Comparison
DiscoLike vs Apollo.io
Apollo is an all-in-one outreach platform built on a people graph. DiscoLike is a search engine built on a crawl of the business web. They solve different problems. Here is where each one actually wins.
TL;DR
Apollo bundles a contact database with sequencing, a dialer, and email engagement. For a small US team that wants find, email, and call in one $49–$119 per-seat tool, it is legitimately the simpler answer.
DiscoLike does one job at a much greater depth: finding companies. We crawl and index 80M+ business websites ourselves, so you can search by what a company actually says it does (natural language, lookalike, or exact phrase) instead of picking from industry dropdowns.
Many teams run both: Apollo for sequencing and contact workflows, DiscoLike to find the accounts Apollo's taxonomy can't surface.
At a Glance
DiscoLike and Apollo.io, side by side
 | Apollo.io | |
|---|---|---|
| Data source | Our own crawl and index of 80M+ business websites, 1B company pages | People-graph assembled from public profiles, licensed datasets, and user-contributed inbox data |
| Company discovery | Natural language ICP search, domain lookalike, and exact phrase matching on homepage text | 65+ filters plus an AI assistant that translates plain English into the same filter taxonomy |
| Niche verticals | Findable by what the website says. No category needs to exist first | Companies that don't map to an industry or title field are effectively unfindable |
| International coverage | 98% of companies worldwide, crawled in 50 languages | Strong in the US; reviewers report accuracy dropping significantly outside North America |
| Outreach execution | None. We integrate with your sequencer, Clay, or CRM | Sequences, dialer, and email engagement built in, a genuine strength |
| Pricing | $99–$1,599/mo flat, self-serve, monthly or annual (20% off) | $49–$119 per user/mo billed annually; 30K–72K credits per seat per year |
| Contact pricing | Billed per contact record: email and phone included when found, no separate phone premium. ContaGen agent fills gaps from the open web | 1 credit per email, 8 credits per phone number |
| For AI agents | MCP server and REST API on every plan, over our own index | Official MCP server on all plans. The difference is the data underneath, not the plumbing |
Apollo.io details verified August 12, 2026 from public pricing pages, documentation, and independent reviews. Spotted something outdated? and we'll fix it.
Where the data comes from
Apollo's database is a people graph: hundreds of millions of contact records assembled from public profiles, licensed third-party datasets, and a contributory network that refreshes records from users' connected inboxes. It's built to answer "who works where, and what's their email?"
DiscoLike is built the other way around. We crawl the business web ourselves (80M+ company websites, 1B pages) and train custom LLMs on that text. Our index knows what a company actually does because we read its website, not because someone typed a category into a profile years ago.
That difference decides which companies you can find at all. If a company's defining trait isn't a field in Apollo's schema (a niche manufacturing process, a regulatory specialty, a technology mentioned only on their site), no amount of filtering will surface it. In DiscoLike you search for the phrase itself.
Apollo tells you about people at companies it categorizes. DiscoLike finds companies by what they say about themselves.
Search: natural language vs. natural language
Apollo shipped an AI assistant in 2026 that accepts plain-English ICP descriptions, a real improvement. But it works by translating your sentence into the same industry, title, and headcount filters underneath. The taxonomy is still the ceiling.
DiscoLike's natural language search runs against website text and firmographic profiles from the full index. Describe your ICP in a sentence, seed a lookalike search with four or five best-customer domains, or require an exact phrase to appear on the homepage. All three run against what companies actually publish, and you can combine them in one query.
Both tools take plain English. Only one of them searches beyond a fixed taxonomy.
Coverage where it gets hard
Apollo is genuinely strong on US SMB and mid-market contact data. Reviewers consistently report the drop-off outside North America and in niche verticals. Independent tests have measured real-world accuracy well below the marketed figure, with bounce rates that make list scrubbing a required step.
DiscoLike covers 98% of companies worldwide because a crawler doesn't care what country a website is in. We index in 50 languages, validate domains by SSL certificate, and exclude parked, dead, and obsolete records. Teams working EMEA, APAC, or obscure verticals typically find this is where the gap is widest. ColdIQ found 49,203 companies and 15,000+ new contacts that their existing stack missed.
If your market is US software companies with clean job titles, Apollo covers it. If it's anything harder, coverage is the reason to look at DiscoLike.
Pricing and contracts
Both products are self-serve with published pricing, rare enough in this category to note. Apollo runs $49–$119 per user per month billed annually (Organization requires three seats), with 30,000–72,000 credits per seat per year and phone numbers priced at 8 credits against 1 per email. Its Trustpilot reviews skew heavily toward billing and cancellation complaints, so read the renewal terms before you commit a card.
DiscoLike is flat-priced per workspace, $99–$1,599/mo across five plans, monthly or annual with 20% off annual. Your full subscription converts to search credits, records you've already retrieved are cached free for 90 days, and you can cancel monthly plans anytime. See pricing for the full breakdown.
For AI agents: same protocol, different substrate
Apollo has a mature, well-documented MCP server. If you're building agents, it works. So does ours. The honest comparison isn't whether an agent can connect; it's what the agent gets back.
An agent querying DiscoLike searches an index of what 80M+ companies publish about themselves, with natural language and exact-phrase queries as first-class operations. An agent querying Apollo gets the same taxonomy-shaped records a human gets. Pick based on which data substrate your agent's task needs. For company discovery, that's the crawl.
Fit
Which one is right for you?
Choose DiscoLike if
- Your TAM includes companies Apollo's filters can't describe: niche verticals, regulated specialties, non-US markets
- You want to search by what a company's website says, including exact phrases
- You build lists from lookalikes of your best customers
- You need one flat workspace price instead of per-seat billing
- You're building AI agents that need a searchable index of the business web
Choose Apollo.io if
- You want prospecting, sequencing, and dialing in one tool
- Your ICP is well-described by standard industry and title filters, mostly in the US
- You need named contacts with emails and mobiles at known companies
- You're a 1–20-person team optimizing for per-seat cost
FAQ
Common questions
Is DiscoLike a replacement for Apollo?
For company discovery, yes: DiscoLike finds companies Apollo's taxonomy can't surface. For outreach execution, no: DiscoLike doesn't do sequencing or dialing. Many teams keep Apollo (or another sequencer) for engagement and use DiscoLike to feed it better accounts.
How is DiscoLike's data different from Apollo's?
Apollo assembles people-graph records from public profiles, licensed datasets, and user-contributed inbox data. DiscoLike crawls 80M+ business websites directly and trains custom LLMs on that text, so companies are searchable by what they actually publish, not by self-reported categories.
Does DiscoLike have contact data like Apollo?
Yes. Contact search with SMTP-validated emails, phone, LinkedIn, seniority, and department filters is on every plan, billed per contact record with email and phone included when found. When the directory doesn't have someone, ContaGen (our contact discovery agent) runs a live web search per company and verifies every email before you see it, free on any plan with your own model and search keys. Apollo's contact database is larger; DiscoLike's advantage is finding the companies first, including ones Apollo doesn't index.
Can I use both DiscoLike and Apollo together?
Yes, and it's common. Export discovered companies from DiscoLike via CSV, API, or Clay, then run enrichment and sequencing in Apollo. DiscoLike fills the top of the funnel with accounts other tools miss.
Researching the wider market? Read best Apollo.io alternatives.
More comparisons
Testimonials
Hear it from our users
Dan Rosenthal
Co-Founder, Workflows.io
"Discolike helped me map out 2M+ companies for over 15 different B2B companies, including a unicorn. I've used all the big prospecting databases, and I can confidently say Discolike is the best tool for building target account lists."
Alex Fine
Co-Founder, Understory
"We've gone from struggling to find alternative lists outside traditional databases to basically having an untapped source of highly relevant companies. The way that Discolike operates on the back-end has been night and day vs their competitors."
Jordan Crawford
Founder, Blueprint
"DiscoLike has unprecedented coverage of companies on the Internet. Their core technology has been instrumental in some of my sneakiest campaigns."
Felix Frank
Founder, StackOptimise
"DiscoLike's segmentation is a powerful tool. It splits the client list into clearly labeled groups we can easily work with, saving us hours on ideal company profile identification."
Panos Sisamos
Co-Founder, Relevance.
"DiscoLike is right next to Clay in my tech-stack. Took me a couple of hours to get the hang of it, but now I can't live without it. Our process at Relevance relies heavily on accurate TAM mapping, and no one does it better than DiscoLike"
Patrick William Joyce
CEO, Outboundless
"DiscoLike's GTM toolbox is awesome for our daily grind, matching account names to domains like a breeze, segmenting our client list into spot-on company profiles, and modeling target accounts for each one to keep our B2B pipeline humming!"
Raouf Lemouchi
Founder, SalesTech Scout
"DiscoLike has a strong lookalike domain search, their wizard makes it incredibly easy to find high-quality prospects that match our ideal customer profile. Being able to automatically segment my targets is a really good feature."
Alex Vacca
Co-Founder, Cold IQ
"DiscoLike has quickly become a must-have in our campaign workflow. It's incredibly good at uncovering look-alike prospects and companies"
Nick Abraham
Founder, Leadbird.io
"Discolike has streamlined our list building process by allowing our team to create larger more accurate lists in half the time compared to regular data tools"
Put a real search engine under your GTM
- 80M+ companies in our own index
- 1B company pages crawled
- Self-serve from $99/mo, no demo required
- Company data from public web sources