SHIFT AI Exposed: I Got Inside Without Paying — The Leaderboard Tells a Very Different Story

“Payouts are on hold while we move to our new payment partner… there is no payout date yet.” — SHIFT AI member dashboard

This is now my fourth investigation into SHIFT AI, and I had no intention of writing another article simply repeating what I had already uncovered.

My first three investigations followed this operation from its pre-launch promises of AI credits and passive income, through the money and marketing behind the opportunity, and eventually into internal SHIFT AI documents that raised even more serious questions about how the business was structured. I examined Marty Hale, EcoPay, the compensation model, the promoters, the AI credit packages, claimed partnerships, patents, revenue projections and the enormous amounts of money being discussed. Each investigation produced more questions, not fewer.

This time, I decided to approach SHIFT AI differently.

Rather than listen to another presentation or analyse another sales pitch, I signed up myself. I went through the same process a prospective participant would experience, selected a Standard Club Membership and received instructions telling me to transfer $498.13 directly to SHIFT Capital, LLC by ACH or bank wire. The payment instructions even explained that the unusual cents were being used to identify and automatically match my payment.

I never sent the money.

What happened next changed the direction of this investigation completely. After resetting my password, I discovered that I could log into the SHIFT AI Suite despite never completing the $498.13 payment. The system itself confirmed that “Your SHIFT membership is not active,” yet I could access areas of the backend, explore the AI tools, examine payout information and, most importantly, reach a leaderboard containing information associated with thousands of SHIFT AI participants.

That gave me something far more valuable than another marketing presentation: SHIFT AI’s own numbers.

I captured the leaderboard data and analysed 2,000 ranked accounts. What emerged deserves considerably more attention than the promises being made from a Zoom stage. More than half of those accounts displayed projected weekly amounts of $1 or less. The median displayed amount was just $0.53. Only a small proportion showed CoachPay specifically identified by SHIFT as “banked” for that week, while an extraordinary proportion of the displayed dollars was concentrated among a relatively tiny number of accounts near the top.

SHIFT’s own dashboard provided another revealing comparison. At the time I captured it, the system displayed 2,765 “Total Club Members” at the $499 club-pack level or above, compared with just 401 “Total Customers” at the $99 membership level. Elsewhere, the dashboard displayed “Last Friday $239,845.47 · 2706 members”, while simultaneously warning participants that payouts were on hold as SHIFT moved to a new payment partner and that there was “no payout date yet.”

Those figures do not, by themselves, prove where every dollar came from or where every dollar went. Nor does appearing on a SHIFT AI leaderboard mean somebody has done anything wrong. Many of the people whose names I found may simply be ordinary participants who believed the claims, bought a package and expected SHIFT AI to deliver what had been promoted to them.

But the numbers give us something we did not have before.

For three investigations I had been looking at SHIFT AI largely from the outside. This time, I was looking at the opportunity through its own backend — and what I found there tells a very different story about who appears to be making money, how much most participants are actually being shown, how heavily the displayed money is concentrated at the top, and what SHIFT AI itself distinguishes as projected versus banked earnings.

So that is where this fourth investigation begins.

Inside SHIFT AI Without Paying

My latest investigation started with a simple objective: follow the signup process exactly as a prospective SHIFT AI member would and find out where the money was actually going. I registered using my own details and selected the Standard Club Membership. SHIFT AI then instructed me to send $498.13 by ACH or bank wire to SHIFT Capital, LLC, with the payment going to an account at Choice Financial Group. I was given a unique payment reference, and the instructions explained that the exact cents were deliberately assigned so the system could automatically match the incoming transfer to my reservation.

The instructions were surprisingly specific. Once the money arrived, SHIFT told me my Standard Club Membership would be activated, 100,000 credits would be placed into the SHIFT AI Suite, my EcoPay attribution and commission streams would activate, and I would receive access to the system. In other words, payment appeared to be the event that was supposed to turn my reservation into an active membership.

There was just one problem.

I never paid the $498.13.

I deliberately stopped before making the bank transfer. Later, I used SHIFT AI’s password-reset process and created a password for the account. During my testing, the system accepted an eight-character numeric password without requiring me to enter it a second time for confirmation. That does not, by itself, establish that SHIFT AI’s entire authentication system is insecure, but it certainly wasn’t the account-creation experience I expected from a company handling membership payments, commissions, banking details and potentially sensitive participant information.

More importantly, once the password was created, I was inside.

The contradiction was visible on SHIFT AI’s own screen. A banner across the member area told me: “Your SHIFT membership is not active.” It also encouraged me to “START MEMBERSHIP.” Yet underneath that warning, substantial portions of the SHIFT AI Suite remained accessible. I could navigate through the backend and see the collection of AI products SHIFT was presenting as live: Chat, Image, Voice, Avatar, Translate, Video & Reel Maker, Deck, Prospect, Music and Brand Pack.

The interface even showed the internal credit pricing attached to some of those tools. Chat was displayed at 35 credits per message, Image at 108 credits or more per image, and Prospect at 90 credits per pack. My account showed zero credits, but the product interface itself remained visible.

That created an obvious question. If I had not paid for the $499 Club package, why was an inactive account being given this level of access to the member environment?

The payout area raised further questions. My account correctly showed $0.00 awaiting payout and $0.00 paid to my bank, but I could still reach the EcoPay settlement area and the process for establishing a payout account. The system explained that setting up payouts required a bank account and tax ID and warned that people whose countries were unsupported would not be able to withdraw earnings. At the same time, another message stated that payouts were being moved to a new payment partner and there was currently “No date yet” for the next payout.

SHIFT went further, telling members: “Your earnings are recorded and safe.”

How that assurance can presently be independently verified is another matter. The backend stated that payouts were on hold, that there was no payout date and that SHIFT would email members when payouts restarted. This was no longer something being alleged by a critic or discussed by somebody on social media. I was reading it directly inside SHIFT AI’s own system.

Then something happened while I was demonstrating all of this during a livestream. My original access stopped working. SHIFT AI representatives were aware of my investigation and, from the circumstances, I suspected my account may have been disabled while I was showing viewers what I could see. I cannot independently prove from the evidence available to me who disabled the access or why, so I am not going to present that suspicion as an established fact.

Instead, I tested the process again.

Using another account I was authorised to access, this time through my mobile phone and a VPN, I repeated the password-reset process. Again, I was able to establish access and capture the remaining screenshots I needed. I did not attempt to break into anybody else’s account, circumvent another person’s password or obtain information by exploiting someone else’s credentials. I was documenting what SHIFT AI made available through accounts I was entitled to use.

And that is when this investigation became considerably more serious.

Inside the system was a leaderboard. It didn’t merely show anonymous rankings or usernames. It displayed names associated with SHIFT AI participants alongside membership tiers and dollar amounts. The dashboard around it also showed broader figures including 2,765 Total Club Members, described as people at the “$499 club pack or above”, and 401 Total Customers, described as the “$99 membership.”

I had gone into the system trying to understand how SHIFT AI collected a $499 payment.

I came out with a dataset showing what 2,000 ranked SHIFT AI accounts were actually being shown as earning.

SHIFT AI’s Own Leaderboard Tells The Story

Finding the leaderboard changed this investigation. Until this point, much of my work on SHIFT AI had involved examining what Marty Hale and his promoters said would happen. Now I had data generated by the system itself showing what was happening across 2,000 ranked accounts.

Before looking at the numbers, there is an important qualification. SHIFT AI describes this leaderboard as “mostly a projection.” According to the explanation displayed with it, each row combines the member’s banked CoachPay for the current week — which SHIFT describes as “real, settled money” — with projected ClubPay and, where applicable, projected CreditPay and CompetePay. SHIFT warns that those projected amounts can change, including moving down, before the weekly close.

That distinction matters because a large number displayed beside someone’s name should not automatically be described as money they have actually received.

I analysed all 2,000 ranked accounts captured from the leaderboard. The first number that jumped out at me was how few showed any CoachPay explicitly identified as banked for that week. Only 44 accounts — 2.2% of the 2,000 — showed banked CoachPay. The remaining 1,956 accounts, or 97.8%, showed none.

That does not mean I can claim 97.8% of SHIFT AI members have never made any money. The leaderboard is a snapshot, and somebody could have received money previously or earned through something not represented by that week’s banked CoachPay. What I can say is much more precise: 97.8% of the 2,000 accounts in the dataset showed no CoachPay identified by SHIFT as banked for that week.

The amounts displayed for the typical account were equally revealing.

Across all 2,000 accounts, the median projected weekly total was just $0.53. In other words, half of the accounts were displaying 53 cents or less. 1,068 accounts — 53.4% — showed $1 or less. 1,466 — 73.3% — showed $2 or less. 1,705 — 85.25% — showed less than $5.

By the time I reached $100, the picture was unmistakable. 1,938 of the 2,000 accounts — 96.9% — displayed less than $100. Only 62 accounts, representing 3.1% of the dataset, displayed $100 or more.

And again, these weren’t necessarily amounts sitting in people’s bank accounts. Much of what I was looking at consisted of SHIFT’s own projected components.

The combined projected weekly total across the 2,000 accounts was approximately $40,542.51. The CoachPay amounts specifically identified as banked totalled approximately $14,266.40. The difference — roughly $26,276 — was therefore not identified in this dataset as banked CoachPay and instead came from the projected components described by SHIFT.

But the most revealing statistic wasn’t how little appeared at the bottom.

It was how much was concentrated at the top.

The top 10 accounts accounted for approximately half of every dollar displayed across all 2,000 accounts. The top 20 accounted for about 62.8%. By the time I reached the top 50, they represented approximately 81.7%.

Then came the number that, for me, put the entire leaderboard into perspective: the top 100 accounts — just 5% of the dataset — accounted for approximately 89% of all the projected weekly dollars displayed.

That left the other 1,900 accounts sharing approximately 11%.

This is why averages can be so misleading when discussing an income opportunity. The average displayed amount across the dataset was around $20.27, but that number bears little resemblance to what the typical person was actually seeing. The median was 53 cents because a comparatively small group at the top was pulling the average upwards.

The membership tiers reveal another layer. Of the 2,000 accounts I analysed, 1,078 were Standard, 695 Bronze, 205 Silver and just 22 Gold. Those 22 Gold accounts represented only 1.1% of the dataset, yet together they accounted for approximately $16,558.68 — around 41% of all the projected weekly dollars displayed.

Meanwhile, the 1,078 Standard accounts — more than half of everybody in the dataset — collectively displayed approximately $1,949.02.

That is the sort of statistic prospective participants deserve to see before deciding whether an opportunity represents a realistic way of making money.

There was another number sitting above the leaderboard that made this even more interesting. SHIFT’s dashboard showed 2,765 “Total Club Members”, described as people with a “$499 club pack or above,” compared with only 401 “Total Customers”, described as having a “$99 membership.”

Based purely on SHIFT’s displayed categories, that’s roughly 6.9 Club Members for every Customer — approximately 87% Club Members compared with 13% Customers across those two displayed totals.

I am deliberately not calling those 401 people “retail customers,” because the dashboard does not provide enough information to establish precisely how SHIFT defines that category. But the distinction SHIFT itself chose to display deserves scrutiny. If this is primarily an AI product business driven by genuine consumer demand, why does its own dashboard show nearly seven people buying $499-or-higher Club packages for every person classified as a $99 Customer?

The same dashboard displayed another eye-catching figure:

“LAST FRIDAY $239,845.47 · 2706 members.”

I have not seen evidence establishing that $239,845.47 was actually deposited into 2,706 members’ bank accounts. Given that SHIFT’s own system distinguishes between projections, accumulated amounts, awaiting payout and money “paid to your bank,” it would be irresponsible to treat that figure as confirmed cash payouts without supporting records.

That distinction has become even more important because the same dashboard now tells participants “payouts on hold, no date yet.”

So instead of asking whether somebody near the top of a promotional leaderboard can make money, I think the more useful question is what happens to everybody else.

SHIFT AI’s own dataset gives us a remarkably clear snapshot: half of the 2,000 ranked accounts displayed 53 cents or less, more than 96% displayed under $100, and just 5% of the accounts accounted for approximately 89% of all the projected weekly dollars shown.

Those aren’t numbers supplied by a critic of SHIFT AI.

They came from inside SHIFT AI itself.

Follow The Credits, Follow The Money

The leaderboard showed me how unevenly SHIFT AI’s displayed earnings were distributed. The next question was whether the AI credits themselves supported the story being told about this supposedly revolutionary AI economy. This matters because SHIFT has repeatedly positioned credits and its AI Suite as the product sitting underneath the opportunity. If genuine use of those products is driving the business, there should be meaningful consumption of the enormous number of credits being distributed with paid memberships.

This is where Oz at BehindMLM did some simple mathematics that I think deserves attention. In his September investigation into SHIFT AI’s payment-processing problems, he reported Marty Hale claiming that SHIFT had taken approximately $6.66 million across 2,613 accounts, including around $5 million during the week before Stripe terminated SHIFT AI’s payment processing. BehindMLM also reported Hale highlighting the fact that users had consumed more than 16 million credits as evidence that people were actually using the product.

On its own, 16 million credits sounds impressive.

Put it against the number of credits SHIFT was distributing, however, and it looks considerably different.

BehindMLM calculated the numbers using SHIFT’s lower packages: 20,000 credits with $99, 100,000 credits with $499 and 200,000 credits with $1,000. At those levels, the packages work out at roughly 202 bundled credits for every dollar spent. Applying that approximate ratio to $6.6 million produces an estimated 1.345 billion bundled credits.

Against that estimate, the reported 16,974,507 credits used represented approximately 1.26% of the credits potentially distributed since launch.

I want to be very clear about what that calculation does and does not establish. SHIFT AI has not, as far as I have seen, published an audited statement saying exactly 1.345 billion credits were issued. BehindMLM derived that estimate by scaling SHIFT’s lower-tier credit allocations against the reported $6.6 million collected. Different package mixes could alter the exact number.

But the calculation raises an important question that SHIFT should be able to answer with actual data: how many credits have been issued, how many have been consumed by genuine users, and what percentage of the money coming into SHIFT is really being driven by demand for AI services?

That question becomes harder to ignore when compared with what I found inside the backend. SHIFT’s own dashboard showed 2,765 Club Members at the $499 package level or above, but only 401 people classified as $99 Customers. Its leaderboard showed money overwhelmingly concentrated among a small percentage of ranked accounts. At the same time, the AI tools I could see were consuming credits in relatively small increments — Chat displayed 35 credits per message, Image 108 credits or more per image, and Prospect 90 credits per pack.

There is another contradiction worth remembering. BehindMLM documented Hale telling prospective participants that they did not need to recruit anyone and did not even need to log in; according to Hale, simply becoming a Club Member meant they would get paid. BehindMLM also documented a demonstration in which Hale described somebody who wasn’t interested in recruiting or even using the product but simply wanted to see whether they could make money.

That marketing matters when evaluating the purpose of the credits.

If people are primarily paying hundreds, thousands or substantially more because they genuinely want to consume AI services, then credit usage should eventually provide evidence of that demand. If enormous quantities of credits are being bundled into packages but only a small proportion are actually being consumed, while the marketing simultaneously emphasises getting paid, revenue sharing and multiple compensation streams, then the credits begin to look less like the economic engine of the business and more like something bundled around the income opportunity.

The current signup language makes this even more interesting. BehindMLM reported that SHIFT subsequently introduced a declaration telling purchasers that the credits “are not an investment and are not purchased to generate revenue,” while also requiring bundled credits to be used within six months.

A disclaimer does not answer the underlying economic question.

What are people actually paying for?

That is the question I keep coming back to. Not what SHIFT calls the transaction. Not what somebody ticks in a checkbox. Not how many billions of credits can theoretically be created inside a database. The meaningful question is whether substantial independent demand exists for these AI services without the attached promise or expectation of earning money.

SHIFT has the records capable of answering that question. It knows exactly how many credits it has issued, how many have been used, how many customers are buying credits purely to consume AI services, how much revenue those customers generate, and how much money is instead coming from people purchasing Club packages that qualify them for the compensation system.

Until those numbers are independently demonstrated, pointing to millions of consumed credits doesn’t tell us very much.

The more useful number is the percentage being consumed compared with the enormous quantity being sold or bundled — and BehindMLM’s estimate puts that figure at approximately 1.26%.

I Took The Evidence Outside SHIFT AI

There comes a point in an investigation where collecting more screenshots and asking more questions is not enough. If I uncover information that I believe deserves independent scrutiny, I believe the responsible thing to do is put the underlying evidence in front of organisations that are actually in a position to examine it.

On 1 October 2026, I did that twice.

The first notification concerned Marty Hale and his current business activities involving SHIFT AI / SHIFT Capital. I had obtained court documents showing that Hale entered a guilty plea in Burnet County, Texas, relating to Invasive Visual Recording, with the plea paperwork appearing to provide for three years of deferred adjudication/community supervision. I subsequently obtained contact details for a person I was informed may be Hale’s probation or community-supervision officer.

I contacted that person and copied her supervisor.

I was deliberately careful about what I alleged. I did not tell the department that Hale had breached his supervision. I don’t know that, and determining whether his current activities have any relevance to his supervision conditions is not my job. My letter explicitly stated: “I am not contacting you to make assumptions about whether Mr Hale has breached any condition of his supervision.”

Instead, I provided information about what I had actually documented.

That included the sale of substantial packages of proprietary AI credits, recruitment and compensation structures involving uplines and downlines, internal documents describing SHIFT as a “network-marketer-facing ecosystem,” documents discussing substantial markups on AI/API credits, significant sums being solicited for packages, passive-income and compensation representations, cryptocurrency and alternative payment arrangements, and SHIFT’s attempts to establish alternative payment processing after Stripe terminated its relationship with SHIFT Capital.

I offered to provide the underlying court records, SHIFT internal documents, recordings, payment information and presentations so that the appropriate authority could make its own determination about whether any of this was relevant to Hale’s supervision conditions.

Then I followed the money.

During my own SHIFT AI signup, I had been instructed to transfer $498.13 directly to SHIFT Capital, LLC. The payment instructions identified Choice Financial Group as the bank and provided a routing number, account number and SWIFT/BIC code. SHIFT also assigned me an individual wire reference and explained that the unusual cents in the payment amount were intentional because “the cents identify your payment so we can match it to you automatically.”

The most important part came next. SHIFT told me that once the payment arrived:

“100,000 credits land in the SHIFT AI Suite, your EcoPay attribution and commission streams activate.”

Remember, this was after SHIFT Capital’s previous payment-processing relationship with Stripe had been terminated. SHIFT was now instructing me to bypass card processing entirely and send the money directly by ACH or bank wire.

So I sent a notification to Mercury and Choice Financial Group, asking that the information be forwarded to their Fraud, AML/BSA or Compliance teams.

Again, I was careful about what I was alleging. I specifically told them that I was not accusing Mercury or Choice Financial Group of doing anything improper, nor was I asking them to disclose confidential information about SHIFT Capital’s account. I was providing evidence and asking their compliance professionals to independently review the customer and activity associated with the account.

I asked them to examine the nature and volume of incoming ACH and wire payments, the systematic use of unusual cent amounts to reconcile participant purchases, the representations being made to people sending money, the relationship between purchases, AI credits and EcoPay commission streams, and whether the activity was consistent with the business activity disclosed when the account was established.

I also offered them the original payment instructions, screenshots of SHIFT’s checkout process, marketing material, internal company documents, recordings and my published investigation.

I don’t control what either organisation does with that information.

The supervising authority may conclude that none of SHIFT AI’s activities have any relevance whatsoever to Hale’s supervision. The financial institutions may review SHIFT Capital’s activity and decide that it complies with their requirements. They may also be prevented by confidentiality obligations from ever telling me what they find.

That isn’t the point.

My job is to document what I can establish, preserve the evidence and put relevant information before people who have powers that I do not.

I cannot inspect SHIFT Capital’s bank records. I cannot determine whether particular transactions trigger AML monitoring. I cannot determine whether Marty Hale has complied with every condition of his community supervision.

But the bank can examine its own customer activity, and the appropriate supervising authority can examine its own conditions.

After four investigations into SHIFT AI, I have now reached the stage where the evidence is no longer sitting only on my website, my YouTube channel or my hard drive. It has been placed before third parties capable of independently examining parts of this operation that I cannot.

What SHIFT AI’s Own Numbers Now Show

At this point, I don’t need another Zoom presentation telling me what SHIFT AI is supposed to become. I have looked at its payment instructions, entered its backend, examined its AI Suite, captured its membership statistics and analysed 2,000 accounts from its own leaderboard.

When those pieces are put together, the picture becomes much harder to reconcile with the story of an ordinary AI product business.

Start with the customer numbers. At the time I captured the dashboard, SHIFT displayed 2,765 Total Club Members, described as having the “$499 club pack or above,” compared with just 401 Total Customers on the “$99 membership.” That is nearly seven higher-priced Club Members for every person SHIFT categorised as a Customer.

Then look at the leaderboard. Of the 2,000 ranked accounts I analysed, 1,068 displayed $1 or less for the week. 1,705 displayed less than $5. Only 62 displayed $100 or more. The median was just 53 cents.

Meanwhile, the money shown on the leaderboard was extraordinarily concentrated. The top 5% of accounts accounted for approximately 89% of all the projected weekly dollars displayed. The 22 Gold accounts alone represented around 41% of the entire displayed total.

And most importantly, SHIFT itself warns that much of what people see on that leaderboard isn’t settled money at all.

Its explanation says the leaderboard is “mostly a projection.” Of the approximately $40,542.51 displayed across the 2,000 accounts, only approximately $14,266.40 was CoachPay explicitly identified by SHIFT as banked for that week. Just 44 of the 2,000 accounts showed any of that banked CoachPay.

Now add the credits.

SHIFT has bundled enormous quantities of AI credits with its packages. BehindMLM’s calculation, based on the reported millions of dollars collected and the credit allocations attached to the lower packages, estimated that around 1.345 billion credits could have been distributed at that approximate rate. Against that estimate, the reported 16,974,507 credits consumed represented only about 1.26%.

No single one of these statistics proves what SHIFT AI ultimately is. Together, however, they create questions that cannot be answered by another marketing presentation.

Where is the substantial customer base purchasing AI services independently of the compensation opportunity?

Why are there so many more $499-or-higher Club Members than people SHIFT itself categorises as $99 Customers?

Why is the typical amount displayed on the leaderboard so tiny while such a large proportion of the displayed money is concentrated among a relatively small number of accounts at the top?

How much of the money displayed by SHIFT has actually reached participants’ bank accounts?

How many credits have really been issued, and what percentage have actually been consumed?

And if the AI products are compelling enough to sustain the business themselves, what happens to sales when the compensation opportunity is removed from the equation?

There is now another problem hanging over all of those questions: payouts are on hold.

SHIFT’s backend doesn’t give participants a date. It says the company is moving to a new payment partner, that earnings are recorded and “safe,” and that members will be emailed when payouts restart. Its payout history page similarly states “No payouts yet” for my account and repeats that there is currently no payout date.

SHIFT also displayed “LAST FRIDAY $239,845.47 · 2706 members.” I would like to see evidence explaining precisely what that number represents. If $239,845.47 was actually paid into participants’ external bank accounts, that should be straightforward to substantiate. If it represents internal allocations, projected amounts or balances recorded inside SHIFT’s system, it should not be confused with money participants actually received.

There is a very simple way for SHIFT AI to address much of my reporting: publish verifiable numbers.

Show the total money collected from Club Members separately from ordinary customers. Show standalone retail purchases from people who have no participation in EcoPay. Show the total number of credits issued and consumed. Show the amount of commissions actually settled externally to members. Show what proportion of compensation is funded by genuine external product consumption rather than money associated with people entering the Club structure.

These are not unreasonable demands for a company presenting itself as a major new AI economy.

The People Appearing In The SHIFT AI Data

For transparency, I am also publishing the names associated with the leaderboard data I obtained. A person’s appearance in this data does not mean I am accusing that person of fraud, promoting SHIFT AI, recruiting anybody, receiving commissions or even knowing how the wider business operates. Some may simply be customers or participants who purchased something after believing SHIFT AI’s marketing.

The purpose of publishing the list is to document the dataset behind this investigation and establish who appeared in the SHIFT AI leaderboard at the time it was captured.

Atrum Custodia Holdings, Captain Shift, Restore Greatness, Aqua Blue Ocean, 3md, AZ, CynthiaTran, Shift AI Alliance, TSC, Ai Mark, RSB 2002, Dale, A Wise 1, Nolehp, Planet Millionaire, X Force, Irish Dude, CGIS, Wealth Solution Services LLC, HConsulting, AIShift Top Team, Angie Rash, msritateam, PJPJ Smellie, Tyler Koehn, Unleash Your AI Genius, lookwithin, Coach Dorian, Nic Eileen, Sandy Drew, BIQ, krusso, XR77 Girl, T-Bone, Angel, WM 22, Mineral Man, Farhan Rehman, WealthIsFreedom, SamuelFRobinson, Garco, EAB ENTERPRISE, JeannyR, BLWE INC, Team Aloha, Silvia Go AI, Magero, Hartbeat International LLC, 4HISLUV, Mona Lisa, Chris Nolasco, Will Kolodziej, New Wall St Movement, EarnDailyFast, ARK, Maxx1000, WinningwithChar, AI Club, SuiteAI, WMG2018, Leslie’s Zone, Mike Healy, New Concepts, Ryan Utah, Nate B, cryptoresiduals, Cuzin Freddie, S&P 100, SC Trojans, GMC Denali, WealthBuilder, DGRAHAM, Grocery Money $$$, Talawn Unger Jackson, TC, Tarheel23, JM Blackwell, Sergeant Major, Chris OBanion, Hey Ed!, coachvan, 4everprofits, Elizabeth AI, Apagz, Amy Lee, Jewels Charlton, FitMe, Cisco, ThePerfectWealth.com, Dr. Hank, Kevin Cochran, DR. K, viplorip, Morpheus AI, RM, Graham Frame, PrettiFly, HelloNeka, misfits4jesus, Barbarianai, Cheri Witzig, Christina Orcutt, cryptogiver, Ambassador T, Coachjjmoney, MrCPMD, D.O.G (DEPEND ON GOD), webpros, Kevin Wilkes, G Wealth, MoneyPlusTime, xoxo, Surplus AI, Marty W, Bill Ormesher, Showtyme, TroyRose, Premier – AI Group, RancherAI, MacDA, MakeThisAI, David Miller, Georgia White, JB3, coremax, Mariah Jade, Janice Godwin, Jess K, PHIL, NoKaOi, Tia LaPiana, freeatlast, degerro, Chillin, The Professor, WeShare Projects, Dave, ivy brooks, Bitcoinizzy, ceewayy, Royal Stewardship Holdings, gmoney52, Lear 25, D L Beene, Godspeed, Mark G, Limitless, Two Doves, Purple Knight, Brandi K, Dwhit82, Tracy Davison, MRT, Beachmon, Rterm411, jjdreamteam, pdf, PraiseGuitar, Great Endeavors, Optimus, hunter_jbh2, Native, Bingaman, JKF, Mega, Tiffany Blue, CMoney, Swiss Miss, Happyface, Kennedy, Cretech, Pinay82, Thax Daggs, Nexlevel, Cash Flow Tx, DomMocha, AnointedJoy, Patricia59, BigManPhx32316, 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This list also creates an opportunity for people involved with SHIFT AI to contact me. If you appear here and believe the information associated with your account provides important context, I want to hear from you. In particular, I am interested in documentary evidence showing what you paid, what package you purchased, whether you recruited anybody, how many AI credits you have actually consumed, what commissions SHIFT recorded for you and — most importantly — how much money has actually arrived in your bank account.

I am equally interested in hearing from people who joined purely because they wanted to use the AI products and had no interest whatsoever in the compensation opportunity.

Because after four investigations, hundreds of pages of material, SHIFT’s own internal documents and now data obtained directly from its backend, verification is what matters most.

Not another projection.

Not another leaderboard.

Not another promise about what happens next Friday.

Show the money that actually left SHIFT AI and reached the people being told this opportunity would pay them.

The Questions SHIFT AI Still Has To Answer

After four investigations, I have reached the point where I believe SHIFT AI should stop answering legitimate questions with marketing language and start producing independently verifiable evidence.

I have listened to the presentations. I have watched the Zoom meetings. I have examined the compensation structure, the AI credits, the internal documents and the financial claims. I have challenged Marty Hale directly. I have now registered for the opportunity myself, followed the payment process, accessed the backend without completing my $498.13 payment and analysed data associated with 2,000 ranked accounts.

The questions have become remarkably simple.

How much money has SHIFT AI actually collected? Not projected revenue, reservations, package values or internal balances. How much money has actually been received by SHIFT Capital, LLC and any other entity collecting funds on its behalf?

How much has actually been paid to participants? SHIFT’s dashboard can display hundreds of thousands of dollars, but I want to know how much money has left SHIFT-controlled accounts and arrived in participants’ external bank accounts.

Where does the money used to pay members come from? What proportion comes from genuine customers purchasing and consuming AI services without participating in EcoPay, and what proportion originates from Club Members purchasing $499-or-higher packages?

Why does SHIFT’s own dashboard show 2,765 Club Members at $499 or above but only 401 people categorised as $99 Customers? If SHIFT believes those categories demonstrate healthy independent product demand, publish the underlying numbers and explain them.

How many AI credits have actually been issued and how many have been consumed? BehindMLM’s calculation estimated credit utilisation at approximately 1.26% based on the package allocations and figures being publicly discussed. SHIFT possesses the exact numbers. Publish them.

Why are the displayed earnings so heavily concentrated at the top? In the 2,000-account leaderboard dataset I analysed, the top 5% accounted for approximately 89% of all projected weekly dollars displayed, while more than half of the accounts showed $1 or less.

Why did only 44 of those 2,000 accounts show CoachPay specifically identified as banked for that week? If other money has been settled and paid externally, provide the figures necessary to distinguish projections, internal balances, banked commissions and actual withdrawals.

What exactly does “LAST FRIDAY $239,845.47 · 2706 members” mean? Was $239,845.47 deposited into members’ bank accounts? Was it allocated internally? Was it projected? Was it earned but unpaid? This should require a straightforward answer.

And perhaps most urgently: when will participants actually be able to withdraw their money again?

At the time of my investigation, SHIFT’s own backend stated that payouts were on hold while it moved to a new payment partner. It told members there was “no payout date yet” while assuring them that their earnings were “recorded and safe.”

If SHIFT wants people to accept that assurance, verification should not be difficult.

Show the payment processor. Show the settlement records. Show aggregate external payouts. Show the retail revenue. Show credit consumption. Show where the money comes from and where it goes.

I will happily examine credible evidence from SHIFT AI, Marty Hale, its management, its promoters or its members, and where evidence establishes that something I have reported is wrong, I will correct it. That is how an investigation is supposed to work.

But credibility cannot be manufactured by putting impressive numbers on a dashboard.

The most important discovery in this fourth investigation wasn’t that I managed to get inside SHIFT AI without paying. It wasn’t even finding the leaderboard.

It was discovering how different the picture becomes when you stop looking at the opportunity through the presentations and start looking at SHIFT AI’s own numbers.

Thousands of higher-priced Club Members. Hundreds classified as Customers. A median displayed weekly amount of 53 cents across the 2,000 ranked accounts analysed. Almost 89% of the displayed weekly dollars concentrated among the top 5%. Most leaderboard amounts described by SHIFT itself as projections. Payouts currently on hold with no date given for their return.

Those are the figures prospective participants should examine before handing over $499, $1,000 or substantially more.

Don’t show me another opportunity presentation. Show me independently verifiable evidence that the underlying business works without people continually buying their way into the opportunity.

Until SHIFT AI can do that, the questions raised throughout my four investigations remain unanswered.

Disclaimer: How This Investigation Was Conducted

This investigation relies entirely on OSINT — Open Source Intelligence — meaning every claim made here is based on publicly available records, archived web pages, corporate filings, domain data, social media activity, and open blockchain transactions. No private data, hacking, or unlawful access methods were used. OSINT is a powerful and ethical tool for exposing scams without violating privacy laws or overstepping legal boundaries.

About the Author

I’m DANNY DE HEK, a New Zealand–based YouTuber, investigative journalist, and OSINT researcher. I name and shame individuals promoting or marketing fraudulent schemes through my YOUTUBE CHANNEL. Every video I produce exposes the people behind scams, Ponzi schemes, and MLM frauds — holding them accountable in public.

My PODCAST is an extension of that work. It’s distributed across 18 major platforms — including Apple Podcasts, Spotify, Amazon Music, YouTube, and iHeartRadio — so when scammers try to hide, my content follows them everywhere. If you prefer listening to my investigations instead of watching, you’ll find them on every major podcast service.

You can BOOK ME for private consultations or SPEAKING ENGAGEMENTS, where I share first-hand experience from years of exposing large-scale fraud and helping victims recover.

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My work exposing crypto fraud has been featured in:

• Coffeezilla 2026): Featured in the investigation exposing the alleged $328M Goliath Ventures Ponzi scheme
• Bloomberg Documentary (2025): A 20-minute exposé on Ponzi schemes and crypto card fraud
• News.com.au (2025): Profiled as one of the leading scam-busters in Australasia
• OpIndia (2025): Cited for uncovering Pakistani software houses linked to drug trafficking, visa scams, and global financial fraud
• The Press / Stuff.co.nz (2023): Successfully defeated $3.85M gag lawsuit; court ruled it was a vexatious attempt to silence whistleblowing
• The Guardian Australia (2023): National warning on crypto MLMs affecting Aussie families
• ABC News Australia (2023): Investigation into Blockchain Global and its collapse
• The New York Times (2022): A full two-page feature on dismantling HyperVerse and its global network
• Radio New Zealand (2022): “The Kiwi YouTuber Taking Down Crypto Scammers From His Christchurch Home”
• Otago Daily Times (2022): A profile on my investigative work and the impact of crypto fraud in New Zealand