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Apollo

Apollo covers company search, contact discovery, browser-based enrichment, and AI outreach drafting in one workflow, but contact freshness and personalization depth still need validation.

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Company + people searchChrome extensionAI email draftingSearch + enrichment API

Strong all-in-one workflow, mixed data reliability

Apollo met the core outreach workflow in testing: it found companies, surfaced employees, exposed some direct contact data, worked inside LinkedIn and company sites through its Chrome extension, offered APIs for automation, and generated usable outreach drafts. The tradeoff is data reliability and depth. Employee coverage was not fully fresh in validation, some contact records needed confidence checks, and the strongest email mode personalized mainly at the company level rather than deeply at the individual level.

Download video: Demo video
Hands-on Apollo workflow demo captured during testing.

In-Depth Review

Our detailed analysis of Apollo — features, performance, and real-world testing.

AV
Ajay V
AI Demos Team
Verified Review

Feature-by-Feature Breakdown

Company search by domain
Returned the right company for a known target.
▾
Test Summary
Feature tested: Company search by domain
Result: Passed — Returned the right company for a known target.

Feature tested: Company search by domain

Result: Passed

Verdict: Returned the right company for a known target.

Expected behavior: Tested whether Apollo could find a real company from the query "vespa.ai" and return a usable company record as the starting point for prospecting.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Search query

Observed output: Output artifact (Image): On Apollo's Find companies page, searching "vespa.ai" returned a matching company result. That gave a direct starting record for moving from company discovery i — apollo-apollo-find-companies-vespa-search.png

Input artifact: Input artifact (Text prompt): Search query

Output artifact: Output artifact (Image): On Apollo's Find companies page, searching "vespa.ai" returned a matching company result. That gave a direct starting record for moving from company discovery i — apollo-apollo-find-companies-vespa-search.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Apollo handled a known company/domain lookup cleanly.

Tested whether Apollo could find a real company from the query "vespa.ai" and return a usable company record as the starting point for prospecting.

INPUT
Search Apollo Find companies for: vespa.ai
↓
image
Output artifact for "Company search by domain" test: On Apollo's Find companies page, searching "vespa.ai" returned a matching company result. That gave a direct starting record for moving from company discovery i, apollo-apollo-find-companies-vespa-search.png

On Apollo's Find companies page, searching "vespa.ai" returned a matching company result. That gave a direct starting record for moving from company discovery into employee and contact research inside the same product.

Bottom Line
Apollo handled a known company/domain lookup cleanly.
Known-person lookup
Strong for locating named prospects.
▾
Test Summary
Feature tested: Known-person lookup
Result: Passed — Strong for locating named prospects.

Feature tested: Known-person lookup

Result: Passed

Verdict: Strong for locating named prospects.

Expected behavior: Tested people search with the known prospect "Tytus Golas" to see whether Apollo could surface the intended person and enough context to verify identity before outreach.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): People search

Observed output: Output artifact (Image): Apollo's Find people search returned Tytus Golas with role and email information, plus enough profile context to help confirm that the result was the intended c — apollo-apollo-find-people-tytus-golas.png

Input artifact: Input artifact (Text prompt): People search

Output artifact: Output artifact (Image): Apollo's Find people search returned Tytus Golas with role and email information, plus enough profile context to help confirm that the result was the intended c — apollo-apollo-find-people-tytus-golas.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Apollo is effective when you already know the person you want to reach.

Tested people search with the known prospect "Tytus Golas" to see whether Apollo could surface the intended person and enough context to verify identity before outreach.

INPUT
Search Apollo Find people for: Tytus Golas
↓
image
Output artifact for "Known-person lookup" test: Apollo's Find people search returned Tytus Golas with role and email information, plus enough profile context to help confirm that the result was the intended c, apollo-apollo-find-people-tytus-golas.png

Apollo's Find people search returned Tytus Golas with role and email information, plus enough profile context to help confirm that the result was the intended contact rather than a namesake.

Bottom Line
Apollo is effective when you already know the person you want to reach.
Prospect relevance still needs manual validation
Plausible matches are not the same as confirmed prospects.
▾
Test Summary
Feature tested: Prospect relevance still needs manual validation
Result: Passed — Plausible matches are not the same as confirmed prospects.

Feature tested: Prospect relevance still needs manual validation

Result: Passed

Verdict: Plausible matches are not the same as confirmed prospects.

Expected behavior: Tested whether a contact surfaced from a company record could be treated as a qualified prospect without additional checking by reviewing Apollo's Chapple company page and then cross-checking the related LinkedIn profile.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Company record review

Observed output: Output artifact (Image): On the Chapple company page, Apollo surfaced a person record that initially looked relevant to the company based on the company/contact association shown in the — apollo-apollo-company-page-chapple.png

Input artifact: Input artifact (Text prompt): Company record review

Output artifact: Output artifact (Image): On the Chapple company page, Apollo surfaced a person record that initially looked relevant to the company based on the company/contact association shown in the — apollo-apollo-company-page-chapple.png

What changed: Text prompt transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Manual validation step

Observed output: Output artifact (Image): Reviewing Ann Chapple's LinkedIn profile showed why Apollo results still need manual validation: a plausible company/contact match is not the same thing as a co — apollo-linkedin-profile-ann-chapple.png

Input artifact: Input artifact (Text prompt): Manual validation step

Output artifact: Output artifact (Image): Reviewing Ann Chapple's LinkedIn profile showed why Apollo results still need manual validation: a plausible company/contact match is not the same thing as a co — apollo-linkedin-profile-ann-chapple.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Apollo can surface likely contacts, but users still need to confirm role and relevance before outreach.

Tested whether a contact surfaced from a company record could be treated as a qualified prospect without additional checking by reviewing Apollo's Chapple company page and then cross-checking the related LinkedIn profile.

INPUT
Open the Apollo company page for Chapple and inspect the people table.
↓
image
Output artifact for "Prospect relevance still needs manual validation" test: On the Chapple company page, Apollo surfaced a person record that initially looked relevant to the company based on the company/contact association shown in the, apollo-apollo-company-page-chapple.png

On the Chapple company page, Apollo surfaced a person record that initially looked relevant to the company based on the company/contact association shown in the record.

INPUT
Cross-check the surfaced contact against LinkedIn: Ann Chapple
↓
image
Output artifact for "Prospect relevance still needs manual validation" test: Reviewing Ann Chapple's LinkedIn profile showed why Apollo results still need manual validation: a plausible company/contact match is not the same thing as a co, apollo-linkedin-profile-ann-chapple.png

Reviewing Ann Chapple's LinkedIn profile showed why Apollo results still need manual validation: a plausible company/contact match is not the same thing as a confirmed, currently relevant prospect.

Bottom Line
Apollo can surface likely contacts, but users still need to confirm role and relevance before outreach.
Contact accuracy on surfaced emails
Usable contact data exists, but accuracy is not guaranteed on hard cases.
▾
Test Summary
Feature tested: Contact accuracy on surfaced emails
Result: Passed — Usable contact data exists, but accuracy is not guaranteed on hard cases.

Feature tested: Contact accuracy on surfaced emails

Result: Passed

Verdict: Usable contact data exists, but accuracy is not guaranteed on hard cases.

Expected behavior: Tested a contact-accuracy edge case by searching Vespa.ai for Frode Lundgren in Apollo and comparing the returned email against an externally verified contact record.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Apollo contact lookup

Observed output: Output artifact (Image): Apollo's Vespa.ai company page filtered to Frode Lundgren returned a direct email, frodelu@vespa.ai, along with a request-phone action. — apollo-apollo-vespa-ai-filtered-contact.png

Input artifact: Input artifact (Text prompt): Apollo contact lookup

Output artifact: Output artifact (Image): Apollo's Vespa.ai company page filtered to Frode Lundgren returned a direct email, frodelu@vespa.ai, along with a request-phone action. — apollo-apollo-vespa-ai-filtered-contact.png

What changed: Text prompt transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): External validation

Observed output: Output artifact (Image): In the validation artifact, Smartlead showed a different verified address for the same person, frode@vespa.ai. That mismatch means Apollo's surfaced email shoul — apollo-smartlead-verified-contact-table.png

Input artifact: Input artifact (Text prompt): External validation

Output artifact: Output artifact (Image): In the validation artifact, Smartlead showed a different verified address for the same person, frode@vespa.ai. That mismatch means Apollo's surfaced email shoul — apollo-smartlead-verified-contact-table.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Apollo can expose direct emails, but researchers should still verify them before sending.

Tested a contact-accuracy edge case by searching Vespa.ai for Frode Lundgren in Apollo and comparing the returned email against an externally verified contact record.

INPUT
Open the Vespa.ai company page in Apollo and filter people for: Frode Lundgren
↓
image
Output artifact for "Contact accuracy on surfaced emails" test: Apollo's Vespa.ai company page filtered to Frode Lundgren returned a direct email, frodelu@vespa.ai, along with a request-phone action., apollo-apollo-vespa-ai-filtered-contact.png

Apollo's Vespa.ai company page filtered to Frode Lundgren returned a direct email, frodelu@vespa.ai, along with a request-phone action.

INPUT
Validate the surfaced Frode Lundgren email against an external verified contact record.
↓
image
Output artifact for "Contact accuracy on surfaced emails" test: In the validation artifact, Smartlead showed a different verified address for the same person, frode@vespa.ai. That mismatch means Apollo's surfaced email shoul, apollo-smartlead-verified-contact-table.png

In the validation artifact, Smartlead showed a different verified address for the same person, frode@vespa.ai. That mismatch means Apollo's surfaced email should be checked before it is used in live outreach.

Bottom Line
Apollo can expose direct emails, but researchers should still verify them before sending.
Employee coverage and freshness
Good breadth, imperfect freshness.
▾
Test Summary
Feature tested: Employee coverage and freshness
Result: Passed — Good breadth, imperfect freshness.

Feature tested: Employee coverage and freshness

Result: Passed

Verdict: Good breadth, imperfect freshness.

Expected behavior: Tested how completely Apollo represented FutureSmart AI by reviewing the company's employee list and comparing it against current company information.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Company employee listing

Observed output: Output artifact (Image): Apollo surfaced 24 employee records for FutureSmart AI, spanning roles such as AI Content Research Intern, Gen AI QA Intern, Gen AI Intern, and Frontend Enginee — apollo-apollo-company-page-futuresmart-ai.png

Input artifact: Input artifact (Text prompt): Company employee listing

Output artifact: Output artifact (Image): Apollo surfaced 24 employee records for FutureSmart AI, spanning roles such as AI Content Research Intern, Gen AI QA Intern, Gen AI Intern, and Frontend Enginee — apollo-apollo-company-page-futuresmart-ai.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Apollo gives a useful org snapshot, but not a guaranteed current roster.

Tested how completely Apollo represented FutureSmart AI by reviewing the company's employee list and comparing it against current company information.

INPUT
Open the Apollo company page for FutureSmart AI and review the people list.
↓
image
Output artifact for "Employee coverage and freshness" test: Apollo surfaced 24 employee records for FutureSmart AI, spanning roles such as AI Content Research Intern, Gen AI QA Intern, Gen AI Intern, and Frontend Enginee, apollo-apollo-company-page-futuresmart-ai.png

Apollo surfaced 24 employee records for FutureSmart AI, spanning roles such as AI Content Research Intern, Gen AI QA Intern, Gen AI Intern, and Frontend Engineer. The breadth was useful for initial prospecting, but validation against current company information showed that the list was not fully current: some team members were missing and some surfaced names may no longer have been active at the company.

Bottom Line
Apollo gives a useful org snapshot, but not a guaranteed current roster.
Natural-language prospect discovery
Good at turning intent into filters, not at delivering a finished shortlist.
▾
Test Summary
Feature tested: Natural-language prospect discovery
Result: Passed — Good at turning intent into filters, not at delivering a finished shortlist.

Feature tested: Natural-language prospect discovery

Result: Passed

Verdict: Good at turning intent into filters, not at delivering a finished shortlist.

Expected behavior: Tested Apollo AI Assistant with the prompt: "Find 10 AI startups in customer support automation and identify the most relevant contacts for partnership outreach."

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): AI Assistant prompt

Observed output: Output artifact (Image): Apollo translated the natural-language request into explicit keyword and industry filters, then returned a large results pool rather than a finished shortlist. — apollo-apollo-ai-startups-customer-support-filtered-search.png

Input artifact: Input artifact (Text prompt): AI Assistant prompt

Output artifact: Output artifact (Image): Apollo translated the natural-language request into explicit keyword and industry filters, then returned a large results pool rather than a finished shortlist. — apollo-apollo-ai-startups-customer-support-filtered-search.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The AI Assistant helps structure prospecting searches, but users still need to narrow and qualify the results.

Tested Apollo AI Assistant with the prompt: "Find 10 AI startups in customer support automation and identify the most relevant contacts for partnership outreach."

INPUT
Find 10 AI startups in customer support automation and identify the most relevant contacts for partnership outreach.
↓
image
Output artifact for "Natural-language prospect discovery" test: Apollo translated the natural-language request into explicit keyword and industry filters, then returned a large results pool rather than a finished shortlist., apollo-apollo-ai-startups-customer-support-filtered-search.png

Apollo translated the natural-language request into explicit keyword and industry filters, then returned a large results pool rather than a finished shortlist. The captured search showed 71K total companies and 7,134 matching results, including companies like Verloop.io, Lucidya, Wati, SuperAGI, INSIDEA, and CEQUENS. This made the prompt useful as a search-builder, but not as a turnkey 'find 10 best prospects' workflow.

Bottom Line
The AI Assistant helps structure prospecting searches, but users still need to narrow and qualify the results.
Chrome extension enrichment on LinkedIn and websites
Helpful for inline research and faster workflow handoff.
▾
Test Summary
Feature tested: Chrome extension enrichment on LinkedIn and websites
Result: Passed — Helpful for inline research and faster workflow handoff.

Feature tested: Chrome extension enrichment on LinkedIn and websites

Result: Passed

Verdict: Helpful for inline research and faster workflow handoff.

Expected behavior: Tested Apollo's browser extension on a real LinkedIn profile and on a company website to see whether it could surface prospect and company information without leaving the page.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): LinkedIn extension test

Observed output: Output artifact (Image): On Tytus Golas's LinkedIn profile, Apollo matched the person record in-page and surfaced role, company, email, and next-step actions like Add to list, Add to Se — apollo-linkedin-plus-apollo-contact-panel-tytus-golas.png

Input artifact: Input artifact (Text prompt): LinkedIn extension test

Output artifact: Output artifact (Image): On Tytus Golas's LinkedIn profile, Apollo matched the person record in-page and surfaced role, company, email, and next-step actions like Add to list, Add to Se — apollo-linkedin-plus-apollo-contact-panel-tytus-golas.png

What changed: Text prompt transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Website extension test

Observed output: Output artifact (Image): On Marblism's website, Apollo identified the company directly from the page and opened a sidebar with company category, location, phone, employee count, and key — apollo-marblism-landing-page-with-apollo-company-sidebar.png

Input artifact: Input artifact (Text prompt): Website extension test

Output artifact: Output artifact (Image): On Marblism's website, Apollo identified the company directly from the page and opened a sidebar with company category, location, phone, employee count, and key — apollo-marblism-landing-page-with-apollo-company-sidebar.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: The extension materially reduces manual effort when researching prospects in the browser.

Tested Apollo's browser extension on a real LinkedIn profile and on a company website to see whether it could surface prospect and company information without leaving the page.

INPUT
Open Tytus Golas's LinkedIn profile with the Apollo extension active.
↓
image
Output artifact for "Chrome extension enrichment on LinkedIn and websites" test: On Tytus Golas's LinkedIn profile, Apollo matched the person record in-page and surfaced role, company, email, and next-step actions like Add to list, Add to Se, apollo-linkedin-plus-apollo-contact-panel-tytus-golas.png

On Tytus Golas's LinkedIn profile, Apollo matched the person record in-page and surfaced role, company, email, and next-step actions like Add to list, Add to Sequence, and Compose email. That reduced context-switching between research and outreach setup.

INPUT
Visit marblism.com with the Apollo extension active.
↓
image
Output artifact for "Chrome extension enrichment on LinkedIn and websites" test: On Marblism's website, Apollo identified the company directly from the page and opened a sidebar with company category, location, phone, employee count, and key, apollo-marblism-landing-page-with-apollo-company-sidebar.png

On Marblism's website, Apollo identified the company directly from the page and opened a sidebar with company category, location, phone, employee count, and keyword-style enrichment tags. That gave quick firmographic context before running a full search in Apollo.

Bottom Line
The extension materially reduces manual effort when researching prospects in the browser.
API search and enrichment access
Automation-friendly.
▾
Test Summary
Feature tested: API search and enrichment access
Result: Passed — Automation-friendly.

Feature tested: API search and enrichment access

Result: Passed

Verdict: Automation-friendly.

Expected behavior: Tested whether Apollo exposes APIs for search and enrichment workflows that could be integrated into internal automation.

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Developer portal check

Observed output: Output artifact (Image): Apollo's developer portal showed separate Search API and Enrichment API entry points, along with usage and subscription pages on the dashboard. That confirms Ap — apollo-apollo-api-quickstart-dashboard.png

Input artifact: Input artifact (Text prompt): Developer portal check

Output artifact: Output artifact (Image): Apollo's developer portal showed separate Search API and Enrichment API entry points, along with usage and subscription pages on the dashboard. That confirms Ap — apollo-apollo-api-quickstart-dashboard.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Apollo can plug into internal prospecting workflows instead of forcing everything through the UI.

Tested whether Apollo exposes APIs for search and enrichment workflows that could be integrated into internal automation.

INPUT
Review Apollo's API Developer Portal for prospect search and enrichment capabilities.
↓
image
Output artifact for "API search and enrichment access" test: Apollo's developer portal showed separate Search API and Enrichment API entry points, along with usage and subscription pages on the dashboard. That confirms Ap, apollo-apollo-api-quickstart-dashboard.png

Apollo's developer portal showed separate Search API and Enrichment API entry points, along with usage and subscription pages on the dashboard. That confirms Apollo can support programmatic prospect search and record enrichment outside the web app.

Bottom Line
Apollo can plug into internal prospecting workflows instead of forcing everything through the UI.
Template-based outreach drafts
Fast but rigid.
▾
Test Summary
Feature tested: Template-based outreach drafts
Result: Passed — Fast but rigid.

Feature tested: Template-based outreach drafts

Result: Passed

Verdict: Fast but rigid.

Expected behavior: Tested Apollo's template-style email generation in a sequence using the AIDemos outreach context and a subject template that personalized the company name.

Test case: PDF document → Image

Input type: PDF document

Input used: Input artifact (PDF document): Context document used for Apollo's outreach email tests. — apollo-aidemos-outreach-context.pdf

Observed output: Output artifact (Image): In template mode, Apollo produced a preview that stayed close to the original sequence template and mainly swapped in light variables such as the company name. — apollo-apollo-outbound-sequence-editor-preview.png

Input artifact: Input artifact (PDF document): Context document used for Apollo's outreach email tests. — apollo-aidemos-outreach-context.pdf

Output artifact: Output artifact (Image): In template mode, Apollo produced a preview that stayed close to the original sequence template and mainly swapped in light variables such as the company name. — apollo-apollo-outbound-sequence-editor-preview.png

What changed: PDF document transformed into Image

Why it matters / Conclusion: Template mode is quick to launch, but it does not add much intelligence by itself.

Tested Apollo's template-style email generation in a sequence using the AIDemos outreach context and a subject template that personalized the company name.

pdf
apollo-aidemos-outreach-context.pdf

Context document used for Apollo's outreach email tests.

↓
image
Output artifact for "Template-based outreach drafts" test: In template mode, Apollo produced a preview that stayed close to the original sequence template and mainly swapped in light variables such as the company name., apollo-apollo-outbound-sequence-editor-preview.png

In template mode, Apollo produced a preview that stayed close to the original sequence template and mainly swapped in light variables such as the company name. The research notes also flagged that unresolved or unsupported variables can leak into the final message, so templates need validation before they are used at scale.

Bottom Line
Template mode is quick to launch, but it does not add much intelligence by itself.
Prompt-driven email writing
More controllable than templates when the prompt is good.
▾
Test Summary
Feature tested: Prompt-driven email writing
Result: Passed — More controllable than templates when the prompt is good.

Feature tested: Prompt-driven email writing

Result: Passed

Verdict: More controllable than templates when the prompt is good.

Expected behavior: Tested Apollo's prompt mode by providing business context and instructions for an outbound email instead of relying on a rigid template.

Test case: PDF document → Image

Input type: PDF document

Input used: Input artifact (PDF document): Context document used for Apollo's prompt-based email test. — apollo-aidemos-outreach-context.pdf

Observed output: Output artifact (Image): Apollo's prompt editor let the researcher choose a model, supply a prompt template, and add user instructions before previewing an email to Tytus Golas. Compare — apollo-apollo-outbound-email-prompt-editor.png

Input artifact: Input artifact (PDF document): Context document used for Apollo's prompt-based email test. — apollo-aidemos-outreach-context.pdf

Output artifact: Output artifact (Image): Apollo's prompt editor let the researcher choose a model, supply a prompt template, and add user instructions before previewing an email to Tytus Golas. Compare — apollo-apollo-outbound-email-prompt-editor.png

What changed: PDF document transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Preview generation

Observed output: Output artifact (Image): The resulting draft referenced Tidio's scale and the difficulty of standing out in a crowded market, showing that prompt mode can produce a usable cold email wh — apollo-apollo-email-preview-tidio-outreach.png

Input artifact: Input artifact (Text prompt): Preview generation

Output artifact: Output artifact (Image): The resulting draft referenced Tidio's scale and the difficulty of standing out in a crowded market, showing that prompt mode can produce a usable cold email wh — apollo-apollo-email-preview-tidio-outreach.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Prompt mode outperformed templates, but success depended heavily on the instructions supplied by the user.

Tested Apollo's prompt mode by providing business context and instructions for an outbound email instead of relying on a rigid template.

pdf
apollo-aidemos-outreach-context.pdf

Context document used for Apollo's prompt-based email test.

↓
image
Output artifact for "Prompt-driven email writing" test: Apollo's prompt editor let the researcher choose a model, supply a prompt template, and add user instructions before previewing an email to Tytus Golas. Compare, apollo-apollo-outbound-email-prompt-editor.png

Apollo's prompt editor let the researcher choose a model, supply a prompt template, and add user instructions before previewing an email to Tytus Golas. Compared with template mode, the draft reflected the supplied positioning and context more directly.

INPUT
Generate a full prompt-driven preview for Tytus Golas at Tidio.
↓
image
Output artifact for "Prompt-driven email writing" test: The resulting draft referenced Tidio's scale and the difficulty of standing out in a crowded market, showing that prompt mode can produce a usable cold email wh, apollo-apollo-email-preview-tidio-outreach.png

The resulting draft referenced Tidio's scale and the difficulty of standing out in a crowded market, showing that prompt mode can produce a usable cold email when enough business context is provided.

Bottom Line
Prompt mode outperformed templates, but success depended heavily on the instructions supplied by the user.
Assisted personalization with Apollo research signals
Best draft quality in the test, but still mostly company-level personalization.
▾
Test Summary
Feature tested: Assisted personalization with Apollo research signals
Result: Passed — Best draft quality in the test, but still mostly company-level personalization.

Feature tested: Assisted personalization with Apollo research signals

Result: Passed

Verdict: Best draft quality in the test, but still mostly company-level personalization.

Expected behavior: Tested Apollo's assisted email mode, which can pull in research signals such as company news, network posts, job postings, executive persona research, and strategic company research.

Test case: PDF document → Image

Input type: PDF document

Input used: Input artifact (PDF document): Context document used for Apollo's assisted personalization test. — apollo-aidemos-outreach-context.pdf

Observed output: Output artifact (Image): Apollo exposed assisted options like Recent company news, Professional network posts, Relevant job postings, Executive persona research, and Strategic company r — apollo-apollo-email-type-and-research-options.png

Input artifact: Input artifact (PDF document): Context document used for Apollo's assisted personalization test. — apollo-aidemos-outreach-context.pdf

Output artifact: Output artifact (Image): Apollo exposed assisted options like Recent company news, Professional network posts, Relevant job postings, Executive persona research, and Strategic company r — apollo-apollo-email-type-and-research-options.png

What changed: PDF document transformed into Image

Test case: Text prompt → Image

Input type: Text prompt

Input used: Input artifact (Text prompt): Assisted preview generation

Observed output: Output artifact (Image): The assisted draft produced the most contextual output of the three approaches: it framed Tidio's challenge as proving real AI support performance against named — apollo-apollo-email-preview-support-proof-gap.png

Input artifact: Input artifact (Text prompt): Assisted preview generation

Output artifact: Output artifact (Image): The assisted draft produced the most contextual output of the three approaches: it framed Tidio's challenge as proving real AI support performance against named — apollo-apollo-email-preview-support-proof-gap.png

What changed: Text prompt transformed into Image

Why it matters / Conclusion: Assisted mode was Apollo's strongest writing workflow in this test, but it still stopped short of deep one-to-one personalization.

Tested Apollo's assisted email mode, which can pull in research signals such as company news, network posts, job postings, executive persona research, and strategic company research.

pdf
apollo-aidemos-outreach-context.pdf

Context document used for Apollo's assisted personalization test.

↓
image
Output artifact for "Assisted personalization with Apollo research signals" test: Apollo exposed assisted options like Recent company news, Professional network posts, Relevant job postings, Executive persona research, and Strategic company r, apollo-apollo-email-type-and-research-options.png

Apollo exposed assisted options like Recent company news, Professional network posts, Relevant job postings, Executive persona research, and Strategic company research, then generated an outreach draft to Tytus Golas.

INPUT
Generate an assisted outreach draft for Tytus Golas focused on Tidio's AI support positioning.
↓
image
Output artifact for "Assisted personalization with Apollo research signals" test: The assisted draft produced the most contextual output of the three approaches: it framed Tidio's challenge as proving real AI support performance against named, apollo-apollo-email-preview-support-proof-gap.png

The assisted draft produced the most contextual output of the three approaches: it framed Tidio's challenge as proving real AI support performance against named competitors like Intercom, Zendesk, and Gorgias. Even so, the personalization remained stronger at the company level than at the individual prospect level.

Bottom Line
Assisted mode was Apollo's strongest writing workflow in this test, but it still stopped short of deep one-to-one personalization.

Apollo pricing observed during testing

Plans captured from Apollo's billing page during the research. Annual billing was shown in the screenshots.

Free
$0
Current plan in the captured view; 75 credits.
Basic
$49 per seat/month
Billed annually; 30,000 credits. Selected in the captured billing view.
Professional
$79 per seat/month
Billed annually; 48,000 credits.
Organization
$119 per seat/month
Billed annually; 72,000 credits.

The captured billing summary showed the Basic plan at $588/year for 1 seat when billed annually.

Is This Right For You?

A side-by-side guide based on our hands-on testing.

✓ Use This If
●You want company discovery, people search, contact lookup, and email drafting in one platform.
●You research prospects directly on LinkedIn or company websites and want inline enrichment from a browser extension.
●You need Search API and Enrichment API access for internal prospecting or enrichment workflows.
✕ Skip This If
●You need employee lists to be fully current without manual verification.
●You need every surfaced direct email to be treated as verified and ready to send.
●You want highly individualized prospect-level personalization without carefully prompting or reviewing the output.
Business & MarketingOthertextMarketing
Yes. In testing, Apollo returned a matching company result for the search "vespa.ai," giving a usable starting record for prospecting inside the platform.
Yes. Searching for Tytus Golas returned the intended contact along with role and other profile context, which helped reduce manual identity checking before outreach.
Mixed. Apollo surfaced direct emails for some contacts, but a Vespa.ai test returned frodelu@vespa.ai for Frode Lundgren while an external validation record showed a different verified address, frode@vespa.ai. The result is usable for research, but email data should still be verified before sending.
Apollo showed useful breadth, but not perfect freshness. For FutureSmart AI, Apollo surfaced 24 employee records across multiple roles, yet validation against current company information indicated that some team members were missing and some surfaced people may no longer have been current.
Yes. In testing, Apollo's Chrome extension matched Tytus Golas directly on LinkedIn and surfaced contact actions in-page. It also identified Marblism from the company website and showed company enrichment data in a sidebar.
Yes, but it behaves more like an AI search-builder than a finished SDR agent. The prompt about finding AI startups in customer support automation was converted into filters and returned a large pool of matching companies, which still required narrowing and selection.
Template mode mostly mirrored the original template with light personalization. Prompt mode reflected the user's instructions and business context more directly. Assisted mode produced the strongest draft by incorporating company-level research signals, but prospect-specific personalization remained limited.
Yes. The developer portal showed separate Search API and Enrichment API entry points, indicating Apollo can support programmatic search and enrichment workflows outside the web app.
The billing page showed Free at $0 with 75 credits, Basic at $49 per seat per month billed annually with 30,000 credits, Professional at $79 with 48,000 credits, and Organization at $119 with 72,000 credits. The captured Basic summary showed $588/year for 1 seat.

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