracking, and reply handling stay inside nqzai for the contacts nqzai owns.

Be honest with yourself about what this buys you: it's two separate tools bridged by copy-and-paste, not a pipeline. It's worth doing when you specifically need Clay's breadth of enrichment sources or Claygent's open-ended research on a subset of high-value accounts, and worth skipping — sticking to nqzai alone — for a straightforward "find, verify, draft, send" run where nqzai's own database and provider search are already sufficient.

Sources

• Clay.com — platform overview, data marketplace and waterfall enrichment, Signals/Intent, CRM enrichment, TAM sourcing, Sequencer.
• Clay.com — Claygent — how Claygent's row-by-row AI research agents work, reasoning trace, use cases.
• Clay.com — Pricing — plan tiers, the data-credit vs. action two-currency system.
• nqzai tool definitions (src/tools/openapi.ts, src/tools/registry.ts in the nqzai codebase) — search_leads, enrich_contacts, verify_contacts, generate_emails, send_emails behavior described above is drawn directly from these tool schemas.