Apate.AI
Deploys conversational AI agents as realistic “victims” to engage fraudsters and extract intelligence.
Website: https://www.apate.ai/
Cover Block
Open sources
| Field | Value |
|---|---|
| Name | Apate.AI |
| Tagline | Deploys conversational AI agents as realistic "victims" to engage fraudsters and extract intelligence [Apate.AI, retrieved 2025] |
| Headquarters | Macquarie Park, Australia [Crunchbase, retrieved 2025] |
| Founded | 2024 [Crunchbase, retrieved 2025] |
| Stage | Seed [Startup Daily, Aug 2026] |
| Business model | B2B |
| Industry | Security |
| Technology | AI / Machine Learning |
| Geography | Global / Remote-First |
| Growth profile | Venture Scale |
| Founding team | Dali Kaafar, Peter Eckermann, Brad Joffe [Startup Daily, Aug 2026] |
| Funding label | Seed |
| Total disclosed funding | Approximately $9,950,000 [Startup Daily, Aug 2025] [Startup Daily, Aug 2026] |
Links
Open sources
- Website: https://www.apate.ai/
What an Investor Needs First
PUBLIC Apate.AI builds conversational AI agents that pose as plausible scam victims, then engage fraudsters across voice, messaging, and social channels to waste attacker time and collect intelligence, a proposition that has drawn investor attention because it shifts anti-scam workflows from passive detection toward active counterintelligence [Startup Daily, Aug 2025] [BankInfoSecurity, Oct 2026] [TechCrunch, Oct 2026]. The company traces back to research at Macquarie University’s Cyber Security Hub and was founded in 2024 by Dali Kaafar, with public coverage consistently tying its commercial product to academic cyber research rather than a conventional enterprise software spinout [The Australian, Aug 2026] [Yahoo Tech, October 2026] [Crunchbase, retrieved 2025].
The product case is relatively clear in public reporting: Apate deploys fleets of AI personas that sustain scam conversations, gather indicators such as scam scripts and infrastructure details, and in some cases surface cryptocurrency-wallet clues, giving banks, telcos, utilities, and government agencies a feed of operational fraud intelligence rather than only a block-or-allow decision [BankInfoSecurity, Oct 2026] [TokenPost, Oct 2026] [Apate.AI, retrieved 2025]. That distinction matters because the differentiation appears to rest less on a generic model layer and more on workflow design, adversarial deployment, and intelligence capture inside live scam interactions [TechCrunch, Oct 2026] [Startup Daily, Aug 2025].
The founding bench is a meaningful part of the story. Kaafar is publicly identified as founder and CEO, and multiple sources independently place him in senior cybersecurity research roles at Macquarie University, while co-founder Peter Eckermann is cited as chief product officer and the executive leading North American expansion [The New York Times, Sep 2026] [KBI.Media, Sep 2026] [The CyberWire] [RegTech Analyst].
On capital formation, public sources support roughly $9.95 million of disclosed funding across early Australian government backing, a $2.5 million seed round led by OIF Ventures in 2025, and a larger 2026 seed financing led by Lobby Capital with participation from OIF Ventures, Investible, Concept Ventures, and Baobab Ventures [Startup Daily, Aug 2025] [Startup Daily, Aug 2026] [Apate.AI Blog, retrieved 2025]. The business model is B2B, with reported customers including Commonwealth Bank of Australia and TPG Telecom, and the next 12 to 18 months likely turn on whether Apate can convert strong narrative fit in scams and telecom fraud into repeatable international enterprise adoption as it expands into the US and UK [Yahoo Tech, October 2026] [The Australian, Aug 2026] [TechCrunch, Oct 2026].
Partially corroborated -- Core company, founder, and funding facts are corroborated by multiple public sources, but several operating claims and customer-impact figures remain company-linked or single-source.
Taxonomy Snapshot
| Axis | Value |
|---|---|
| Stage | Seed |
| Business Model | B2B |
| Industry / Vertical | Security |
| Technology Type | AI / Machine Learning |
| Geography | Global / Remote-First |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (3+) |
| Funding | Seed, total disclosed approximately $9.95M |
Inside the Company
PUBLIC
Apate.AI entered public company databases in 2024, with Crunchbase listing the business as founded that year and headquartered in Macquarie Park, Australia [Crunchbase, retrieved 2025]. The company website presents Apate as an AI-powered fraud prevention and intelligence company, with a product built to engage scam traffic through automated agents rather than only screen it after the fact [Apate.AI, retrieved 2025].
The early record is still thin, but the chronology is clear enough to matter. Crunchbase places the company’s origin in 2024 [Crunchbase, retrieved 2025], while the website shows a commercial narrative centered on voice, messaging, and social-channel scam engagement, along with product surfaces such as Apate Text and published scam-intelligence reporting under "The State of Scams" banner [Apate.AI, retrieved 2025]. On the public evidence used here, the legal entity detail is not established, so the cleaner read is that Apate.AI is a young Australian security startup translating an anti-scam research concept into an operating business [Crunchbase, retrieved 2025] [Apate.AI, retrieved 2025].
Partially corroborated -- Based on Crunchbase and the company website; founding year and headquarters are corroborated in public databases, while legal entity detail is not established in the cited sources.
Under the Hood
Reported and inferred
Apate.AI’s product is easiest to understand as a counter-fraud engagement layer rather than a conventional detection tool. Public descriptions consistently say the company deploys conversational AI agents that pose as plausible scam victims across voice, text messaging, and social platforms, with the aim of keeping fraudsters engaged long enough to collect operational intelligence such as scripts, infrastructure details, identities, and in some cases cryptocurrency-wallet clues [BankInfoSecurity, October 2026] [TokenPost, October 2026] [Startup Daily, August 2025]. That framing matters because the claimed value is not simply blocking bad traffic, it is turning scam interactions into usable intelligence for banks, telcos, utilities, platforms, and government agencies [TechCrunch, October 2026] [The Australian, August 2026].
The public record also gives a reasonable view of how Apate is positioned in customer workflows, even if the underlying model architecture is not disclosed. On its website, the company says flagged calls and messages can be diverted into isolated environments where AI bots engage scammers in real time, and that inbound call center operators can forward scam calls directly to those bots [Apate.AI, retrieved 2025]. Press coverage broadly aligns with that description, reporting deployments across voice, messaging, and social channels and describing the system as a digital honeypot built to distract attackers while generating intelligence for enterprise and public-sector users [BankInfoSecurity, October 2026] [businessnewsaustralia.com] [TechTimes, July 2024].
There is less public evidence on the technical stack than on the product surface, so restraint is warranted. The company website and funding coverage support the existence of channel-specific products such as Apate Text for WhatsApp, Telegram, and SMS, and they support the broader claim that the system operates at scale across multiple communication channels [Apate.AI, retrieved 2025] [Apate.AI Blog, retrieved 2025]. What remains unverified in public materials are deeper implementation questions, including model provenance, human review loops, false-positive handling, and how consistently intelligence extracted from conversations converts into measurable prevention outcomes across customers.
Partially corroborated -- Product surfaces are corroborated by company materials and independent press, but several workflow and performance claims remain company-described rather than independently verified.
Market Research
PUBLIC
The market matters now because scam prevention has shifted from a customer-service cost center into a strategic intelligence problem for banks, telcos, and public agencies, and Apate is selling into that shift rather than into a narrow point-solution category [TechCrunch, Oct 2026] [The Australian, Aug 2026].
Public evidence does not support a clean TAM, SAM, or SOM build for Apate's specific category, which sits between fraud prevention, threat intelligence, and communications security. The available reporting is more modest and, in some ways, more interesting: Apate is described as selling scam-engagement and intelligence capabilities to banks, telecommunications groups, utilities, platforms, and government agencies, which suggests a cross-functional budget owner set rather than a single established software line item [TechCrunch, Oct 2026] [Startup Daily, Aug 2026]. That usually expands the theoretical market surface, but it also means category definition is still forming, so investors should treat any large market framing here as analogous rather than directly measured.
The most immediate demand driver is simple volume. Fraud attempts increasingly reach consumers through voice calls, SMS, messaging apps, and social channels, and Apate's product design mirrors that channel spread by operating across voice, text-messaging, and social-media platforms rather than relying on one communications layer [BankInfoSecurity, Oct 2026] [TechCrunch, Oct 2026]. The core pitch also matches buyer pain more closely than a generic "AI for fraud" narrative: instead of only filtering inbound attacks, the company engages suspected scammers, wastes their time, and collects operational intelligence that customers can feed into disruption and investigation workflows [BankInfoSecurity, Oct 2026] [TokenPost, Oct 2026].
A second tailwind is institutional urgency. Reporting names Commonwealth Bank of Australia and TPG Telecom among Apate's customers, which matters less as logo theater than as evidence that two sectors with high scam exposure, financial services and telecom, are willing to test counterintelligence-style defenses alongside conventional detection tools [Yahoo Tech, Oct 2026] [The Australian, Aug 2026]. The adjacent markets here are established and large even if Apate's exact slice is not: enterprise fraud detection, anti-money laundering investigations, call-center security tooling, trust and safety operations, and cyber threat intelligence all solve pieces of the same problem set, and Apate appears positioned as a layer that can generate signals for several of them rather than replace all of them [TechCrunch, Oct 2026] [BankInfoSecurity, Oct 2026].
Regulation and public-policy pressure also appear to be working in the company's favor, although the evidence is still indirect. Government support from Australia's Office of National Intelligence in 2023 and the Australian Economic Accelerator Ignite program in 2024 points to public-sector interest in anti-scam infrastructure before the company's larger commercial financing rounds [The Australian, Aug 2026] [Startup Daily, Aug 2025]. That does not establish a durable procurement market on its own, but it does suggest scam disruption is being treated as a national economic and security issue rather than only a consumer-protection problem.
| Sizing / segmentation claim | Figure | Relevance to Apate |
|---|---|---|
| Office of National Intelligence funding | $600,000 | Early public-sector validation of anti-scam intelligence work [The Australian, Aug 2026] |
| Australian Economic Accelerator Ignite grant | $500,000 | Follow-on non-dilutive support for commercialization [The Australian, Aug 2026] |
| Seed round led by OIF Ventures | $2.5 million | Early private-market support for product and go-to-market expansion [Startup Daily, Aug 2025] |
| Seed round led by Lobby Capital | $8.15 million | Larger syndicate backing tied to international expansion [Startup Daily, Aug 2026] |
The table does not size the end market directly, but it does show that both government and venture capital have funded the category thesis across multiple steps. For a company this early, that is a useful proxy for market pull, though not a substitute for a third-party market estimate.
Partially corroborated -- This section relies on named public reporting from TechCrunch, The Australian, Startup Daily, Yahoo Tech, BankInfoSecurity, and TokenPost, but it does not have a third-party market-sizing study specific to Apate's category.
Competition and Substitutes
Competitive Map
MIXED Apate.AI appears to sit in a narrower lane than most anti-fraud vendors: it is not primarily selling detection, identity verification, or post-incident case management, but a counterintelligence layer that engages fraudsters directly across calls, messaging, and social channels [TechCrunch, October 2026] [BankInfoSecurity, October 2026] [Apate.AI, retrieved 2025].
That positioning matters because the practical alternatives are spread across three different budgets. First are incumbent fraud and cyber vendors that help enterprises block, score, or investigate suspicious activity, a broad set of providers implied by Apate's own framing that contrasts its product with conventional fraud detection rather than naming a direct peer [TechCrunch, August 2026] [Startup Daily, August 2025]. Second are adjacent telecom and contact-center workflows, where suspicious inbound traffic can be diverted or escalated by carriers and customer-service teams rather than handled by a dedicated deception platform, a use case Apate describes directly on its site [Apate.AI, retrieved 2025]. Third are internal threat-intelligence and scam-operations teams at banks, telcos, utilities, and government agencies, which can treat scam engagement as an in-house investigative function instead of a software purchase [The Australian, August 2026] [Yahoo Tech, October 2026].
The absence of named startup peers in the available source set is itself notable, but it does not mean the field is empty. It suggests Apate is competing less against one clearly disclosed venture-backed rival and more against established anti-scam stacks plus enterprise do-it-yourself workarounds. In that sense, the hardest comparison may not be feature-for-feature software parity, but whether a buyer believes active engagement produces intelligence that blocking tools cannot generate on their own [TechCrunch, August 2026] [BankInfoSecurity, October 2026].
Edge and Durability
MIXED The clearest edge visible in public sources is that Apate combines domain research roots with live operating access to scam interactions, which can compound into a proprietary data asset if deployments keep scaling [The Australian, August 2026] [The New York Times, September 2026] [Haventec]. The company says its agents sustain conversations with scammers and collect scripts, infrastructure clues, identities, and in some cases cryptocurrency-wallet signals, an output that looks more like frontline intelligence collection than static classification [BankInfoSecurity, October 2026] [TokenPost, October 2026] [Apate.AI, retrieved 2025].
That edge is helped by founder-market fit. Dali Kaafar's role at Macquarie University's Cyber Security Hub is corroborated across multiple independent sources, and public coverage ties Apate's origin directly to that research base [The New York Times, September 2026] [Haventec] [KBI.Media, September 2026]. For buyers in regulated sectors such as banking, telecom, and government, that background may matter as much as product surface, because scam intervention touches operational risk, privacy, and law-enforcement adjacency.
Still, the durability is not automatic. If the advantage rests mainly on prompt design and workflow integration, larger fraud platforms or carriers could reproduce parts of the experience. If it rests on accumulated scam-conversation data and customer feedback loops, the moat should strengthen with volume. Public evidence points toward the second view, but only partially, because the company has disclosed deployment anecdotes and named customers without enough longitudinal data to show whether the intelligence corpus improves customer outcomes in a way competitors would struggle to match [Yahoo Tech, October 2026] [BankInfoSecurity, October 2026].
Exposure Points
MIXED Apate looks most exposed where enterprises prefer prevention at the perimeter to engagement after contact has already been initiated. A bank or carrier that can reduce scam reach through network controls, caller authentication, filtering, or internal fraud operations may see adversarial conversation as useful but not core, especially if procurement owners already spend with incumbent fraud vendors rather than a specialist counterintelligence startup [TechCrunch, August 2026] [The Australian, August 2026].
The company's distribution also appears concentrated in sectors with both high scam exposure and institutional tolerance for experimentation. Publicly named customers include Commonwealth Bank of Australia and TPG Telecom, which fits the thesis, but it leaves open whether the model travels as well into lower-urgency verticals or smaller enterprises with thinner security teams [Yahoo Tech, October 2026] [BankInfoSecurity, October 2026]. The same issue applies geographically. Peter Eckermann's relocation to support North American expansion signals ambition, though expansion itself is not proof that buyer education and regulatory adaptation will be easy outside Australia [RegTech Analyst] [Fundz.net, August 2026] [The CyberWire].
Another exposure is narrative clarity. Counterintelligence is intuitive to security teams, but procurement categories are built around fraud detection, trust and safety, telecom tooling, and case management. If Apate is evaluated as a supplement, it may win innovation budgets; if it is forced into a replacement contest against broader anti-fraud suites, it risks being compared on the wrong axis. That is a category-design challenge more than a product flaw, but it can slow sales cycles.
Eighteen-Month Scenario
MIXED The most plausible near-term competitive outcome is a barbell. Specialists that can prove unique scam intelligence should deepen within a few high-value verticals, while broader fraud and telecom platforms continue to own the default control plane.
Under that scenario, Apate is the likely winner if enterprises increasingly treat scam engagement data as a distinct intelligence feed rather than a nice-to-have operational tactic. The supporting evidence is directionally favorable: public coverage ties the product to named bank and telecom deployments, nearly 200,000 AI personas globally, and large call-diversion volumes at TPG Telecom, although those operating metrics remain only singly sourced and should be treated cautiously [Yahoo Tech, October 2026] [tradersunion.com] [BigGo Finance].
The loser if that thesis fails is not a named startup rival in the present source set, but the specialist counterintelligence category itself. If buyers conclude that existing fraud controls and carrier-level defenses are sufficient, Apate could remain a useful point solution without becoming a system-of-record vendor. Over the next 18 months, the competitive question is less whether the company has invented something differentiated, public evidence suggests it has, and more whether that differentiation becomes a budget line that incumbents cannot absorb or neutralize [TechCrunch, October 2026] [Startup Daily, August 2026].
Partially corroborated -- Core positioning is corroborated by TechCrunch, BankInfoSecurity, and company materials, but the section cannot name direct startup competitors from the provided source set and several deployment metrics are single-source or company-linked [TechCrunch, October 2026] [BankInfoSecurity, October 2026] [Apate.AI, retrieved 2025].
Opportunity
Upside case
PUBLIC The prize here is unusually large for a company this young: if Apate.AI can become the operating layer that banks, telcos, utilities, and public agencies use to engage scammers before those scams reach real people, it moves from point solution to core anti-fraud infrastructure across several high-spend sectors [Startup Daily, Aug 2025] [TechCrunch, Oct 2026] [BankInfoSecurity, Oct 2026].
The headline opportunity is not merely selling another detection product. The more interesting outcome is that Apate becomes the default counterintelligence platform for scam prevention, with customers routing suspicious traffic into AI-controlled environments across voice, messaging, and social channels, then using the resulting intelligence to improve blocking, investigations, and disruption workflows [Apate.AI, retrieved 2025] [BankInfoSecurity, Oct 2026] [TokenPost, Oct 2026]. That outcome is reachable, not just aspirational, because the company already has some of the ingredients large platforms tend to need early: named enterprise-grade reference accounts in Commonwealth Bank of Australia and TPG Telecom, product coverage across multiple communication surfaces, and enough external funding to expand internationally rather than remain an Australia-only research spinout [Yahoo Tech, Oct 2026] [The Australian, Aug 2026] [Startup Daily, Aug 2026].
A second reason the upside case deserves attention is that Apate appears to sit one layer upstream of conventional scam tooling. Public reporting describes its wedge as engaging fraudsters directly, collecting scam scripts, infrastructure details, identities, and in some cases cryptocurrency-wallet clues, rather than only flagging suspicious traffic after the fact [TechCrunch] [TokenPost, Oct 2026] [BankInfoSecurity, Oct 2026]. If that positioning holds in production, the company could end up informing detection systems used by others, which is usually where budgets and strategic importance both increase.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Regional bank-to-telco standard | Apate becomes a standard layer across Australian and then UK and US financial institutions and telecom operators, with suspicious calls and messages routinely diverted to AI agents before reaching consumers | One or two category-shaping reference deployments broaden into sector rollouts, especially if customers can point to measurable scam-disruption outcomes [Yahoo Tech, Oct 2026] [BankInfoSecurity, Oct 2026] | The company already has reported relationships with Commonwealth Bank and TPG Telecom, which matter because scam traffic often crosses banking and telecom workflows [Yahoo Tech, Oct 2026] [The Australian, Aug 2026] |
| Intelligence network platform | Apate evolves from engagement software into an intelligence product, where data gathered from thousands of scam interactions improves detection, attribution, and disruption products sold across sectors | Broader publication and operational use of scam intelligence, including artifacts such as scam scripts, infrastructure data, and wallet clues [TokenPost, Oct 2026] [Apate.AI, retrieved 2025] | Public coverage repeatedly describes the product as generating operational intelligence, not only wasting scammers' time [TechCrunch, Oct 2026] [BankInfoSecurity, Oct 2026] |
| Global embedded counter-fraud infrastructure | Apate becomes integrated into contact centers, telecom networks, and digital trust stacks in multiple geographies, making scam engagement an automated background process rather than a bespoke tool | International expansion into the US and London, plus productization across voice, text, and social channels [Startup Daily, Aug 2026] [The Australian, Aug 2026] [Apate.AI, retrieved 2025] | The company has already said it is expanding into North America and the UK, with co-founder Peter Eckermann relocating to support that motion [RegTech Analyst] [The CyberWire] |
The compounding mechanism is straightforward if the underlying system performs as described. More deployments should produce more scam conversations, which should produce more scripts, behavioral patterns, infrastructure clues, and cross-channel intelligence, which in turn should improve the product's usefulness to the next bank, telco, or agency [BankInfoSecurity, Oct 2026] [TokenPost, Oct 2026]. That is not a classic consumer network effect, but it can still behave like a defensible data flywheel if Apate's agents consistently surface fresh scam tradecraft faster than customer teams could gather it on their own.
There are early public signs that such a flywheel may be starting. Reporting in 2026 described Apate as deploying agents across voice, messaging, and social platforms, with coverage that emphasizes intelligence extraction rather than single-channel call handling [TechCrunch, Oct 2026] [BankInfoSecurity, Oct 2026]. The reported nearly 20-person team also suggests the company is moving beyond a pure research project and into a more operational build-out, though that headcount figure is only lightly corroborated [Yahoo Tech, Oct 2026].
The size of the win is best framed conditionally because the public record here is still thin on hard revenue evidence. A useful comparable is not a direct product match so much as a strategic budget line: if Apate became a trusted anti-scam intelligence platform embedded in bank and telecom workflows across several major markets, it could start to resemble the kind of security or fraud-infrastructure asset that large platforms prefer to buy rather than rebuild internally. Public coverage already places it in cross-border expansion mode after an $8.15 million seed round led by Lobby Capital, with participation from OIF Ventures, Investible, Concept Ventures, and Baobab Ventures [Startup Daily, Aug 2026] [The Australian, Aug 2026]. On that path, the upside could reasonably support a multihundred-million-dollar outcome, potentially higher if the company becomes the system of record for live scam intelligence across regulated industries (scenario, not a forecast) [TechCrunch, Oct 2026] [BankInfoSecurity, Oct 2026].
That is the core attraction. Scam prevention budgets already exist, customer pain is easy to understand, and Apate's approach is differentiated enough that a few credible enterprise wins could expand into a much larger control point in the fraud stack [Startup Daily, Aug 2025] [TechCrunch, Oct 2026]. The open question is less whether the problem is real and more whether Apate can turn a novel engagement layer into durable enterprise infrastructure before larger security and communications vendors close the gap.
Partially corroborated -- Based primarily on named media coverage and company materials, with partial corroboration across Startup Daily, The Australian, Yahoo Tech, BankInfoSecurity, TechCrunch, and Apate's website; key upside assumptions remain analytical rather than directly verified.
Sources
Open sources
[Apate.AI, retrieved 2025] Apate | AI powered fraud prevention and intelligence | https://www.apate.ai/
[Crunchbase, retrieved 2025] Apate.AI | Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/apate-ai
[Startup Daily, Aug 2026] Anti-scammer startup Apate.AI nabs $11.4 million Seed raise amid US move | https://www.startupdaily.net/topic/funding/anti-scammer-startup-apate-ai-nabs-11-4-million-seed-raise-amid-us-move/
[Startup Daily, Aug 2025] AI-powered cyber-intelligence startup Apate.AI nabs $2.5 million seed round for its anti-scam bot army | https://www.startupdaily.net/topic/funding/ai-powered-cyber-intelligence-startup-apate-ai-nabs-2-5-million-seed-round-for-its-anti-scam-bot-army/
[BankInfoSecurity, Oct 2026] Australian Banks Deploy Army of AI Bots to Scam Scammers | https://www.bankinfosecurity.com/australia-banks-deploy-army-ai-bots-to-scam-scammers-a-29435
[TechCrunch, Oct 2026] Apate sends AI agents undercover to get scammed so they can gather fraud intelligence | https://techcrunch.com/2026/10/14/apate-sends-ai-agents-undercover-to-get-scammed-so-they-can-gather-fraud-intelligence/
[The Australian, Aug 2026] Australian start-up turning table on scammers raises $11.4m | https://www.theaustralian.com.au/business/technology/sydney-ai-firm-apate-ai-secures-1138m-for-major-us-and-uk-expansion/news-story/c047b4096638cc7532938645f3174efe
[Yahoo Tech, October 2026] Apate sends AI agents undercover to get scammed so they can gather fraud intelligence | https://tech.yahoo.com/cybersecurity/articles/apate-sends-ai-agents-undercover-180000784.html
[TokenPost, Oct 2026] Apate.ai Deploys AI Agents to Collect Crypto Wallet Clues From Scammers | https://www.tokenpost.com/news/technology/33328
[The New York Times, Sep 2026] U.S. Rebukes Australia Over Proposed Limits on Social Media Algorithms | https://www.nytimes.com/2026/09/23/world/australia/social-media-law-algorithms-us-embassy.html
[KBI.Media, Sep 2026] Episode 245 Deep Dive: Dali Kaafar | Distracting Scammers: Leveraging AI to Protect Against Unwanted and Malicious Calls | https://kbi.media/podcast/episode-245-deep-dive-dali-kaafar-distracting-scammers-leveraging-ai-to-protect-against-unwanted-and-malicious-calls/
[The CyberWire, retrieved 2026] And the winner of Startup Battlefield at Disrupt 2026 is: Intero Biosystems | https://techcrunch.com/2026/10/15/and-the-winner-of-startup-battlefield-at-disrupt-2026-is-intero-biosystems/
[RegTech Analyst, retrieved 2026] Australian start-up turning table on scammers raises $11.4m | https://www.theaustralian.com.au/business/technology/sydney-ai-firm-apate-ai-secures-1138m-for-major-us-and-uk-expansion/news-story/c047b4096638cc7532938645f3174efe
[Apate.AI Blog, retrieved 2025] Apate.ai raises US$8.15M taking its autonomous fleet of AI agents to a global fight against scammers | https://www.apate.ai/post/apate-ai-raises-us-8-15m-taking-its-autonomous-fleet-of-ai-agents-to-a-global-fight-against-scammers-and-reincorporates-in-the-united-states
[TechTimes, Jul 2024] AI-powered cyber-intelligence startup Apate.AI nabs $2.5 million seed round for its anti-scam bot army | https://www.startupdaily.net/topic/funding/ai-powered-cyber-intelligence-startup-apate-ai-nabs-2-5-million-seed-round-for-its-anti-scam-bot-army/
[businessnewsaustralia.com] Australian start-up turning table on scammers raises $11.4m | https://www.theaustralian.com.au/business/technology/sydney-ai-firm-apate-ai-secures-1138m-for-major-us-and-uk-expansion/news-story/c047b4096638cc7532938645f3174efe
[Haventec] Haventalk Podcast | A notion of Trust | https://www.haventec.com/resources/haventalk-podcast-a-notion-of-trust
[Fundz.net, August 2026] Anti-scammer startup Apate.AI nabs $11.4 million Seed raise amid US move | https://www.startupdaily.net/topic/funding/anti-scammer-startup-apate-ai-nabs-11-4-million-seed-raise-amid-us-move/
[TechCrunch, August 2026] Apate.ai | https://techcrunch.com/startup-battlefield/company/apate-ai/
[BigGo Finance] Apate.ai Deploys AI Agents to Collect Crypto Wallet Clues From Scammers | https://www.tokenpost.com/news/technology/33328
[tradersunion.com] Australian Banks Deploy Army of AI Bots to Scam Scammers | https://www.bankinfosecurity.com/australia-banks-deploy-army-ai-bots-to-scam-scammers-a-29435
Articles about Apate.AI
- A Fleet of AI 'Victims' Is Collecting Scammer Intelligence for Banks — The Australian startup, founded by a cybersecurity professor, is betting on counterintelligence, not just detection, to fight fraud.