Couldn't land an interview using LoopCV ?It's not your faultCouldn't land an interview using LoopCV ? It's not your fault

Founders Reply

Yes, we do hire associates based in India, including both full-time team members and vetted gig workers. Having a team in India is what allows us to offer this service at around $4/hour. Without that structure, the exact same human-assisted work would cost 4 to 5x more, which would put it out of reach for most job seekers. Every associate goes through multiple rounds of screening, including English proficiency checks, task-specific evaluations, and hands-on training before they ever work on a customer account. While there may have been some difficulty in understanding English, it usually comes down to accent, not an inability to speak the language. I’ve personally gone through this myself. When I moved to the U.S., I struggled for the first few months because of accent differences and even today, I still sometimes struggle with certain European English accents. That doesn’t mean people don’t speak English well; it just means accents take time to get used to. It’s also important to call out a simple reality: this is a human-powered service, not software. Unlike SaaS, where marginal cost is close to zero, human time always has a real cost. At this price point, we genuinely don’t know of any comparable human-assistant service that operates more affordably. If someone is specifically looking for a U.S.-only or locally based assistant team, that’s completely valid but it’s also a different service category, with very different pricing. Scale.jobs is built to balance quality, accessibility, and sustainability, and our team structure is a core part of that balance

Founders Reply

That’s correct and we’re very transparent about it. scale.jobs is a human assistant service, not a career coaching or strategy consulting service. Our assistants are trained to handle the grunt and operational work involved in job applications i.e., sourcing roles, filling out applications, managing data, and ensuring consistency, not to perform high-level strategic judgment or subjective career decision-making. Manually customizing every resume at a deep, strategic level would require a senior career coach or recruiter per customer, which would fundamentally change both the nature and cost of the service. Even then, there’s no objective authority who can say that a specific manual tweak will definitively improve interview chances. At the same time, AI technology has improved dramatically in certain areas and resume tailoring is one of them. We’ve taken a measured, pragmatic approach to AI: we use it where it genuinely adds value and avoid it where it doesn’t. For resume customization specifically, modern AI systems have reached a point where they are highly effective at tailoring resumes to job descriptions, often more consistently and efficiently than humans can at scale. In our experience, this approach delivers better outcomes than manual edits done under time and cost constraints. Importantly, this isn’t something we hide in fine print. We explicitly call this out as “AI Custom Resumes” in our pricing and product descriptions not “Custom Resumes.” We believe clarity upfront is better than surprise later. If someone is looking for fully manual, white-glove resume coaching for each application, that’s a valid need - it’s just a different service category than what Scale.jobs is designed to offer.

Founders Reply

Scale.jobs is a human assistant service, not a SaaS subscription where marginal cost is close to zero. Every new customer immediately triggers real, irreversible work on our side - onboarding calls, payment gateway fees, internal coordination, assigning a dedicated human assistant, and time spent aligning on preferences and expectations. Those costs exist whether a customer stays for a week or a month. We’re also a bootstrapped business, not a heavily VC-subsidized company that can absorb unlimited losses. Our goal is to make job search easier for candidates while keeping the business financially sustainable. That balance matters if we want to exist long-term. For that reason, our refund policy is pro-rated, with a one-time $100 onboarding fee to cover initial setup and operational costs. This policy is placed right next to our pricing section, not hidden in fine print so customers can make an informed decision before signing up. Comparisons to companies like Amazon or Walmart aren’t apples-to-apples. Those businesses operate at massive scale, with diversified revenue streams that offset cancellations and returns. We don’t have that luxury at our current stage and pretending otherwise wouldn’t be honest. For one-time services like LinkedIn Makeovers or Resume Reviews, we clearly state that they are non-refundable. These involve direct, one-off work from experienced career coaches, and once the work is done, the cost is already incurred. We understand refunds can be an emotional topic, especially during a stressful job search. Our aim is not to be rigid, it’s to be clear, fair, and upfront, so there are no surprises on either side.

Founders Reply

Yes, we did, and we’re open about it. We no longer offer this incentive, but like most businesses, we previously encouraged customers who had a positive experience to share it publicly. The important distinction was how we incentivized them. We didn’t offer cash, gift cards, or Amazon coupons. Instead, we offered additional service credits more of the same service they had already purchased. Customers would only opt in if they genuinely found the service useful enough to recommend. Extra credits wouldn’t have appealed to someone who didn’t see value in the service. From our perspective, the program was simply a way to: -Encourage word-of-mouth -Reward engaged customers -Give customers more value in the same form they originally paid for We weren’t trying to manufacture opinions or buy praise. We offered more of our service to customers who independently chose to share a positive experience. Transparency matters to us, which is why we’re open about this past practice rather than trying to disguise it.

Founders Reply

Let’s be very clear about what Scale.jobs does and what it doesn’t. We’re not doing anything magical here. We’re not promising jobs, interviews, or shortcuts. What we do is take the time-consuming, repetitive grunt work of job applications off your plate and give it to a trained human assistant, so you can redirect your time and mental energy toward things that actually move the needle: networking, referrals, interview prep, and skill-building.For many people, that shift alone can improve their odds but it’s not a guarantee. The reality is that the job market over the past few years has become highly volatile and unpredictable, with layoffs, hiring freezes, and constantly changing recruiter behavior across industries and geographies. This environment is very different from when we first started . In markets like this, outcomes such as recruiter responses or interview calls can fluctuate wildly, even when the quality, rigor, and consistency of our execution remain the same or continue to improve. Understandably, frustration with poor outcomes sometimes gets directed toward us, even when those outcomes are driven by forces far beyond our control. Here’s what we don’t control: -Hiring cycles and freezes -Recruiter bandwidth and response behavior -Internal referrals or headcount approvals -ATS filtering rules -Timing, competition, or market sentiment -Your Individual strength of profile for the role -Sponsorship Limitations We don’t have leverage inside companies, and we don’t have a magic wand to tilt decisions in anyone’s favor. Results depend heavily on timing, role availability, and an individual’s background, many variables no ethical service can influence. That said, we do take ownership when we make mistakes, miss context, or fall short of our own standards, and we actively correct course when that happens. What we ask is simple: please don’t use recruiter call volume or job offers as the sole yardstick to judge our effort or effectiveness, especially in an unstable market. Our role is to maximize execution quality, consistency, and coverage within real-world constraints, not to promise outcomes that no honest service can truly guarantee.

Founders Reply

It’s a trap!! Run away. Lower cost doesn’t always mean broader coverage or better outcomes. Most AI auto-apply platforms work only on short, one-page applications, typically on ATS platforms like Greenhouse and Lever. That limitation isn’t always made obvious. What is often omitted is that these platforms cannot apply to longer, more complex systems such as Workday, iCIMS, Taleo, and similar enterprise ATS tools. In practice, this means AI auto-apply tools tend to focus on a small slice of the job market—largely early-stage startups and select tech companies while silently skipping a much larger portion of roles, including many positions at Fortune 500 companies and large organizations. As a result: - You may be excluded from a significant number of legitimate opportunities without realizing it - Applications get concentrated into a narrow pool of roles that everyone using the same tool is applying to - Competition intensifies for that limited subset of jobs, making outcomes even more unpredictable The polished UI and “selected roles” messaging can make this feel intentional or curated, when in reality it’s often driven by technical constraints, not strategy.

Founders Reply

Yes, we do hire associates based in India, including both full-time team members and vetted gig workers. Having a team in India is what allows us to offer this service at around $4/hour. Without that structure, the exact same human-assisted work would cost 4 to 5x more, which would put it out of reach for most job seekers. Every associate goes through multiple rounds of screening, including English proficiency checks, task-specific evaluations, and hands-on training before they ever work on a customer account. While there may have been some difficulty in understanding English, it usually comes down to accent, not an inability to speak the language. I’ve personally gone through this myself. When I moved to the U.S., I struggled for the first few months because of accent differences and even today, I still sometimes struggle with certain European English accents. That doesn’t mean people don’t speak English well; it just means accents take time to get used to. It’s also important to call out a simple reality: this is a human-powered service, not software. Unlike SaaS, where marginal cost is close to zero, human time always has a real cost. At this price point, we genuinely don’t know of any comparable human-assistant service that operates more affordably. If someone is specifically looking for a U.S.-only or locally based assistant team, that’s completely valid but it’s also a different service category, with very different pricing. Scale.jobs is built to balance quality, accessibility, and sustainability, and our team structure is a core part of that balance

Founders Reply

That’s correct and we’re very transparent about it. scale.jobs is a human assistant service, not a career coaching or strategy consulting service. Our assistants are trained to handle the grunt and operational work involved in job applications i.e., sourcing roles, filling out applications, managing data, and ensuring consistency, not to perform high-level strategic judgment or subjective career decision-making. Manually customizing every resume at a deep, strategic level would require a senior career coach or recruiter per customer, which would fundamentally change both the nature and cost of the service. Even then, there’s no objective authority who can say that a specific manual tweak will definitively improve interview chances. At the same time, AI technology has improved dramatically in certain areas and resume tailoring is one of them. We’ve taken a measured, pragmatic approach to AI: we use it where it genuinely adds value and avoid it where it doesn’t. For resume customization specifically, modern AI systems have reached a point where they are highly effective at tailoring resumes to job descriptions, often more consistently and efficiently than humans can at scale. In our experience, this approach delivers better outcomes than manual edits done under time and cost constraints. Importantly, this isn’t something we hide in fine print. We explicitly call this out as “AI Custom Resumes” in our pricing and product descriptions not “Custom Resumes.” We believe clarity upfront is better than surprise later. If someone is looking for fully manual, white-glove resume coaching for each application, that’s a valid need - it’s just a different service category than what Scale.jobs is designed to offer.

Founders Reply

Scale.jobs is a human assistant service, not a SaaS subscription where marginal cost is close to zero. Every new customer immediately triggers real, irreversible work on our side - onboarding calls, payment gateway fees, internal coordination, assigning a dedicated human assistant, and time spent aligning on preferences and expectations. Those costs exist whether a customer stays for a week or a month. We’re also a bootstrapped business, not a heavily VC-subsidized company that can absorb unlimited losses. Our goal is to make job search easier for candidates while keeping the business financially sustainable. That balance matters if we want to exist long-term. For that reason, our refund policy is pro-rated, with a one-time $100 onboarding fee to cover initial setup and operational costs. This policy is placed right next to our pricing section, not hidden in fine print so customers can make an informed decision before signing up. Comparisons to companies like Amazon or Walmart aren’t apples-to-apples. Those businesses operate at massive scale, with diversified revenue streams that offset cancellations and returns. We don’t have that luxury at our current stage and pretending otherwise wouldn’t be honest. For one-time services like LinkedIn Makeovers or Resume Reviews, we clearly state that they are non-refundable. These involve direct, one-off work from experienced career coaches, and once the work is done, the cost is already incurred. We understand refunds can be an emotional topic, especially during a stressful job search. Our aim is not to be rigid, it’s to be clear, fair, and upfront, so there are no surprises on either side.

Founders Reply

Yes, we did, and we’re open about it. We no longer offer this incentive, but like most businesses, we previously encouraged customers who had a positive experience to share it publicly. The important distinction was how we incentivized them. We didn’t offer cash, gift cards, or Amazon coupons. Instead, we offered additional service credits more of the same service they had already purchased. Customers would only opt in if they genuinely found the service useful enough to recommend. Extra credits wouldn’t have appealed to someone who didn’t see value in the service. From our perspective, the program was simply a way to: -Encourage word-of-mouth -Reward engaged customers -Give customers more value in the same form they originally paid for We weren’t trying to manufacture opinions or buy praise. We offered more of our service to customers who independently chose to share a positive experience. Transparency matters to us, which is why we’re open about this past practice rather than trying to disguise it.

Founders Reply

Let’s be very clear about what Scale.jobs does and what it doesn’t. We’re not doing anything magical here. We’re not promising jobs, interviews, or shortcuts. What we do is take the time-consuming, repetitive grunt work of job applications off your plate and give it to a trained human assistant, so you can redirect your time and mental energy toward things that actually move the needle: networking, referrals, interview prep, and skill-building.For many people, that shift alone can improve their odds but it’s not a guarantee. The reality is that the job market over the past few years has become highly volatile and unpredictable, with layoffs, hiring freezes, and constantly changing recruiter behavior across industries and geographies. This environment is very different from when we first started . In markets like this, outcomes such as recruiter responses or interview calls can fluctuate wildly, even when the quality, rigor, and consistency of our execution remain the same or continue to improve. Understandably, frustration with poor outcomes sometimes gets directed toward us, even when those outcomes are driven by forces far beyond our control. Here’s what we don’t control: -Hiring cycles and freezes -Recruiter bandwidth and response behavior -Internal referrals or headcount approvals -ATS filtering rules -Timing, competition, or market sentiment -Your Individual strength of profile for the role -Sponsorship Limitations We don’t have leverage inside companies, and we don’t have a magic wand to tilt decisions in anyone’s favor. Results depend heavily on timing, role availability, and an individual’s background, many variables no ethical service can influence. That said, we do take ownership when we make mistakes, miss context, or fall short of our own standards, and we actively correct course when that happens. What we ask is simple: please don’t use recruiter call volume or job offers as the sole yardstick to judge our effort or effectiveness, especially in an unstable market. Our role is to maximize execution quality, consistency, and coverage within real-world constraints, not to promise outcomes that no honest service can truly guarantee.

Founders Reply

It’s a trap!! Run away. Lower cost doesn’t always mean broader coverage or better outcomes. Most AI auto-apply platforms work only on short, one-page applications, typically on ATS platforms like Greenhouse and Lever. That limitation isn’t always made obvious. What is often omitted is that these platforms cannot apply to longer, more complex systems such as Workday, iCIMS, Taleo, and similar enterprise ATS tools. In practice, this means AI auto-apply tools tend to focus on a small slice of the job market—largely early-stage startups and select tech companies while silently skipping a much larger portion of roles, including many positions at Fortune 500 companies and large organizations. As a result: - You may be excluded from a significant number of legitimate opportunities without realizing it - Applications get concentrated into a narrow pool of roles that everyone using the same tool is applying to - Competition intensifies for that limited subset of jobs, making outcomes even more unpredictable The polished UI and “selected roles” messaging can make this feel intentional or curated, when in reality it’s often driven by technical constraints, not strategy.