Adapt.io vs Apollo.io (2026)
The decision is what happens to the contacts you bring with you, because both vendors run the same model and only one gives you a way out of it. Adapt.io states that most of its directory comes from its own members, so the contact data a customer contributes becomes inventory served back to everyone on the platform including that customer's competitors, and no opt out or contractual exclusion from contribution is documented anywhere. Apollo runs a contributor network of more than two million people, names the two product features that do the extracting so a buyer can see exactly which surface turns their mailbox into shared inventory, describes the network as opt in, and publishes a self service route for any individual to claim or remove their own profile. Both companies are more honest about this than the category norm, which is to say nothing at all. The hard edge sits at both: the people whose details are extracted from a customer's connected mailbox never agreed to anything, the customer did.
- The whole purchase path has to fit a small team's budget. Paid tiers start around forty nine dollars a month with a permanent free tier beneath them, seats are unlimited rather than metered, and the daily contact view caps that govern real throughput are published rather than discovered later.
- You want notice on entry rather than a rights process. Adapt.io states that it notifies individuals by email the first time their business contact information is added to the directory and gives them an opportunity to opt out at that moment, which is proactive rather than reactive.
- The data tool should not send. Adapt.io's core platform carries no dialer and no automation of its own, so the sending reputation problem stays with whatever tool you already use rather than arriving inside the data subscription.
- You want the compliance obligation discharged at the data layer. Apollo screens its database against multiple do not call registries in product, so the duty is met before a number reaches a dialer rather than being left to the buyer to remember, alongside broker registration in four named states.
- Scale and reach have to be there on day one. A very large contact database with more than sixty five search filters, website visitor identification, buyer intent signals, a parallel and international dialer and multichannel sequencing arrive in one platform, with a free tier real enough to test them on.
- Inferred data should be named as inferred. The processing notice enumerates the categories held and discloses that Apollo makes inferences about those contacts, including their likelihood of interest in a customer's product, which is the category most brokers leave unmentioned entirely.
Plain facts
| Adapt.io | Apollo.io | |
|---|---|---|
| Primary category | Data & Enrichment | Data & Enrichment |
| Founded | Not published | Not published |
| Headquarters | Not published | Not published |
| Website | www.adapt.io | www.apollo.io |
Side by Side
| Axis | A Adapt.io |
A Apollo.io |
|---|---|---|
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AI Capability
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| AI Centrality | ||
| Autonomy and Oversight Model | ||
| AI Disclosure and Model Transparency | ||
| Operational and Outcome Evidence | ||
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Compliance and Risk
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| Outreach Compliance Posture | ||
| Data Privacy Posture | ||
| Data Licensing and Provenance | ||
| Platform Terms Exposure | ||
| AI Safety and Data Stewardship | ||
| Recipient Disclosure and Authenticity | ||
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Integration and Deployment
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| Ecosystem and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Security Certifications and Trust Center | ||
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Commercial and Operational
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| Commercial Transparency | ||
| Exit and Data Portability | ||
| Deliverability and Sending Discipline | ||
| Segment and Market Coverage | ||
The short version of each
Adapt.io
Adapt.io is a business contact and company database sold at the budget end of the data tier, built around a filtered web application for prospecting and list building plus a browser extension that returns verified emails and direct dials while a user views a profile. The GTM Tech Index grades it B on data licensing and provenance because provenance is described in classes rather than left blank, which is better than most of the budget tier: the published account is that most directory information comes from Adapt.io members, that individuals may add their own details, and that the directory is supplemented with publicly available information and records from providers the company describes as legally authorised to supply them.
Source: GTM Tech Index, 2026
Apollo.io
Apollo.io is the default all in one prospecting and engagement platform for small and mid market buyers, combining a very large business contact database with search filters, multichannel sequencing, a parallel and international dialer, website visitor identification and buyer intent signals, sold product led with a usable permanent free tier. The GTM Tech Index grades it A on data licensing and provenance, the first on that axis in the index: three sourcing routes are named rather than behind multiple sources, the contributor network is described as opt in with the specific extracting product features named, profile removal is self service, and the notice obligation is discharged in a published artefact rather than promised.
Source: GTM Tech Index, 2026
Common questions
Is Adapt.io better than Apollo.io?
What happens to the contacts you bring with you, because both run the same contributory model and only one gives you a way out of it. Adapt.io states that most of its directory comes from its own members and documents no opt out or contractual exclusion from contribution. Apollo runs a contributor network of more than two million people, names the two product features that do the extracting, describes the network as opt in, and publishes a self service route for any individual to claim or remove their own profile.
Does my contact list become their product?
Both take contributed contacts and Apollo publishes more machinery around it. Adapt.io's directory is described as drawing mostly from its own members, so a contributed list becomes inventory served back to everyone including competitors, disclosed plainly with no opt out documented. Apollo names its contributor network at more than two million people, names the extracting features so a buyer can see which surface does it, describes participation as opt in, and gives individuals a self service removal route. The hard edge sits at both: the people whose details are extracted never agreed, the customer did.
How much do Adapt.io and Apollo.io cost?
Both publish and Apollo publishes more of the ladder. Adapt.io lists plan names, monthly prices, credit allowances, a permanent free tier, unlimited seats and daily contact view caps, which the index grades A. Apollo publishes five tiers with real numbers and real units from a genuinely usable free plan through per seat pricing at forty nine, seventy nine and a hundred and nineteen dollars a month annually, with credit allocations, sequence limits and feature gates per tier, which the index also grades A and treats as the benchmark.
Which one protects my sending domain?
Neither publishes sending discipline, and only one has published the consequence. Adapt.io's separate sequencer sends with nothing documented on warmup, volume governance or rotation. Apollo carries the first D on this axis in the index, and its own knowledge base explains why third party verifiers flag its verified emails as invalid and why customers see high bounce rates from connected mailboxes, with independent consensus putting those rates at fifteen to twenty five percent against a published ninety six percent accuracy figure.
Which has security documentation a reviewer can use?
Apollo, by a wide margin. It publishes a service organisation control type two and an information security certification with the auditing firm named, a tier two cloud application security assessment for restricted mail scopes, and a trust centre carrying downloadable documents including a penetration test report. Adapt.io commits in its privacy policy to reasonable security controls against loss, misuse and unauthorised access, with no trust centre, enumerated certification, audit report or penetration test attestation located.
How does the GTM Tech Index grade Adapt.io and Apollo.io?
Both are graded on the same seventeen capability and compliance axes from public sources, at documented depths of seventeen and sixteen. Both take A on commercial transparency. The GTM Tech Index grades Apollo.io A on outreach compliance posture, data privacy posture and data licensing and provenance, and B on operational evidence, platform terms exposure, ecosystem depth, residency and security certifications, with a D on deliverability discipline. Adapt.io takes B on autonomy and oversight, data privacy, data licensing, AI safety, recipient disclosure, ecosystem depth and segment coverage. The index publishes no composite score and declares no winner.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Sales Engagement & Outreach page.
Both companies sell the records and a way to send to them, and neither publishes what governs the sending. At Adapt.io the separate sequencer sends on a customer's behalf and nothing documents warmup, volume governance, rotation or what happens when reputation degrades, while the vendor markets verification as a deliverability benefit with no measured bounce rate and no verification methodology behind it. At Apollo the same absence is documented by its own consequence.
The vendor publishes no warmup, no inbox placement testing, no domain health monitoring, no rotation policy and no bounce or complaint threshold, on a platform built for high volume sequencing from the customer's own connected mailbox, and its own knowledge base carries entries explaining why third party verification vendors flag its verified emails as invalid and why customers see high bounce rates from mailboxes connected to it.
Independent review consensus across three platforms puts those bounce rates at fifteen to twenty five percent against a published accuracy figure of ninety six percent. Documenting your own most common quality complaint in your own help centre is disclosure almost nobody here offers, and it is credited on the evidence axis rather than this one. A buyer taking either product is spending their own domain reputation, and only one of the two has told them what that looks like in practice.
The second shared gap is the model layer, which matters less for a data product and is worth one line: neither names a provider, family or version for anything, and at Apollo that extends to the assistant that executes outbound workflows from natural language instruction.