All analysis was generated autonomously, without human review. Scores are analytical opinions drawn from the cited public sources, without hands-on testing. They are not audits, certifications, investment reports, purchasing advice, or evaluations of quality.
Banks, government agencies, and enterprises buy Reality Defender's deepfake detection, which catches AI-faked audio, video, images, and text in real time. The customer proof is concrete: JP Morgan, Accenture, Booz Allen Hamilton, US and UK government agencies, and an Orange Business deal embedding detection in telecom services. Reality Defender holds the front-runner position in a market Gartner calls nascent. A nascent category may lack a settled budget owner. Biometric, fraud-prevention, and identity-verification vendors already selling to these buyers could add detection to contracts they hold. Reality Defender is the stronger fit for a buyer that needs real-time detection under its data-residency terms, weaker where a platform the buyer already runs would bundle detection as a feature.
| Description | Reality Defender detects deepfakes and AI-generated media across audio, video, image, and text in real time, protecting enterprises, financial institutions, and governments from synthetic-media fraud and impersonation. | [f1] |
|---|---|---|
| Founded | 2021 | [f2] |
| HQ | New York, New York, United States | [f2] |
| Latest funding | Series A expanded to $33M, Oct 2024, led by Illuminate Financial, with Booz Allen Ventures, IBM Ventures, Accenture | [f2] |
| Product | What it does |
|---|---|
| RealScan | Web-based detection platform with a drag-and-drop interface that analyzes images, video, audio, and documents for AI manipulation in seconds. |
| RealAPI | Developer SDKs and a public API for embedding multimodal deepfake detection into applications, fraud tools, and workflows. |
| RealCall | Real-time voice deepfake detection for contact centers and live calls, scanning speech for synthetic voice and voice-clone impersonation. |
| RealMeeting | Detects AI-generated video and voice in real time inside Zoom and Microsoft Teams meetings, helping enterprises prevent impersonation and fraud. |
Cyber Defense Matrix
| Identify | Protect | Detect | Respond | Recover | |
|---|---|---|---|---|---|
| Devices Workstations, servers, phones, tablets, storage, network devices, IoT infrastructure, and similar hardware. | |||||
| Applications Software, interactions, and application flows on the devices. | |||||
| Networks Connections and traffic flowing among devices and apps, plus communication paths. | |||||
| Data Content at rest, in transit, or in use across devices, apps, and networks. | |||||
| Users The people using the devices, apps, networks, and data. |
RealScan, RealAPI, and RealCall detect AI-generated media, verifying whether a presented voice, face, or artifact is authentic across users, channels (applications), and media data. These lines map to the Cyber Defense Matrix. [f3]
How well the company can compete in its security market, scored across eight dimensions against public evidence.
| Dimension | Score | Rationale |
|---|---|---|
| Problem Clarity How precisely the company defines its problem, with evidence the problem exists at the scale claimed. | 4/5 | A specific buyer persona of banks, enterprises, and governments pairs with independent corroboration of the pain. The US Senate Judiciary Subcommittee held a hearing on AI election deepfakes at which the CEO testified (s14, s15), an academic in-the-wild benchmark catalogs real 2024 deepfakes (s12), and Gartner frames the market as real (s4). [s14, s15, s12, s4, s3] |
| Capability Depth How specific the technical capabilities are, with evidence beyond marketing claims such as docs and third-party validation. | 3/5 | Multimodal detection across audio, video, and image is detailed on the platform page (s7) and in press (s5). An academic in-the-wild benchmark evaluated the company's commercial models among seven detection vendors but anonymized the per-vendor results (s12), corroborating that the category's commercial detectors work without isolating this product's depth, so the score stays present but unproven. [s7, s12, s4, s5] |
| Market Timing Whether the market is ready for this product, with evidence that buyers are actively seeking solutions. | 4/5 | The enabler is the recent leap in generative audio and video, with an in-the-wild benchmark cataloging real 2024 deepfakes from the latest generators (s12), which turned a theoretical risk into live enterprise fraud. Buyer-side signals follow within the last year, a Gartner front-runner note and the Orange Business deal embedding detection into telecom communication services, showing buyers actively adopting solutions. [s4, s6, s12] |
| Team Credibility Demonstrated domain expertise with public signals such as prior exits, publications, and industry recognition. | 4/5 | Recognition is now multiply independent. CEO Ben Colman testified before the US Senate Judiciary Subcommittee on AI election deepfakes (s14, s15), the company won the 2024 RSA Innovation Sandbox (s8), and that record sits on senior Goldman Sachs and Google pedigree (s11). [s14, s15, s8, s11] |
| GTM Proof Evidence of actual traction (customers, revenue signals, partnerships) beyond stated intentions. | 4/5 | Named tier-one customers come from an AWS partner case study (s3), with the Orange Business deal in independent press (s6), independent CB Insights tracking of the company (s13), and a Gartner front-runner mention (s4), strong multiply-sourced traction but without independently reported revenue, scale, or customers testifying in their own voice. [s3, s6, s13, s4] |
| Funding Efficiency Whether funding matches go-to-market ambition, with signs of capital-efficient growth. | 3/5 | The $33 million Series A is proportional to an early enterprise go-to-market stage (s2) with visible shipping in Real Suite and named deals (s5, s6), but no disclosed revenue, margin, or growth figure confirms efficiency, which is the honest default for a funded startup. [s2, s5, s6] |
| Category Clarity Whether the company creates or fits a recognizable category that buyers can quickly place in their stack. | 3/5 | Gartner names deepfake detection a market and the company its front-runner (s4), but Gartner calls the category nascent, a forming space buyers place with analyst help rather than an established budget line. [s4, s5] |
| Incumbent Defensibility How vulnerable the core value proposition is to absorption as a feature by a platform vendor. | 3/5 | There is a partial structural moat. The ensemble-of-models data effect and a regulated-enterprise install base raise the bar, but biometric, fraud, and identity-verification platforms sit adjacent to the same buyers and could add detection, so absorption pressure is real. [s4, s3] |
Reality Defender addresses a problem that has moved from theoretical to operational: AI-generated audio, video, images, and text now defeat the identity and authenticity assumptions that banks, enterprises, and governments rely on. The company frames the gap precisely. Tools for voice authentication, contact centers, identity verification, and video conferencing can check a credential, but none can prove the person behind the voice or face is real.
The pain is corroborated well outside the vendor. The US Senate Judiciary Subcommittee held a hearing on AI election deepfakes at which the company's CEO testified, an academic in-the-wild benchmark catalogs real 2024 deepfakes drawn from dozens of languages and websites, and a December 2025 Gartner note names Reality Defender the front-runner within high-stakes enterprise verticals. Named buyers and the Orange Business contact-center deal show enterprises actively defending against synthetic-voice fraud and executive impersonation, the concrete demand that gives the problem a named buyer and a budget line.
The buyer is well defined. Financial institutions protecting contact centers and high-net-worth clients, enterprises guarding executive communications, and government agencies protecting critical communications and identity channels all map to distinct, reachable personas rather than a diffuse market. [s14, s15, s12, s4, s3, s6]
The product is multimodal real-time detection delivered as a platform. Reality Defender analyzes audio, video, and image for synthetic-media markers, with audio detection targeting voice clones of executives, employees, and customers across calls and meetings. Deployment spans API integration, private cloud, on-premise, and hosted SaaS, which matters for the regulated buyers who require data control.
In late 2025 the company unveiled the Real Suite of enterprise tools. RealScan offers a drag-and-drop web interface for images, video, and audio, RealAPI ships developer SDKs for embedding detection into workflows, RealCall handles real-time voice detection for contact centers, and RealMeeting detects AI-generated video and voice inside Zoom and Microsoft Teams meetings.
Capability claims gain weight from outside sources. An academic in-the-wild benchmark evaluated the company's commercial models among seven detection vendors and found commercial detectors outperform off-the-shelf open-source models while still trailing human forensic analysts. The cited Gartner note describes the underlying ensemble-of-models approach and points to a free public detection API, an architecture statement beyond the company's own marketing. [s7, s12, s4, s5]
Reality Defender positions as the dedicated, multimodal detection layer that feeds a signal into the fraud, call-center, and conferencing tools an enterprise already runs, rather than a replacement for them. With that API-first framing, Reality Defender concedes the surrounding stack and claims the one job those tools do not do, proving whether a voice or face is authentic.
Reality Defender differentiates on breadth and standing. Multimodal coverage across four media types, enterprise deployment options including on-premise, and a Gartner front-runner designation separate it from narrower point tools. The ensemble-of-models design is the claimed technical edge.
The exposure is adjacency. Biometric, identity-verification, and fraud-prevention platforms sell to the same banks and governments and could fold detection into existing contracts, so the competitive question is less about features today than about who reaches the buyer first when the category matures. [s4, s3, s1]
Traction is unusually well evidenced for a company at this stage. An AWS case study names Accenture, Booz Allen Hamilton, tier-one banks including JP Morgan, and US and UK government agencies as customers, and a 2026 deal embeds detection into Orange Business communication services, a channel whose enterprise division serves thousands of customers.
The motion is enterprise and partnership-led. The company sells into regulated verticals through direct enterprise relationships, builds on AWS infrastructure while pursuing AWS Marketplace as a go-to-market path, and offers a public API and SDK for developers embedding detection into their own applications.
Third-party validation reinforces the pipeline. The 2024 RSA Conference Innovation Sandbox win and the December 2025 Gartner front-runner note are recognition that shortens enterprise sales cycles, and CB Insights independently tracks the company and its named investors. These signals come from outside the company rather than its own messaging. [s3, s6, s4, s13]
The founding team pairs financial-sector credibility with a technical co-founder bench. CEO Ben Colman led cybersecurity commercialization at Goldman Sachs and worked with the partnerships team at Google, and the company lists Ali Shahriyari and Gaurav Bharaj as co-founders, a roster that maps to a detection product sold to banks.
The company's origin signals conviction. It began as a non-profit company with a mission-driven core, betting on the deepfake threat years before the market felt it, which gave the team time to refine detection while awareness caught up.
External recognition supports the team's standing. CEO Ben Colman testified before the US Senate Judiciary Subcommittee on AI election deepfakes, and the 2024 RSA Conference Innovation Sandbox win is a further public signal of domain credibility beyond self-description, the kind of validation risk-averse enterprise buyers weigh when evaluating a young vendor. [s11, s8, s14, s15]
Reality Defender publishes an inspectable trust posture rather than a single self-asserted badge. Its trust center lists a SOC 2 Type 2 report dated October 2025, a UK Cyber Essentials 2025 certificate, GDPR and HIPAA alignment, a recent penetration test, and a documented policy library available on request.
Deployment options match regulated-buyer requirements. On-premise and private-cloud options let banks and governments keep media and detection inside their own infrastructure, addressing data-residency and sovereignty constraints that gate enterprise procurement.
The posture is solid table stakes rather than a moat. SOC 2 and Cyber Essentials ease procurement but do not legally mandate the purchase, and no US federal authorization appears in the public record, so trust collateral supports sales without locking out a determined competitor. [s9, s7]
| Company | Relationship | Note | Compare |
|---|---|---|---|
| Pindrop | competes with | Voice-fraud and audio-deepfake detection for contact centers, overlapping Reality Defender's real-time voice line. | |
| Sensity AI | competes with | Multimodal deepfake and AI-generated media detection, a direct pure-play overlap. | N/AWe captured the evidence for these companies under different evidence-model versions (v1 vs v2), so the totals were scored under different conditions and are not directly comparable. |
| Hive | competes with | AI content classification including deepfake and AI-generated media detection via API. | |
| Reken | adjacent | Generative-AI fraud and deepfake defense startup targeting enterprise communication threats. | N/AWe captured the evidence for these companies under different evidence-model versions (v1 vs v2), so the totals were scored under different conditions and are not directly comparable. |
Add analyzed competitors to compare them side by side with Reality Defender.
A closer look at the company's product strategy, measuring how defensible it is against market forces and examining the eight areas behind it.
reinforce or reposition
Reality Defender's engineering is harder for a rival to reproduce than its data. Real-time detection across audio, video, image, and text is years of specialized machine-learning and systems work, the firmest barrier the company has. The data is weaker protection: the public record names no exclusive dataset, a funded entrant with comparable data could rebuild the detection models, and each new generative model can erode accuracy. Banks and governments replace an integrated vendor slowly, and a departing customer must re-plumb detection out of contact-center, fraud, and conferencing workflows. Certifications ease procurement without excluding rivals. Reality Defender holds a head start built on engineering and integration effort, not yet a durable lock.
| Dimension | Score | Rationale |
|---|---|---|
| Value Delivery Does the product sell software as the product, or judgment, trust, or accountability with software as the delivery mechanism. | 1/3 | Customers buy detection software and an API delivered as a product, integrated into their own fraud and communication tools. There is no managed-accountability service layer where Reality Defender accepts liability for verdicts, so software is the product the buyer configures and runs. |
| Switching Cost How expensive leaving is for a customer: data portability, integrations, learned workflows, network effects, regulatory data residency. | 2/3 | Once detection is wired into contact-center, fraud, and conferencing workflows, a buyer must re-plumb integrations and reabsorb the authenticity step to leave, which is meaningful friction in effort rather than a network-effect lock. The Orange Business embedding illustrates the integration depth. |
| Compliance Moat Whether certifications, liability acceptance, or audit trails block an easy replacement. | 1/3 | The trust center publishes SOC 2 Type 2, UK Cyber Essentials, GDPR, and HIPAA alignment, which ease procurement but block nothing, since a determined operator could obtain the same. The cited record identifies no vendor-specific regulatory or insurer mandate, and no US federal authorization appears in the record. |
| Problem Complexity Whether the product requires ML, optimization, real-time systems, or years of specialized expertise. | 3/3 | Real-time multimodal detection of adversarial synthetic media across audio, video, image, and text is hard ML and real-time-systems work requiring years of specialized expertise, and the cited Gartner note on the ensemble-of-models architecture points to depth beyond marketing. |
| Buyer Profile Whether buyers are SMB operators, mid-market IT teams, or regulated enterprises and governments with procurement gates. | 3/3 | The named buyers are regulated enterprises and governments with strict procurement reviews, including tier-one banks such as JP Morgan, Accenture, Booz Allen Hamilton, and US and UK government agencies, where legal and procurement review sit between the vendor and any replacement. |
| Layer Whether the product is an end-user application, a platform with application features, or infrastructure other applications depend on. | 2/3 | The product is an application that feeds a detection signal into many other systems across fraud, call-center, and conferencing channels, broader than a single end-user app but not infrastructure that other applications structurally depend on, so it spans channels without owning the layer beneath them. |
| Proprietary Data, Content, or IP Whether the product accumulates datasets, content licenses, or IP that a rival cannot recreate from scratch. | 1/3 | Detection improves with the diverse synthetic-media datasets the ensemble accumulates, an advantage the cited Gartner note frames as a data network effect, but the public record names no exclusive corpus or production feedback loop a rival could not rebuild, so the asset is replicable with time and comparable data access by a funded entrant. |
Reality Defender targets regulated, high-trust organizations where a single deepfake can cause large financial or reputational loss. The clearest segments are financial services, professional services, telecommunications, and government, each protecting different surfaces: bank contact centers and high-net-worth clients, enterprise executive communications, telecom customer channels, and government agency critical communications and identity channels.
The personas are inferred rather than documented. The cited sources name industries and customers, not buyer roles, so fraud and security teams at banks, enterprise security leaders championing executive protection, and government buyers moving through long acquisition cycles are likely evaluators rather than observed ones. The most recent commercial proof of demand is the Orange Business deal announced in 2026. The Gartner material is analyst validation rather than demand evidence, with a front-runner note dated December 2025 and a June 2026 report naming Reality Defender a Market Shaper in deepfake detection, both of which speak to category position.
The segment focus is disciplined for a company at this stage. Rather than chase consumer or platform-moderation volume, Reality Defender concentrates on enterprise and government buyers whose deal sizes can support a direct sales motion, which is the right match for an expensive, trust-driven sale.
The product detects synthetic and manipulated media across audio, video, image, and text, with audio detection aimed at voice clones of executives, employees, and customers. Detection runs in real time and is delivered through API integration, private cloud, on-premise, and hosted SaaS, giving regulated buyers control over where media and inference live.
The claimed AI advantage is an ensemble of models combined with the data they accumulate. Reality Defender cites a Gartner note describing an ensemble-of-models approach that creates a data network effect by leveraging diverse datasets to continuously improve detection, an analyst framing the company surfaces rather than a vendor self-claim alone. If the synthetic-media attack samples Reality Defender sees across banking, telecom, and government deployments were pooled into shared detection priors that reached every customer's ensemble ahead of a new generator's spread, that cross-customer flywheel would be a real moat, but the public record does not yet evidence such a production feedback loop.
The advantage carries a structural caveat. Detection is an adversarial problem where each new generative model can degrade current accuracy, so the data effect funds a treadmill the company must keep running rather than a one-time moat. The same ensemble breadth that differentiates today is replicable by a well-funded entrant with access to comparable synthetic-media datasets.
Reality Defender runs an enterprise and partnership-led motion. It sells directly into regulated verticals, names customers including Accenture, Booz Allen Hamilton, tier-one banks such as JP Morgan, and US and UK government agencies, and builds on AWS infrastructure while pursuing AWS Marketplace as a go-to-market path.
Channel and developer motions extend the reach. The 2026 Orange Business deal embeds detection into a telecom's communication services, and the Real Suite launch added a public RealAPI and SDK so developers can build detection into their own applications, a lighter-touch entry alongside the enterprise sale.
Third-party recognition shortens cycles. The 2024 RSA Conference Innovation Sandbox win and the December 2025 Gartner front-runner note are external signals that can ease procurement for a young vendor selling to risk-averse buyers, and both come from outside the company.
Public pricing is not disclosed, which fits an enterprise and government motion where deals are negotiated against deployment scope and volume rather than listed. Enterprise plans and controlled deployments use a contact-led sales motion, consistent with custom enterprise contracts, while the developer API is self-service. Reality Defender's home page offers a contact request alongside a free start path, with 50 audio or image scans a month at no charge.
The structure points toward consumption and deployment tiers. Detection charged by volume of media analyzed or calls processed would align price with the value a buyer measures, the fraud avoided per scanned interaction, and the deployment choices of API, private cloud, on-premise, and SaaS suggest tiering by control and scale.
A free public Deepfake Detection API sits alongside the enterprise sale. That lowers developer adoption friction and seeds the funnel, and the named enterprise and government customers suggest negotiated contracts are the likely primary monetization path, though no public source discloses the revenue mix.
Delivery is API-first and designed to slot into existing workflows. Reality Defender positions itself as a signal that feeds the fraud tools, call-center platforms, and video-conferencing solutions a buyer already runs, rather than a system that replaces them, which lowers the integration burden for a security team.
Deployment flexibility is a deliberate operations choice. API integration, private cloud, on-premise, and hosted SaaS let regulated buyers meet data-residency and sovereignty constraints, and on-premise in particular addresses banks and governments that will not send media to a vendor cloud.
Real-time operation is the demanding requirement. Detecting deepfakes live during a call or meeting, then handing a signal back fast enough to act, is a latency and reliability problem, and the contact-center work is the operational evidence, with Reality Defender describing concurrent scanning of all voice traffic in and out of customer call centers. The Orange Business agreement is an announced telecom embedding rather than a demonstrated production integration, since the reporting covers the deal and not a go-live.
Reality Defender publishes an inspectable trust posture rather than a single self-asserted badge. Its trust center lists a SOC 2 Type 2 report dated October 2025, a UK Cyber Essentials 2025 certificate, GDPR and HIPAA alignment, a recent penetration test, and a documented policy library available on request.
Deployment options reinforce the trust story for regulated buyers. On-premises and Secure Container keep processing in buyer-controlled infrastructure, while the virtual private cloud is a dedicated environment Reality Defender runs, which matters where third-party risk review and data sovereignty gate the purchase.
The posture is strong table stakes rather than a moat. SOC 2 and Cyber Essentials ease procurement but do not legally compel the purchase, and no US federal authorization appears in the public record, so the collateral supports the sale without locking out a determined competitor.
Reality Defender positions as a detection layer inside other vendors' ecosystems rather than a standalone platform. Its value proposition is explicitly to feed a real-time authenticity signal into the fraud, call-center, and conferencing tools an enterprise already uses, which is integration-led rather than platform-led.
The ecosystem moves are partnerships and embedding. The Orange Business deal integrates detection into a telecom's communication services, AWS serves as the infrastructure foundation with AWS Marketplace as a stated go-to-market path, and the public API invites third-party developers to build on the detection engine.
The platform ambition is bounded by the product's nature. A detection signal is a powerful component but does not by itself create the two-sided dynamics of a platform, so durable positioning is more likely to come from being the embedded standard inside many ecosystems than from owning a platform of its own.
The founding team pairs financial-sector credibility with hands-on technical experience. CEO Ben Colman led cybersecurity commercialization at Goldman Sachs and worked with the partnerships team at Google, and the company describes co-founder Ali Shahriyari as a technologist and AI expert with over 20 years in software development who led product at the AI Foundation, with Gaurav Bharaj listed as the third co-founder. That composition maps directly to a detection product sold to banks and governments.
The company's history signals conviction and patience. It started as a non-profit company with a mission-driven core, building detection years before the market felt the threat, which gave the team time to mature the technology while awareness caught up.
External recognition supports execution credibility. The 2024 RSA Conference Innovation Sandbox win and the December 2025 Gartner front-runner note are public signals that the team is taken seriously in the category, the kind of validation that helps a young vendor close risk-averse enterprise buyers.
| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | https://www.realitydefender.com | official | 2026-06-21 |
| f2 | https://www.prnewswire.com/news-releases/reality-defender-expands-series-a-to-33-million-to-enhance-ai-detection-capabilities-302283098.html | press | 2026-06-21 |
| f3 | https://www.realitydefender.com/platform | official | 2026-06-21 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Reality Defender: Deepfake Detection “Identify synthetic media in real time across calls, meetings, access workflows, and executive communications, integrated into the systems you already run.” | official | 2026-06-21 |
| s2 | PR Newswire: Reality Defender Expands Series A to $33 Million “Reality Defender, the premier deepfake and AI-generated media detection platform, announced today that its Series A fundraising has been expanded, securing a total of $33 million in capital investment. The expanded fundraising round was led by Illuminate Financial” | press | 2026-06-21 |
| s3 | AWS Startups: Reality Defender vs the deepfake era “Reality Defender is now serving some of the leading names in their respective fields, including professional services firms like Accenture and Booz Allen Hamilton, tier one banks such as JP Morgan, as well as government agencies in the US and UK.” | official | 2026-06-21 |
| s4 | Reality Defender: Recognized by Gartner as the Deepfake Detection Company to Beat “Reality Defender Recognized by Gartner as the Deepfake Detection Company to Beat. The current market is nascent, but Reality Defender is currently the front-runner, particularly within high-stakes enterprise verticals.” | official | 2026-06-21 |
| s5 | Biometric Update: Reality Defender brings web-based deepfake protection to enterprise “Reality Defender has unveiled Real Suite, a set of enterprise tools. RealScan is a web-based platform with a drag-and-drop interface with support for video, audio and imagery. Real Suite introduces RealAPI, a set of developer SDKs, and RealCall.” | press | 2026-06-21 |
| s6 | Biometric Update: Reality Defender strikes deal to provide deepfake detection to French Orange “The deal integrates multimodal deepfake detection, including audio, video, image and document analysis, directly into Orange Business's existing communication services, including video conferencing, contact center platforms and voice telephony.” | press | 2026-06-21 |
| s7 | Reality Defender: Platform “Reality Defender's audio detection technology rapidly identifies synthetic and manipulated speech and voice clones of executives, employees, and customers.” | official | 2026-06-21 |
| s8 | Reality Defender: Wins Most Innovative Startup at RSA Conference Innovation Sandbox “We are deeply honored and humbled to be named the Most Innovative Company at this year's RSA Innovation Sandbox.” | official | 2026-06-21 |
| s9 | Reality Defender: Trust Center “Compliance SOC 2 GDPR UK Cyber Essentials HIPAA. Assessments: UK Cyber Essentials Certificate 2025, SOC2 Type 2 Report October 2025, Penetration Test 2025.” | official | 2026-06-21 |
| s10 | About Reality Defender “We equip high-trust systems with the tools to verify authenticity at scale. Co-Founders Ali Shahriyari and Gaurav Bharaj.” | official | 2026-06-21 |
| s11 | Reality Defender: Ben Colman, Co-Founder and CEO “Prior to this, Ben led cybersecurity commercialization at Goldman Sachs, and worked with the partnerships team at Google. He holds an MBA from NYU Stern.” | official | 2026-06-21 |
| s12 | arXiv: Deepfake-Eval-2024, a Multi-Modal In-the-Wild Deepfake Benchmark “We evaluate commercially available deepfake detection models from companies that partnered with TrueMedia.org: Hive, Reality Defender, Pindrop, AI or Not, Hiya, Fraunhofer, and Sensity AI.” | research | 2026-06-30 |
| s13 | CB Insights: Reality Defender Company Profile “Investors of Reality Defender include BNY Ascent Program, Fusion Fund, Samsung NEXT, Bank of New York Mellon, CyberBoost Catalyse and 41 more.” | research | 2026-06-30 |
| s14 | US Senate Judiciary: Oversight of AI, Election Deepfakes Hearing “Ben Colman CEO and Co-Founder Reality Defender New York, NY” | regulatory | 2026-06-30 |
| s15 | Congress.gov: S.Hrg. 118-573 Oversight of AI, Election Deepfakes “STATEMENT OF BEN COLMAN, CEO AND CO-FOUNDER, REALITY DEFENDER, NEW YORK, NEW YORK” | regulatory | 2026-06-30 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Reality Defender: Deepfake Detection “Get started for free with 50 audio or image scans per month.” | official | 2026-08-06 |
| s2 | PR Newswire: Reality Defender Expands Series A to $33 Million “The expanded fundraising round was led by Illuminate Financial, with additional participation from Booz Allen Ventures, IBM Ventures, the Jefferies Family Office, and Accenture, as well as additional participation from original Series A lead investor DCVC” | press | 2026-06-21 |
| s3 | AWS Startups: Reality Defender vs the deepfake era “Reality Defender is now serving some of the leading names in their respective fields, including professional services firms like Accenture and Booz Allen Hamilton, tier one banks such as JP Morgan, as well as government agencies in the US and UK.” | official | 2026-06-21 |
| s4 | Reality Defender: Recognized by Gartner as the Deepfake Detection Company to Beat “According to Gartner, Reality Defender's ensemble-of-models approach creates a powerful data network effect, leveraging diverse datasets to continuously improve detection capabilities. It also offers free access to the Deepfake Detection API.” | official | 2026-06-21 |
| s5 | Biometric Update: Reality Defender brings web-based deepfake protection to enterprise “Real Suite introduces RealAPI, a set of developer SDKs for embedding detection into apps and workflows. The platform also includes RealCall, a real-time voice deepfake detection capability.” | press | 2026-06-21 |
| s6 | Biometric Update: Reality Defender strikes deal to provide deepfake detection to French Orange “The deal integrates multimodal deepfake detection, including audio, video, image and document analysis, directly into Orange Business's existing communication services, including video conferencing, contact center platforms and voice telephony.” | press | 2026-06-21 |
| s7 | Reality Defender: Platform “Deployments: API Integration, Private Cloud, On-Premise, Hosted SaaS. Reality Defender's audio detection technology rapidly identifies synthetic and manipulated speech and voice clones of executives, employees, and customers.” | official | 2026-06-21 |
| s8 | Reality Defender: Trust Center “Compliance SOC 2 GDPR UK Cyber Essentials HIPAA. Assessments: UK Cyber Essentials Certificate 2025, SOC2 Type 2 Report October 2025, Penetration Test 2025.” | official | 2026-06-21 |
| s9 | AWS Startups: Reality Defender, API-first signal “You need a tool that can actually scan that person's voice or face in real time and then feed that signal into all the fraud tools, real-time call center platforms or video conferencing solutions that everyone already uses.” | official | 2026-06-21 |
| s10 | Reality Defender: Wins RSA Conference Innovation Sandbox “We are deeply honored and humbled to be named the Most Innovative Company at this year's RSA Innovation Sandbox.” | official | 2026-06-21 |
| s11 | About Reality Defender “Co-Founders Ali Shahriyari and Gaurav Bharaj. We equip high-trust systems with the tools to verify authenticity at scale.” | official | 2026-06-21 |
| s12 | Reality Defender: Ben Colman, Co-Founder and CEO “Prior to this, Ben led cybersecurity commercialization at Goldman Sachs, and worked with the partnerships team at Google. He holds an MBA from NYU Stern.” | official | 2026-06-21 |
| s13 | Reality Defender: Ali Shahriyari, Co-Founder and Advisor “An accomplished technologist and AI expert with over 20 years of experience in the software development industry, Shahriyari served as the Director of Product at the AI Foundation, building the first AI-Native Human Platform and developing Digital Deepak, an iOS and Android Unity-based app.” | official | 2026-08-05 |
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