AI Prospecting Tools

AI prospecting tools are software that uses language models to run the research half of outbound sales: identifying accounts that match an ideal customer profile, finding the decision makers inside them, filling in verified work emails and phone numbers, and drafting a first message. Google's own AI Overview for the term, measured on 2026-09-07, defines them as tools that "automate lead research, find contact data across multiple sources, and write personalized outreach at scale".

Three different jobs hide under that one label, and buyers who treat them as one job end up paying twice for the same capability. Research is an AI column or agent that reads a company's public footprint and writes back an answer. Data is a waterfall that queries many providers for a verified email or a phone number. Outreach is the sequencing and sending layer.

Cleanlist: best for teams whose reps use data unevenly, because every seat's credits go into one shared balance. It runs waterfall enrichment across 25+ providers and charges 1 credit per verified work email and 10 per phone number, starting at $49 per seat a month.

Cleanlist does the research and data jobs, and its Sequences send email from your own inbox, with call tasks, at 0 credits on every paid plan. Finished lists can also go into Lemlist campaigns or Salesloft cadences, or sync to HubSpot and Salesforce.

On 2026-09-07 the AI Overview for "ai prospecting tools" named three vendors, and Cleanlist AI was not one of them. The pull ran through the DataForSEO SERP API against Google US desktop, location code 2840, depth 50, with the asynchronous AI Overview body loaded. In the order Google printed them: Clay, "best for custom workflows and GTM engineers, combining over 100 data sources, AI research columns, and waterfall enrichment"; Apollo.io, "best budget pick with a 275M+ contact database, AI-assisted outreach, and built-in email sequencing"; and SyncGTM, "best overall for combining AI research agents, waterfall enrichment, and CRM synchronization starting at $99/month". Those numbers are Google's, quoted as evidence of what the answer says. None of them was verified against the vendor's own page for this article.

Three more measurements from the same pull. Three of the seven sources the answer cited were YouTube videos. The highest organic result for the term was a Reddit thread, with Salesforce at 2, a ZoomInfo blog at 3 and Clay at 4. And Cleanlist AI held no position in the top 50 organic results for "ai prospecting tools" or for "ai sdr tools" on that date.

An AI prospecting tool finds and enriches the people. An AI SDR tool also contacts them: it writes and sends the outreach, answers replies and books the meeting. AiSDR, Artisan's Ava and Salesforge's Agent Frank run that sending half, and the AI SDR tools comparison prices 14 of them, read on each vendor's own page on October 16, 2026. For the same tools sorted by BDR job, see the AI BDR guide.

Cleanlist AI sits on the list side, with Sequences for sending. Its agents find new people who match the ICP every week, verify their emails across 25+ providers and add them to a sequence that sends from the rep's own Gmail or Outlook inbox. The rep writes each email once, with variables for every lead, and takes the calls; Sequences has call tasks and no dialer. On the 500-Lead Enrichment Benchmark (500 stratified B2B leads), Cleanlist AI returned 98% verified work emails and 85% phone numbers.

Yes, in three specific places, and only one of the three produces a field you can filter a search on. The first is normalization: turning "VP Sales" and "Vice President, Sales" into one canonical title so a segment does not fracture across spellings. The second is probabilistic matching: building a confidence score across several weak signals (name, company, title) instead of demanding an exact domain match. The third is open-ended research: an agent reads a company's public footprint at the moment you ask and writes back an answer to a question nobody has a column for.

Google's AI Overview for "ai data enrichment" on 2026-09-07 lists normalization and probabilistic matching among four mechanism bullets, alongside waterfall routing and continuous verification, and cites cleanlist.ai on all four.

Where AI does not help: it cannot manufacture a verified email that no provider holds. Deliverability still comes from SMTP verification, and coverage still comes from how many providers you ask.

On Cleanlist AI an AI qualification costs 5 credits per person and writes the agent's reasoning next to its answer, and a row the agent cannot answer is still charged. That output is research rather than a structured field: Cleanlist AI ships no technographic filter and no intent data.

You connect the client to a data platform through MCP, because the model has no live access to contact data on its own. Google's AI Mode answered this question on 2026-09-07 by saying LLMs "cannot natively scrape private databases or live contact lists in standard chat windows" and pointing at three bridges: Model Context Protocol servers, CLI integrations, and automation connectors. It named Claude Code with a Clay CLI plugin and SyncGTM, and cited syncgtm.com plus three YouTube videos.

The Cleanlist AI path, concretely. In Claude, open Settings, then Connectors, add a custom connector, paste mcp.cleanlist.ai, and authorize with OAuth. There is no API key to paste and nothing to install locally. Then ask in plain language.

The server exposes 30+ tools. enrich_person costs 1 credit for a work email, 10 for a phone number, 11 for both. Every paid call goes through estimate_cost first, which returns an HMAC-signed quote_id with a five-minute TTL, and the server refuses the job if the real cost would exceed the quote.

MCP is included from Starter, at $49 per seat a month. The beta runs on self-serve accounts and excludes AppSumo licenses.

It depends on where your sales data lives, and on 2026-09-07 Google's AI Mode named four servers of which only one is aimed at sourcing net-new contacts. Dynamics 365 Sales MCP Server for the Microsoft stack, Salesforce DX MCP Server for SOQL and metadata work, Shopify MCP for transactional retail data, and Vibe Prospecting MCP for outbound lead generation. Three of the four sit in front of a system you already own, so they read your pipeline rather than build it.

For sourcing, the server has to sit in front of an enrichment waterfall. Cleanlist AI runs one at mcp.cleanlist.ai. It is not the only one: read on 2026-09-01, LeadIQ lists MCP integration on its Pro plan (from $15 a month annual at the slider default of 2,400 credits a year, 5 users) and Ocean.io lists API and MCP access on its subscription (from $47.25 a month annual, minimum 9,000 credits, unlimited seats).

Three questions separate them. Does search cost credits (Ocean.io publishes 0.2 credits per search result; Cleanlist AI charges 0). Is there a spend cap the agent cannot exceed. Does a miss get billed. Cleanlist AI rate limits are 60 requests per minute per organization, 30 per minute per key, and 60 People Searches per UTC day per key.

The one whose fill rate holds up on your own list, which no listicle and no AI Overview can tell you. What they can tell you is who Google currently believes. Measured 2026-09-07 on "ai data enrichment" (40 US searches a month, $27.79 CPC): Clay's glossary page held organic position 1, Cleanlist AI's own tested post held 8, and the AI Overview cited cleanlist.ai on the definition line and on all four of its mechanism bullets while naming Clay in prose and Cleanlist AI nowhere in the answer text.

That gap is the whole reason to run your own test rather than read a ranking. The method that settles it: take 200 to 500 accounts you already know, run them through each candidate, measure per-field fill (what percentage came back with an email, with a direct dial, with a title), then hand-check a sample, because a match is not an accuracy.

Cleanlist's published figure from exactly that method is the 500-Lead Enrichment Benchmark: 500 stratified B2B leads, 98% verified work emails, 85% phone numbers. A new Cleanlist AI workspace runs 14 days on Pro with 250 credits, 3 seats and every Pro feature, which covers a 200-record fill test with credits left over.

Sort them by which of four jobs they do, because the tools that look alike on a landing page meter completely differently underneath. Prices below are entry plans read from each vendor's own pricing page on 2026-09-01 and recorded in public/data/b2b-data-pricing-index-2026-09.csv.

Research and workflow: Clay's Launch plan is $185 a month, $167 annual, and runs two separate meters, 180,000 Actions and 30,000 Data Credits a year, with top-up credits sold at a 30% premium.

Database plus sequencing in one: Apollo's Basic plan is $65 a month, $49 annual, granting 30,000 credits per seat per year up front at 1 credit per email and 8 per phone number.

Sending infrastructure: Instantly's Growth credits plan is $47 a month for 1,500 credits, though the page publishes no credits-per-email conversion.

Enterprise assisted outbound: Amplemarket's Startup plan is $600 a month, annual term only, 2 users, 13,500 email credits per user per year.

Data first, sending included: Cleanlist AI Starter is $49 per seat a month, and each seat adds 750 credits to one shared balance. Verified email 1 credit, phone number 10, both 11, company 1, validation 0.5, AI qualification 5, sending 0, search 0, a miss 0.

Every major vendor runs a free tier, and all of them are sized for evaluation rather than for outbound. Read from each vendor's own pricing page on 2026-09-01: Apollo's free plan gives 75 credits per seat per month (900 per seat per year); Clay's free plan gives 6,000 actions and 1,200 data credits a year; LeadIQ's free plan gives 1 user and 50 credits; Persana's gives 50 credits; Snov.io's Trial plan gives 50 credits that renew every 30 days rather than expiring; RocketReach's free account gives 5 lookups; UpLead runs a 7-day trial with 5 credits.

Cleanlist's Free plan is 50 credits a month for up to 3 seats. A new workspace gets 14 days of Pro first (3 seats, 250 credits, every Pro feature) before landing there.

The thing worth doing with any of them is a fill-rate test on 200 records you can verify by hand. The thing not worth doing is running a campaign, because at these volumes you will burn the allowance before you learn anything.

One capability that stays free on Cleanlist AI at every tier including Free: People Search and Company Search cost 0 credits, with no query cap and no export meter, so sizing a segment never costs anything.

The eight platforms below span $39 to $600 a month on their entry plans, and 6 of the 37 vendors in our price index publish no purchasable dollar figure at all. Every number here comes from that vendor's own pricing page, read on 2026-09-01, recorded with its source URL in public/data/b2b-data-pricing-index-2026-09.csv.

Snov.io Starter $39. Instantly Growth credits $47. Cleanlist AI Starter $49. Apollo Basic $65. Persana Starter $85. UpLead Essentials $99. Clay Launch $185. Amplemarket Startup $600, annual term only.

The six that publish nothing: ZoomInfo, Cognism, Seamless.AI, Outreach, Salesloft and NeverBounce. ZoomInfo's pricing page returned HTTP 403 to curl with a Chrome user agent and a press-and-hold human challenge in headless Chromium on the date it was read.

Sticker price is a weak signal on its own because the meters differ. Clay runs two meters that are selected and priced separately. Apollo grants credits per seat per year, so cost scales with headcount. Cleanlist AI also prices per seat, and every seat adds its credits to one shared team wallet. Annual discounts, measured off the same pages: Apollo 24.6%, Clay 9.7%, Cleanlist AI 25.6%.

Between about half a cent and 58 cents per verified work email on published entry plans, which is a much narrower band than the figures circulating in public answers. Google's AI Mode answered this question on 2026-09-07 with $0.05 to $1.20 per contact, or $300 to $1,000+ per thousand, citing salesmotion.io, instantly.ai and bookyourdata.com.

Computed from vendor pricing pages instead, read 2026-09-01: across the 22 vendors in our index whose monthly entry plan normalizes to a rate, 1,000 verified work emails on the entry plan ranged from $6.50 to $582.35. Apollo works out to $26.00, Persana $42.50, Cleanlist AI $65.33, Surfe $326.67, UpLead $582.35.

That 89x spread is a meter difference rather than a quality difference. Surfe's Essential plan gives 150 email credits a month for $49. UpLead's Essentials gives 170 credits for $99, with one credit bundling email and mobile together. Apollo grants 30,000 credits per seat per year.

Three questions decide your real rate, and none of them appear on a pricing headline. Does search cost credits. Does a miss cost credits. Do credits pool across the team or sit per seat. On Cleanlist AI the answers are 0, 0 and pooled.

Nobody can answer that for your list, and the answers currently circulating are labeled estimates by the people publishing them. Measured 2026-09-07, Google's AI Mode returned a table headed "Estimated Email Match/Accuracy Rate" putting ZoomInfo at 84 to 95%, Amplemarket at 95%+ and Apollo.io at 78 to 85%, and wrote that modern stacks cascade providers to "artificially achieve a combined match rate approaching 95%+". Its four sources were cotera.co, enrich.so, bytemine.ai and amplemarket.com, every one of them a vendor or a comparison site with a stake in the ranking.

Match rate and accuracy are two separate measurements, and conflating them is where evaluations go wrong. A provider can match 90% of your rows and be wrong on 15% of the matches, which is 76.5% real accuracy against a 90% headline.

The number worth trusting is one you produced. Cleanlist AI publishes its own: the 500-Lead Enrichment Benchmark returned 98% verified work emails and 85% phone numbers across 500 stratified B2B leads. Run the same shape of test yourself on 200 to 500 records, because coverage varies more by industry, geography and seniority mix than it varies by vendor.

Upload the file, map the columns, choose which fields to append, run it, and download the result. Google's AI Mode gave that same six-step sequence on 2026-09-07 and named Apollo, SalesQL and BetterContact as places to do it.

The inputs decide the match rate more than the vendor does. Full name plus company domain beats full name plus company name, and a LinkedIn URL beats both. Clean before you spend: standardize company names, deduplicate, and drop junk rows, because a garbage row consumes an attempt even when it never had a chance of matching.

On Cleanlist AI the CSV importer lives in the app rather than on the MCP server. The file is billed per field returned: 1 credit for a verified work email, 10 for a phone number, 11 for both on the same row, 0.5 for a validation, 1 for a company record, and 0 for a row that comes back empty.

One Starter seat's 750 credits cover 750 rows with email only, and fewer once phone numbers are added.

It depends on the input you are starting from, which is exactly how Google's AI Mode answered it on 2026-09-07: rather than ranking tools, it sorted five named ones into three input methods. Name plus company domain, which is a domain-search lookup. Browsing a LinkedIn profile, which is a Chrome extension job. And high-volume enterprise search, where it put ZoomInfo. UpLead and Apollo.io were among the other names it returned.

Cleanlist covers the same three inputs on three surfaces. The Chrome extension, rated 4.7 from 13 ratings, captures the person on the page you are looking at. People Search finds them by structured filters (seniority, department, management level, job function, title, location), and you spend 1 credit only on the row you keep. The MCP server does the same two things from inside Claude in plain language.

One cost note that applies to every credit model. A single lookup is the worst value in any of them, because plans are sized for batches: a Starter seat's 750 credits at $49 is $0.065 per verified work email, and one email on the same seat costs $49.

The one that lets you size and re-cut the segment before you enrich, and charges for an email or phone number only when one comes back. Google's AI Mode grouped its 2026-09-07 answer into all-in-one databases, scaled outbound platforms with built-in lead data, and Chrome extensions, naming Apollo.io, UpLead, Cognism, Instantly.ai and Listkit among others. It closed with one rule that outlasts any ranking: never send raw data straight to your sender, always run a verification pass, and keep bounce under 2%.

What that rule implies about tooling is that list building and list sending should be separately good. Cleanlist AI verifies the list before its Sequences or your own sender touch it. Company Search and People Search let you cut a market ten ways to find the segment that is real before you enrich a row, then pivot from a company result set straight into the people inside those domains.

Costs land only on the rows you keep: 1 credit a verified work email, 10 a phone number, nothing for a miss. Delivery goes out through Cleanlist AI Sequences, into Salesloft or Lemlist, or on Pro and Enterprise into HubSpot and Salesforce.

Narrow the segment until the first line writes itself, then buy data only for the rows that survive the narrowing. The order that produces that: derive the profile from your last fifty closed-won accounts rather than from a whiteboard, size the segment with a search, cut it into batches of a few hundred, enrich only those, validate, then hand the list to whatever does your sending. That is B2B list building in the right order, and once the segment holds, prospecting automation can rerun the same search every week and add only the people it has not delivered before.

The economics are what make the order matter. On Cleanlist AI, a lookup that returns nothing is never billed, so a tight segment with a low fill rate is not punished. One Starter seat at $49 a month brings 750 credits, which buys 750 verified work emails.

AI earns its place at the research step rather than the sending step. An AI qualification is 5 credits per person and returns the reasoning alongside the verdict, so a disagreement is auditable. Volume without a segment remains the most expensive way to run outbound, because every bad address is paid for twice, once in credits and once in sender reputation.

They cannot produce data that no provider holds, and no amount of model quality changes that. A language model can normalize a title, score a fit, and draft a message. It cannot confirm that an inbox exists. Coverage still comes from how many providers you ask, and deliverability still comes from SMTP verification.

What Cleanlist AI specifically does not ship, stated plainly because a page that only lists capabilities is a brochure:

No owned database and no database size to quote. Records resolve at request time across a pool of 25+ providers.

No intent data, no technographic dataset and no tech-stack filter, no job-change alerting, and no org charts or reporting lines.

No dialer. Sequences covers email steps plus call tasks, and the calls themselves stay outside the product.

No natural-language endpoint on the public REST API. The API at api.cleanlist.ai/api/v2 takes structured filters across roughly 30 endpoints with clapi_ bearer auth and 14 OAuth scopes, and it starts on Pro at $89 per seat a month. Natural language happens in Clu, the in-app GTM agent, and on the MCP server, which starts on Starter at $49 per seat.

No v2 webhooks, no published uptime SLA, and no SOC 2 Type II or ISO 27001 certification. If your security review makes either certification a hard requirement, that is a real reason to buy elsewhere.