Second Talent alternatives, compared on what you can actually verify

Second Talent is an APAC (Asian Pacific) focused hiring platform. It publishes more information than many competitors. Its developer rate card breaks rates down by country, city, seniority and engagement type.

What it does not publish is how those figures were calculated.

On 18 August 2026, we reviewed twelve platforms in this category. All twelve publish figures about their services. None explains the method, sample size or observation period behind its vetting, retention or savings claims.

The alternatives covered are Toptal, Proxify, Arc.dev, Revelo, Lemon.io, Index.dev, Andela, Braintrust, Gun.io, Howdy, Turing and RocketDevs.

This article focuses on what a buyer can verify before signing. We apply the same test to RocketDevs.

Key facts

The takeaway is simple: the sector is not short of numbers. It is short of denominators.

Every absence recorded here means the information was not stated on the page we reviewed on that date. It is not a claim about what the company knows or does internally.

In this article:

• What Second Talent actually publishes
• Where its AI citations actually come from
• Which platforms publish a screening rate
• What the research says a real filter looks like
• Why the pool-size numbers do not add up
• The five things nobody discloses
• How to compare platforms when the numbers are unverifiable
• Which platforms practitioners actually discuss
• The alternatives, one by one
• Where RocketDevs sits, held to the same standard
• Conclusion
• FAQ

What does Second Talent actually publish?

More than its homepage suggests. That is worth stating because the homepage alone gives an incomplete picture.

An earlier version of this research concluded that Second Talent published nothing checkable. That was wrong. We had reviewed only one page. Correcting that mistake made the finding stronger.

The homepage describes its vetting process as “Coding tests, peer interviews, and role checks, matched to your exact stack”. It says there are “$0 upfront costs, pay only when you make a hire”. It also names Adobe, Crypto.com, Lacoste, L'Occitane, Lululemon, Yusen Logistics and Neopets as clients.

It publishes several headline figures:

• “50-70% payroll savings”
• “save $103,000+ per hire”
• “92% talent retention rate”
• “4.9/5” client rating
• Matching within “24 Hours”

These figures are self reported by Second Talent. We do not include them in the comparison table below. The next section explains why.

Second Talent also publishes a developer rate card. This is unusually detailed.

The Philippines page breaks developer pay down by salary, engagement type and location. Monthly salaries range from “₱30,000 – ₱50,000” for junior developers to “₱90,000 – ₱160,000” for senior developers.

Hourly rates range from “$8 – $18” for a junior remote hire to “$50 – $80” for a lead or architect.

The page also gives city level ranges. Metro Manila is listed at “₱55,000 – ₱180,000”. Davao City is listed at “₱35,000 – ₱95,000”

Where do Second Talent's AI citations actually come from?

Not from hiring authority. They come from a content strategy.

Second Talent's strongest search visibility comes from AI related explainers rather than hiring content. These include reviews of ChatGPT Atlas targeting a query with 40,500 monthly searches, comparisons of Claude and Gemini models, roundups of Chinese AI companies, remote work statistics targeting a 14,800 monthly search query, and a review of Perplexity Comet.

Its own brand term, “second talent”, has a reported search volume of 40.

Two independent signals point to limited brand awareness. A Hacker News search for the exact term “secondtalent” returns no results. Semrush reports monthly search volume of 40 for the brand term.

The answer engine visibility is real. The practitioner audience behind it is less established.

The mechanism is straightforward. Second Talent publishes a high volume of structured explainers on topics that answer engines frequently encounter. Those pages can then be cited in AI generated answers.

The citations themselves are genuine. They are not evidence of hiring quality. A buyer should not treat an AI citation as an endorsement of Second Talent's placement service. That is more detail than most platforms in this sector publish. Credit where it is due.The problem is the missing methodology.

The page does not state its data source. It does not give a sample size. It does not explain how the salary bands were calculated or when they were last updated. A four way breakdown with ranges precise to the nearest thousand pesos suggests a substantial dataset. The dataset is not identified.

That matters more than simply having another number. A vague claim invites scepticism. A precise table can create confidence. Without a source or methodology, that precision is not evidence.

Which platforms publish a screening rate?

Four of the twelve publish a screening rate. Only one also publishes the applicant volume behind it.

Toptal publishes a five stage funnel with a pass rate for each stage. Proxify states that “only 1% of applicants” are accepted. Lemon.io says, “Only 1% do.” Index.dev implies a rate of about 1.2% by comparing a pool of 30,000 with a source population of 2.5 million. The other eight publish no numeric screening rate.

Proxify is the only platform in this group that publishes both figures. Its statistics page lists “1% Top accepted applicants” alongside “20,000 applicants per month”.

That pairing is more useful than a percentage alone. A rate without a denominator tells you very little. One percent of a small, self selecting applicant pool is not the same filter as one percent of 20,000 applicants each month.

RocketDevs is included on the same terms as every other platform. Our 98%+ rejection rate and Top 2% acceptance bar are self reported. We also publish the cohort denominator. For Q1 2026, that figure was n=14,233. No external party has audited it.

What does the research say a real filter looks like?

This is the part of the subject where genuine measurement exists. None of it comes from a hiring platform.

Personnel selection has been studied for decades. A major 1998 meta analysis published in Psychological Bulletin found that the strongest combinations for predicting job performance included general mental ability with a work sample, an integrity test or a structured interview. The strongest combinations had mean validity scores between .63 and .65.

Two other meta analyses reached a similar conclusion about interviews. A 1994 study analysed 245 coefficients from 86,311 people. It found that structured interviews had higher validity than unstructured interviews. A 1988 study based on 150 validity coefficients found structured interviews were about twice as valid as unstructured ones.

That distinction matters when evaluating hiring platforms.

Every platform in this comparison describes its filter by counting stages. None explains whether its interviews are structured. None explains whether candidates complete the same tasks under the same scoring system. None shows whether its work samples resemble the job being filled.

Stage count is what platforms advertise. Structure is what the research measures. A five stage process is not automatically better than a two stage process. The quality of the assessment matters more than the number of steps.

One of the most useful questions to ask on a sales call is: How is each candidate assessed, and is the process structured and scored consistently?

It costs nothing to ask.

Why do the pool size numbers not add up?

Two platforms in this comparison publish pool figures that do not clearly reconcile. Neither case is difficult to spot.

Arc.dev gives two different figures on the same page. Its hiring page says Arc has “239279 full-time and freelance developers, engineers, programmers, coders, contractors, and tech experts ready to interview”. Its FAQ later states “450,000+ talent in 190 countries”.

Both figures could be accurate if they refer to different groups. Arc does not explain the difference. A reader cannot tell which population each figure represents.

Andela's figures also vary by source. Its homepage states “17K certified AI-native engineers” and “200K+ talent trained on emerging technologies”. Wikipedia describes a pool of more than 150,000 digital talent. TechCrunch reported on Andela's $200 million Series E in September 2021. It quoted the chief executive describing thousands of developers using the platform and engineers in more than 80 countries.

These figures may all describe different populations. Trained talent is not the same as certified talent. Certified talent is not necessarily available to hire today.

None of this is an accusation. Measuring a talent network is genuinely difficult. Different definitions can produce different figures. The practical issue for buyers is simpler: a pool figure without a stated population cannot be compared reliably with another pool figure. Ranking platforms by network size is therefore only useful when you know exactly what each number counts.

What does nobody in this sector disclose?

Five important things are largely missing from the public information. Their absence can tell a buyer more than the headline figures.

1. A method.

Zero of twelve platforms state a method behind their key performance figures. The only data source we found belongs to Howdy. Its cost calculator says estimates are based on Glassdoor, Salary.com and live Howdy data. That is a useful disclosure. It applies to the salary calculator, not to the vetting or retention figures published elsewhere on the site.

2. The denominator.

Only one platform publishes the applicant volume behind its screening rate. The others give percentages without showing how many applicants those percentages represent.

3. The savings baseline.

A claim such as “50-70% savings” is meaningless without knowing what it is compared with. Savings against a US senior developer salary is very different from savings against an offshore agency rate.

4. Vetting depth in hours.

Listing stages does not tell you how long the process takes. Hours give a clearer picture of the work involved in assessment.

5. Trial and guarantee terms.

Only two of twelve platforms publish a numeric trial or guarantee window. This is the most practical figure on the list because it transfers some risk back to the platform.

For buyers, the last point deserves particular attention. A headline percentage is easy to publish. A contractual guarantee is much harder to ignore.

How do you compare platforms when the numbers are unverifiable?

Stop comparing claims. Compare commitments. A claim describes what a platform says about its past. A commitment describes what the platform will do if it gets something wrong.

Four questions cut through most of the marketing:

1. *What happens if the developer is not a good fit, and how quickly?*A money back window is a commitment. A vague replacement promise is not. Only two of the twelve platforms reviewed publish a specific time period.

2. *How many hours does each candidate spend in assessment?*A platform with a defined vetting process should be able to give you a number. If the answer is only adjectives, ask for the hours.

3. *What is your acceptance rate, and how many applicants does that represent?*A percentage without a denominator tells you very little. Only one platform in twelve publishes both figures. You may need to ask the others directly.

4. *Are the interviews structured?*Ask whether candidates complete the same tasks and receive the same scoring criteria. A conversation alone tells you less than a consistent assessment.

None of these questions requires you to trust a marketing page. All can be answered during a sales call. The better test is to ask what the platform can measure, what it can explain and what it is willing to put in writing.

Which platforms do practitioners actually discuss?

Very few. The difference is measurable.

Hacker News story counts for the exact platform names are small enough to check individually:

• usebraintrust: 2 stories
• index.dev: 1 story
• arc.dev: 10 stories, including 3 from the company's own blog
• lemon.io: 12 stories, mostly unrelated
• secondtalent: 0 stories
• gun.io: 184 stories, including one 51 point thread with 21 comments

A lack of discussion does not mean a platform is bad. It means word of mouth is not generating much visible discussion around it. This matters because buyers then have fewer independent signals to work with. They are more likely to rely on company websites, search results and AI generated summaries. This is what makes sourcing important. When independent discussion is limited, a published claim can carry more weight than it deserves.

The alternatives, and what each one lets you check

Every claim below is what the platform states about itself, based on pages read on 18 August 2026. None has a second independent source. That is why these figures are not treated as measurements in the comparison.

Toptal

Best for: buyers who want the selection process explained stage by stage.

Toptal publishes the clearest selectivity funnel in the group. It gives a pass rate for each of five stages: 26.4% pass the language and personality screen, followed by 7.4%, 3.6%, 3.2% and finally 3%. It also states that the full screening process takes three to eight weeks. Test projects take one to three weeks.

Pros: the only stage by stage funnel in the group, plus a stated duration.

Cons: no applicant volume, trial term, pool size or observation period behind the figures.

Proxify

Best for: buyers who want a published rate, price and notice period.

Proxify states that only 1% of applicants are accepted from 20,000 applicants per month. It also reports more than 6,000 vetted developers. Candidates are presented in an average of two days. Integration takes two weeks or less.

Its pricing page gives an indicative €5,100 to €8,000 per month for one senior developer working 40 hours a week. That equals €32 to €50 per hour. Contract termination requires two weeks' notice.

Pros: the only platform in this group that publishes an acceptance rate with its applicant volume. It also publishes prices and a notice period.

Cons: no trial window, vetting duration or stated method behind the 1% acceptance rate or 94% match success figure.

Arc.dev

Best for: buyers who want a published freelance rate and trial period.

Arc.dev publishes freelance rates of $15 to $110+ per hour. It states that hiring can take as little as 14 days. It also offers a risk free trial with refund and replacement.

Pros: a public rate range and trial terms.

Cons: two unreconciled pool figures appear on the same page. There is also no published acceptance rate.

Revelo

Best for: buyers hiring in Latin America who want a defined trial period.

Revelo describes its network as “LatAm's largest tech talent network of 400K+ vetted developers”. It promises an expert shortlist within 48 hours and reports an average time to hire of 14 days. Its clearest commercial term is the “14-day risk-free trial”.

Pros: one of only two platforms in the group with a numeric trial window.

Cons: no acceptance rate or published rates. The pool figure has no stated population.

Lemon.io

Best for: buyers who want a fast match and a relatively small vetted network.

Lemon.io states that “Only 1% do” when describing candidates who pass its vetting. It also reports more than 1,500 fully vetted developers, an average matching time of 24 hours and 2.3 million hours worked since 2015.

Its screening process is described as being run by “AI agents trained on 10 years of engineering assessments”. That gives more information about the mechanism than most platforms provide. It does not give a sample size or validation data.

Pros: a stated screening rate and some description of the assessment process.

Cons: no applicant volume, published rates or trial term on the pages reviewed. Its “50M+ profiles” figure counts profiles searched, not vetted developers.

Index.dev

Best for: buyers who want to see the selectivity arithmetic, even if indirectly.

Index.dev states that its pool contains more than 30,000 senior engineers, PhD researchers and evaluation specialists. It says this pool is filtered from 2.5 million professionals. That makes an implied selection rate of about 1.2% possible to calculate. The platform also reports matching within 24 to 48 hours, a 97% client repeat rate and $80 million in client hiring costs saved.

Pros: publishes both a pool and source population, making the implied rate calculable.

Cons: no published rates or trial terms. There is also no methodology behind the repeat rate or savings figure.

Andela

Best for: enterprise buyers who value scale and a long public track record.

Andela states that it has 17,000 certified AI native engineers and more than 200,000 people trained in emerging technologies. It also reports 98% enterprise client satisfaction.

TechCrunch independently reported on Andela's $200 million SoftBank Series E in September 2021. Wikipedia records its 2014 founding and a pool of more than 150,000.

Pros: substantial independent coverage of the company itself.

Cons: no acceptance rate, vetting duration, time to match or trial terms. Its network figures also vary across sources and do not use a common definition.

Braintrust

Best for: buyers looking across engineering, design, product and operations.

Braintrust states that buyers can access more than 2 million vetted professionals across those fields. It also describes AI matching that happens “in hours” and claims to accelerate time to hire by 80%.

Pros: the largest stated network in this group. It also describes its matching process.

Cons: no acceptance rate, vetting duration, published rates or trial terms on the pages reviewed. The 80% claim has no stated baseline.

Gun.io

Best for: buyers who want to check availability by specific skill.

Gun.io publishes counts for available developers by skill. Its figures include 1,967 Java developers, 2,820 Python developers, 3,950 JavaScript developers and 3,412 React developers. It is also the only platform in this group with a substantial Hacker News footprint.

Pros: skill level availability is more useful than a single headline pool figure. There is also genuine practitioner discussion.

Cons: no acceptance rate, vetting stages, vetting duration, time to match, published rates or trial terms on the page reviewed.

Howdy

Best for: buyers who want a cost estimate before speaking to sales.

Howdy states that it interviews more than 100,000 people each year. It also reports 98% retention.

Its cost calculator explains its data sources: “Estimations are based on information from Glassdoor, salary.com and live Howdy data.”

Pros: the only stated data source found across the twelve platforms. It also provides a public cost calculator.

Cons: the data source applies to the salary estimate, not the vetting or retention figures. There is no published acceptance rate, vetting duration or trial term.

Turing

Best for: buyers who plan to evaluate candidates themselves.

Turing's main page does not publish an acceptance rate, vetting duration, pool size, time to match or trial terms. This is a finding about the page reviewed on 18 August 2026. It does not mean the company has no such information elsewhere.

Pros: none that this research could verify from the page reviewed.

Cons: little publicly checkable information on the selection process.

Second Talent

Best for: buyers hiring in APAC who want regional pay benchmarks.

As covered above, Second Talent publishes one of the most detailed rate cards in the group. It breaks pay down by country, city, seniority and engagement type.

Pros: detailed regional pay bands are publicly available.

Cons: no source, sample size or revision date is given for those figures. There is also no published acceptance rate, vetting duration or trial term.

The side by side comparison

Published, unverified means the figure appears on the platform's own page, but no independent source confirms it. Not published means we read the relevant page on 18 August 2026 and found no figure there. Neither is an accusation. Both describe what a buyer can verify publicly.

None of these figures has a stated methodology.

Toptal's funnel does not state the period or applicant volume behind its rates. Second Talent's rate card gives no source or sample size. Arc.dev publishes two pool figures that do not clearly count the same population.

RocketDevs is not independently audited either.

That is the real finding. The sector publishes precise looking numbers, but rarely explains how those numbers were produced. For a buyer, the methodology matters more than the headline figure.

For broader comparisons, see our guides to the best remote developer platforms, Howdy alternatives, Toptal alternatives, Arc.dev alternatives and Upwork alternatives.

Where does RocketDevs sit?

In the same self reported category as everyone else, but with more of the underlying numbers made public.

We publish rates instead of broad savings claims:

• $9.99/hr for Associate developers
• $21.99/hr for Mid senior developers
• $30.99/hr for Senior developers

We also publish vetting depth of 6 to 8 hours per developer. Our applicant rejection rate is 98%+, with a Top 2% acceptance bar. For Q1 2026, the published cohort denominator is n=14,233.

Our trial is 14 days. It is risk free and money back.

None of these figures has been independently audited. It would be misleading to claim otherwise while criticising competitors for the same limitation.

The narrower claim is that our figures are specific and falsifiable. An assessment lasting 6 to 8 hours can be checked. A 14-day money back promise can be tested. A savings percentage with no stated baseline cannot.

There are also two areas where competitors disclose more than we do. Toptal publishes its funnel stage by stage. We publish a single rejection figure. Proxify publishes its acceptance rate alongside monthly applicant volume. We publish a cohort denominator, but not our ongoing intake. Both are useful disclosures. We should be held to the same standard.

Start with a vetted developer and judge the numbers against what happens during the trial window.

Conclusion

The problem with comparing developer platforms is not a lack of numbers. It is a lack of context behind those numbers.

Platforms publish acceptance rates, talent pool sizes, savings figures and retention claims. Few publish the denominator, methodology or time period behind them. Even fewer explain how their vetting process is measured. That does not make the numbers false. It makes them difficult to compare.

The better approach is to ask what you can actually verify. Look for the applicant volume behind an acceptance rate. Ask how many hours candidates spend being assessed. Check whether interviews are structured. Read the trial and replacement terms before you sign.

The same standard should apply to RocketDevs. Our published figures are self reported. They are not independently audited. What we can do is make them specific enough to test.

That is ultimately what this comparison is about. Not finding the platform with the biggest number. Finding the platform that gives you enough information to understand what the number means.

When a platform cannot show you the method, ask for it. When it cannot show you the denominator, ask for it. When it makes a promise, check whether that promise appears in the contract. Precise numbers are useful. Verifiable numbers are better.

Frequently asked questions

What are the best Second Talent alternatives?

The main alternatives in this category are Toptal, Proxify, Arc.dev, Revelo, Lemon.io, Index.dev, Andela, Braintrust, Gun.io, Howdy, Turing and RocketDevs.

The best choice depends on what the platform can verify. Look for a clear trial window. Ask how many hours candidates spend in assessment. Ask for the applicant volume behind any acceptance rate.

Is Second Talent legitimate?

Nothing in this research suggests otherwise. Second Talent publishes a described vetting process, an APAC sourcing footprint, named clients and a detailed rate card. The issue is not whether the company is legitimate. It is whether buyers can independently verify its published figures.

That limitation applies to almost every platform in this comparison, including RocketDevs.

Which platform publishes the most verifiable information?

Proxify performs best on the specific measures used in this comparison. It is the only one of twelve platforms that publishes an acceptance rate alongside its applicant volume. It also publishes indicative prices and a notice period.

Toptal provides the most detailed process disclosure. It publishes a five stage funnel with pass rates for each stage and a stated screening duration.

Neither publishes a methodology behind these figures.

Why does this comparison have so many cells that say “not published”?

Because filling those cells would mean turning marketing claims into apparent measurements.

Every quantitative platform claim we checked had a single source: the platform itself. Calling a figure “not published” is more useful than presenting an unverified number as if it were independently measured.

What should I ask a hiring platform before signing?

Ask four questions:

1. How many hours does one candidate spend in assessment?
2. What is your acceptance rate, and how many applicants does that represent?
3. Are the interviews structured, with the same tasks and scoring criteria for every candidate?
4. What happens if the hire is wrong, and exactly how long do I have to act?

All four questions can be answered on a sales call. None requires you to take a marketing page at face value.

Does a lower rate mean lower quality?

Not necessarily. Rate reflects the labour market and the margin added by the platform. Quality depends on the selection process.

A lower rate is not automatically a warning sign. A platform that will not explain how it assesses candidates gives you less information about the variable that matters most.

Ask about the filter before judging the price.

Sources

• Second Talent and its Philippines developer rate card, company website, all quoted claims read 18 August 2026. All figures attributed to Second Talent are self-reported by the company.
• Toptal, Top 3 Percent, Arc.dev hiring page, Turing, Index.dev, Proxify and its pricing page, Revelo, Lemon.io, Braintrust, Andela, Gun.io and Howdy, all company websites, all read 18 August 2026 and all figures self-reported by each company.
• Schmidt and Hunter, The validity and utility of selection methods in personnel psychology, Psychological Bulletin 124(2), 1998.
• McDaniel, Whetzel, Schmidt and Maurer, The validity of employment interviews: A comprehensive review and meta-analysis, Journal of Applied Psychology 79(4), 1994, drawing on 245 coefficients from 86,311 individuals.
• Wiesner and Cronshaw, A meta-analytic investigation of the impact of interview format and degree of structure on the validity of the employment interview, Journal of Occupational Psychology, 1988.
• TechCrunch, SoftBank sinks $200M into Andela, 29 September 2021, and the Wikipedia entry for Andela.
• Hacker News story counts via the Algolia API, accessed 18 August 2026.
• RocketDevs rates, vetting depth, rejection rate, cohort denominator and trial terms are our own published figures and have not been third-party audited.

James Hitch, COO at RocketDevs