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.
Daxa sells data governance software to enterprises using generative AI, and it markets Proxima, a secure AI knowledge engine, to regulated industries. The software limits AI applications and agents to the data each person may see, by permissions and the data's meaning. Leaders from Cisco, McAfee, F5 and Trend Micro founded Daxa in 2019. Its Pebblo software tracks those permissions and the data's meaning as developers load data into AI applications, and it supports the LangChain toolkit. It sold $3.125 million of a $3.5 million offering, per a US securities filing. Gartner included Daxa in its 2025 market guide for AI trust, risk and security management. Makers of the AI assistants enterprises already run could add the same controls, reducing demand for Daxa's tool.
| Description | Daxa builds data governance software for generative AI, enforcing identity-aware and semantic access controls on the enterprise data that AI applications and agents can retrieve, write, or share at runtime. | [f1] |
|---|---|---|
| Founded | 2019 | [f2] |
| HQ | Cupertino, California, USA | [f2] |
| Funding | $3.125M total | [f2] |
| Latest funding | 3.13 million dollar offering (2022, SEC Form D) | [f2] |
| Product | What it does |
|---|---|
| Pebblo | Open source data-security layer for generative AI apps that classifies data at load time and enforces identity and semantic access controls on retrieved context, with native LangChain support. |
| Proxima | Secure AI knowledge engine for regulated industries that connects data, models, and workflows while enforcing governed retrieval and access controls. |
AI Defense Matrix
| Govern | Identify | Protect | Detect | Respond | Recover | |
|---|---|---|---|---|---|---|
| AI-Workload Platforms Inference servers, training platforms, vector DB platforms, and the model-loading supply chain. | ||||||
| AI Orchestration Tools Agentic orchestration tools, plus their plugins, skills, hooks, system prompts, scaffolding, harnesses, configuration settings, and MCP clients on user devices. | ||||||
| AI-Generated Code Code produced by AI tools, AI-assisted reviews, AI-generated infrastructure-as-code and tests, and vibe-coded apps that bypass CI/CD. | ||||||
| AI Gateways & Routers MCP proxies and gateways, LLM routers, outbound AI-service traffic, shadow AI egress, and model-registry traffic. | ||||||
| AI Model Model weights, fine-tuning checkpoints, model cards, registries, AIBOM, and the third-party LLMs your enterprise consumes. | ||||||
| Training Data Datasets used for training, fine-tuning, and continued learning. | ||||||
| Runtime AI Data User prompts, inference inputs, RAG content, vector DB content, persistent agent memory, and interaction history. | ||||||
| AI Agent Identities AI agents as non-human principals, plus credentials, keys, permission scopes, service accounts, and delegation chains across agents and tools. |
Pebblo classifies enterprise data and, with Proxima, enforces identity-aware and semantic access controls on the data that generative AI applications retrieve at runtime, and governs the actions AI agents can take on that data. These capabilities are mapped to the AI 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. | 3/5 | Daxa names a clear buyer and a real problem: enterprise data governance does not follow information into AI apps and agents, exposing sensitive records. The pain is genuine and Gartner has built the AI trust, risk, and security management category around it, but the specific harm is vendor-asserted rather than independently quantified. [s1, s9] |
| Capability Depth How specific the technical capabilities are, with evidence beyond marketing claims such as docs and third-party validation. | 4/5 | Pebblo is public open-source code with a documented SafeLoader and SafeRetriever architecture, and Daxa's docs state it is natively supported in LangChain. The inspectable open-source implementation is an external validation point beyond marketing that most peers lack. The enterprise products are thinner in public technical depth. [s4, s5, s6] |
| Market Timing Whether the market is ready for this product, with evidence that buyers are actively seeking solutions. | 3/5 | Enterprise adoption of generative AI and retrieval apps since 2023 created the data-governance gap Daxa targets, a credible enabler. Buyer-side demand shows mainly through Gartner's 2025 AI trust, risk, and security management market guide, which named Daxa, not through multiple independent signals. The window risk is incumbents bundling the same control. [s9, s1] |
| Team Credibility Demonstrated domain expertise with public signals such as prior exits, publications, and industry recognition. | 3/5 | The founders and team carry senior in-domain experience from Cisco, McAfee, F5, and Trend Micro, and the advisor bench includes Nico Popp, a former Tenable and Forcepoint chief product officer. No notable prior exit by the founders appears in the public record, holding this at verifiable experience rather than recognized track record. [s2, s3] |
| GTM Proof Evidence of actual traction (customers, revenue signals, partnerships) beyond stated intentions. | 3/5 | Traction depends on Pebblo's open-source distribution and native LangChain support, an HPE partnership and NVIDIA Inception program membership, and vendor-posted testimonials from Postman's and SAP's security leaders. These references are vendor-displayed with no disclosed revenue, so traction is real in developer and ecosystem terms but unproven at enterprise scale. [s5, s6, s10, s11, s9, s14, s15] |
| Funding Efficiency Whether funding matches go-to-market ambition, with signs of capital-efficient growth. | 2/5 | Daxa discloses one 3.13 million dollar offering in a 2022 SEC filing, with no later round in the public record and a rebrand from Cloud Defense, Inc. in between. On a small raise now four years old, capital efficiency is unconfirmed, and the stale, thin funding evidence sits below the deploying-startup default. [s7, s8] |
| Category Clarity Whether the company creates or fits a recognizable category that buyers can quickly place in their stack. | 3/5 | Daxa fits the emerging AI trust, risk, and security management category and Gartner has listed it there, but the space is contested and Daxa layers its own coined positioning on top. Buyers still need vendor explanation to place it against data-posture tools and AI firewalls. [s9, s1] |
| Incumbent Defensibility How vulnerable the core value proposition is to absorption as a feature by a platform vendor. | 2/5 | Governing which enterprise data an AI app retrieves is a plausible near-term feature for Microsoft Purview and Copilot, which sit adjacent to the buyer, and Pebblo's open-source core is copyable. No proprietary data flywheel or structural lock-in offsets that absorption risk. [s4, s1] |
Daxa targets a gap that opens when enterprises connect generative AI to their own data. Traditional access controls do not follow information into a retrieval-augmented app or an AI agent, so sensitive records can reach a model or a user who should not see them. Daxa frames this as the point where data governance ends and AI risk begins.
The buyer is an enterprise security, governance, or AI platform team in a regulated industry that wants to deploy AI assistants without leaking data. The problem is real and widely discussed, and Gartner has built an AI trust, risk, and security management category around it. The problem statement is clear, though the specific harm stays vendor-asserted rather than independently measured. [s1, s9]
Pebblo is Daxa's open-source core and the clearest evidence of what the company builds. Pebblo identifies semantic topics and entities in the data its loader ingests, and its SafeRetriever enforces identity and semantic rules before LLM inference so a retrieval app returns only context a given user may see. The project ships as public open-source code, and Daxa's docs state it is natively supported in LangChain, so its capability is inspectable rather than marketing alone.
Proxima packages this into an enterprise product, a secure AI knowledge engine for regulated industries that connects data, models, and workflows under the same controls. Daxa also positions a governance layer that reasons over what actions an AI agent may take on specific data. The public technical depth is strongest for Pebblo, while the enterprise products are documented mostly through the vendor's own pages. [s4, s5, s6, s16]
Daxa sits in a crowded, fast-forming space where several kinds of vendor are converging. Microsoft can extend Purview and Copilot to govern which data its own AI assistant retrieves, absorbing much of Daxa's job for customers already on that stack. Data-security platforms such as BigID discover and classify sensitive data and are extending into AI, and need-to-know controls from vendors like Knostic address the same enterprise-AI oversharing problem.
Daxa's own site names Glean as a competitor, positioning Proxima against enterprise AI search. Its differentiation rests less on a unique capability than on Pebblo's developer following and an identity-aware, semantic approach to retrieval. Because Pebblo is open source, that approach is visible to and reproducible by better-funded rivals. [s1, s4, s17]
Daxa's most visible traction is developer interest in Pebblo rather than named enterprise revenue. The project draws community interest on GitHub and, more meaningfully, native support inside LangChain, which puts the loader in front of teams already building retrieval apps.
Named references are limited to vendor-posted testimonials, including Postman's chief information security officer Sam Chehab and SAP's Ryan Tolentino, and no disclosed revenue or paying-customer list appears in the public record. Daxa adds ecosystem signals that suggest momentum without confirming scale. It joined the NVIDIA Inception startup program, announced a partnership with HPE around secure AI factories, and Gartner included it in the 2025 AI trust, risk, and security management market guide. A Gartner market guide names representative vendors rather than leaders, and none of these substitutes for disclosed customers or revenue. [s5, s6, s10, s11, s9, s14, s15]
Daxa was founded by industry veterans. Co-founder and chief executive Huseni Saboowala leads a team the company says draws from Cisco, McAfee, F5, and Trend Micro, and SEC records confirm Saboowala as an officer and director of the legal entity, Cloud Defense, Inc. The founders have senior in-domain backgrounds, though the public record shows no prior notable exit by them.
The advisor bench is a credibility signal in its own right, including Nico Popp, a former chief product officer at Tenable and Forcepoint. Advisors strengthen the story but are not the operating team, and the company remains small. [s2, s3, s7]
Daxa displays a SOC 2 badge in its website footer, which signals the baseline security posture enterprise buyers expect. The badge is self-displayed, and a probe of the homepage, footer, trust and security subdomains, and common trust paths found no inspectable audit report or third-party trust portal as of 2026-07-03, so the badge reads as a claimed attestation rather than verified collateral.
As a company incorporated in Delaware in 2019 and operating with a small team, Daxa is early in building the trust apparatus that regulated-industry buyers scrutinize. Its products speak directly to compliance needs, but the company's own verifiable attestations remain modest. [s12, s13, s8]
| Company | Relationship | Note | Compare |
|---|---|---|---|
| Microsoft | adjacent | Purview and Copilot can extend data governance to Microsoft's own AI assistant, absorbing much of Daxa's job for customers on that stack. | N/AMicrosoft is scored by product line, not as a whole company, so there is no company-wide column to compare. Open its profile to compare a specific product. |
| BigID | competes with | Data-security platform that discovers and classifies sensitive data and is extending into AI data governance. | |
| Knostic | competes with | Addresses the same enterprise-AI oversharing problem with need-to-know controls over AI assistants. | |
| Glean | competes with | Named on Daxa's own site as a competitor, with Proxima positioned against enterprise AI search. |
Add analyzed competitors to compare them side by side with Daxa.
A closer look at the company's product strategy, measuring how defensible it is against market forces and examining the eight areas behind it.
pivot urgently
Nothing in Daxa's structure is hard for a well-funded rival to reproduce. The product enforces identity and semantic controls on the data a generative AI app retrieves, which takes real engineering. But Pebblo's core ships as freely licensed open source, so its published components are forkable, and the cited record names no proprietary dataset. Whether platform vendors running enterprise AI assistants or established data-security tools would bundle the same control is an unquantified risk. Daxa's SOC 2 presence is a badge asset with no inspectable report, and switching friction from connector integration and policy configuration is an unsized inference. Its visible edge is Pebblo's documented but unquantified LangChain support, which pays off only if open-source users convert first.
| 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 | Daxa sells software rather than a managed service. Customers configure and run the open-source Pebblo loader and server, the enterprise products' deployment model is not detailed in the record, and no human-accountability layer is part of what is sold, which is the software-product level. |
| Switching Cost How expensive leaving is for a customer: data portability, integrations, learned workflows, network effects, regulatory data residency. | 2/3 | Leaving carries moderate friction: a customer wires Pebblo into its enterprise permission systems through SafeConnectors and configures policies, friction that follows from the documented integration surface rather than a sized migration record. The cited pages do not document how Proxima integrates with those systems. That integration is real but shallow and the core is open source and portable. The cited record shows no cross-customer network effect, and it does not quantify migration cost for the audit and policy history Daxa says Pebblo accumulates. |
| Compliance Moat Whether certifications, liability acceptance, or audit trails block an easy replacement. | 1/3 | Daxa's homepage markup carries a SOC 2-named badge asset, and a probe found no inspectable report or trust portal. The cited record documents no certification detail, liability acceptance, or unusual accountability commitment. |
| Problem Complexity Whether the product requires ML, optimization, real-time systems, or years of specialized expertise. | 2/3 | Enforcing identity-aware and semantic controls on data reaching a model, propagating fine-grained permissions from source systems in real time, is meaningful engineering. It is not extraordinarily hard, and a well-funded rival can build it, as the open-source core itself demonstrates. |
| Buyer Profile Whether buyers are SMB operators, mid-market IT teams, or regulated enterprises and governments with procurement gates. | 2/3 | Daxa targets sophisticated regulated-enterprise security and AI teams with real budgets, a buyer that supports durable pricing. The company has not shown a proven install base with that buyer, so the score reflects the buyer it credibly addresses rather than demonstrated enterprise traction. |
| Layer Whether the product is an end-user application, a platform with application features, or infrastructure other applications depend on. | 2/3 | Pebblo's SafeRetriever sits in the retrieval path, and Daxa's documentation shows it wired in as a retrieval chain around a plain vector-store retriever, so replacing it with that plain retriever removes Pebblo's enforcement. That is moderate embedding. The cited record does not document the effort of removal or how an installed application behaves once the control is gone. |
| Proprietary Data, Content, or IP Whether the product accumulates datasets, content licenses, or IP that a rival cannot recreate from scratch. | 1/3 | Daxa names no proprietary, non-public dataset. Its classifiers and policies are configurable, the core ships as open source, and no cross-customer data asset appears in the record, so nothing here is a barrier a funded rival could not rebuild. |
Daxa aims at enterprises in regulated industries deploying generative AI on their own data, the segment where data-access mistakes carry compliance consequences. Proxima is pitched as a secure knowledge engine for regulated industries. The segmentation is coherent: the buyer is a security or AI platform team that must let employees and agents use enterprise data without oversharing.
Daxa faces a depth-versus-breadth tension. Pebblo's LangChain integration pulls in a broad developer audience building any retrieval app, while Proxima chases a narrower, higher-value regulated-enterprise buyer. Serving both with an undisclosed headcount risks diffusing focus, and the company has not yet shown which segment funds the business.
Daxa's capability is permission-aware, semantically aware retrieval. Pebblo classifies data at load time and enforces identity and semantic controls at retrieval, so an AI app returns only what a given user may see, using an architecture Daxa calls TwinGuard with SafeConnectors and SafeRetriever. The mechanism is real engineering, because propagating fine-grained permissions from source systems into the retrieval path is non-trivial.
The advantage is narrower than the marketing suggests. The core is open source, so the technique is public, and the cited record identifies no proprietary model or non-public AI asset. What Daxa shows is Pebblo's native LangChain support, an ecosystem position rather than an irreproducible capability.
Daxa's go-to-market leans on open source and ecosystem partnerships rather than a visible enterprise sales motion. Pebblo functions as a developer on-ramp, and NVIDIA Inception membership, a startup program, plus the HPE partnership aim to place Daxa where enterprise AI infrastructure is bought. Public pages emphasize demo and contact-led selling, with no self-serve enterprise purchase flow visible on the cited pages.
The gap is proof at scale. Named references are limited to vendor-posted testimonials from Postman's chief information security officer and SAP's cloud-security lead, with no public evidence of a repeatable enterprise sales engine and no current revenue disclosure beyond the low seven-figure ceiling range checked on the 2022 Form D. For a company selling into regulated enterprises, that thin, vendor-posted proof is what a buyer would weigh most heavily.
No pricing for Proxima or the enterprise platform appears on the cited product and documentation pages, which is typical for a vendor pursuing negotiated regulated-enterprise deals. Pebblo is MIT-licensed open source, a common entry point that lowers adoption cost and defers revenue to the enterprise tier.
The model implies Daxa charges for the enterprise product and the operational governance around it, not for the open-source loader. Without published prices or disclosed deal sizes, how effectively Daxa converts open-source adoption into paid revenue cannot be assessed from the public record.
Daxa delivers the open-source Pebblo as software the customer configures and runs, installing into the customer's own data pipeline through its loader and enforcement components, while the enterprise products' deployment model is not detailed in the cited record beyond reaching data behind its permission systems. This is a software-product delivery model, not a managed service that accepts operational accountability.
Operating a real-time enforcement step in the retrieval path raises reliability expectations, because a governance layer that fails can block legitimate answers. With total headcount undisclosed, sustaining enterprise-grade uptime and support across regulated customers is an execution risk the public record cannot yet resolve.
Trust is central to Daxa's pitch and only partly evidenced. A SOC 2-named badge asset sits in the served homepage markup inside a footer block marked hidden, so whether visitors currently see it is unclear, and its products generate compliance reporting for the customer's obligations. That posture matches a buyer's checklist for a data-touching tool.
The SOC 2-named badge asset in the homepage markup is not the same as an inspectable report or a third-party trust portal, and a 2026-07-03 probe found the trust and security subdomains unregistered and the /trust and /security paths returning 404. The compliance features Daxa ships help customers meet their obligations rather than establishing Daxa's own accountability. For an early-stage vendor asking regulated enterprises to route sensitive data through its controls, deeper verifiable trust collateral is the next bar to clear.
Daxa's ecosystem position is its strongest strategic asset. Pebblo's native place in LangChain, plus NVIDIA Inception membership and the HPE AI factory partnership, position Daxa at the layers where enterprise AI is assembled. For an infrastructure-adjacent security tool, sitting inside the developer framework and a hardware partner's stack is ecosystem positioning and potential channel access. The cited sources do not document realized co-selling, marketplace reach, or customers won through these routes.
The dependency cuts both ways. Pebblo's Safe DataLoader documentation lists current LangChain support with LlamaIndex and Haystack planned, though the current product page describes broader surfaces, including MCP clients and an OpenAI-compatible API. If developer reach stays concentrated in one framework while the ecosystem shifts, the distribution edge narrows.
Daxa's public leadership page names a compact roster whose total size the record does not state. The founders and early team draw from Cisco, McAfee, F5, and Trend Micro, and the advisor bench includes senior security-product leaders such as Nico Popp, a former Tenable and Forcepoint chief product officer. SEC filings confirm Huseni Saboowala as an officer and director of Cloud Defense, Inc.
Execution capacity is the open question. With the cited record documenting one 2022 offering of $3.125 million sold, Daxa competes for regulated-enterprise trust against far larger vendors. The move from the Cloud Defense, Inc. origin to the Daxa brand shows adaptability, but scaling enterprise sales and support on this base is unproven.
| Id | Source | Tier | Accessed |
|---|---|---|---|
| f1 | Daxa homepage | official | 2026-07-03 |
| f2 | SEC Form D, Cloud Defense, Inc. (CIK 1920837, filed 2022-04-06) | regulatory | 2026-07-03 |
| f3 | Pebblo product page | official | 2026-07-03 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Daxa homepage “one governance layer that reasons over data, identity, and agent action in real time” | official | 2026-07-03 |
| s2 | Daxa about page, leadership “DAXA was founded by data, security, and AI industry leaders from Cisco, McAfee, F5, and Trend Micro.” | official | 2026-07-03 |
| s3 | Daxa about page, advisors “Nico Popp Former Chief Product Officer, Tenable & ForcePoint” | official | 2026-07-03 |
| s4 | Pebblo product page “Pebblo's permissions and semantic aware AI data ingestion layer sets the stage for secure, compliant, and role aware access to enterprise data for AI apps and agents.” | official | 2026-07-03 |
| s5 | GitHub: daxa-ai/pebblo repository metadata “{"full_name": "daxa-ai/pebblo", "description": "Pebblo enables developers to safely load data and promote their Gen AI app to deployment", "archived": false, "stargazers_count": 150, "forks_count": 44” | other | 2026-07-03 |
| s6 | Pebblo documentation overview “Pebblo Safe DataLoader currently support Langchain framework.” | other | 2026-07-03 |
| s7 | SEC Form D, Cloud Defense, Inc. (filed 2022-04-06) “Total Offering Amount $ 3,500,000 USD or Indefinite Total Amount Sold $ 3,125,000 USD” | regulatory | 2026-07-03 |
| s8 | SEC Form D, Cloud Defense, Inc. (Huseni Saboowala, officer and director), year of incorporation “Year of Incorporation/Organization Over Five Years Ago X Within Last Five Years (Specify Year) 2019” | regulatory | 2026-07-03 |
| s9 | Silicon UK (Business Wire): Daxa recognized in the 2025 Gartner AI TRiSM Market Guide “Daxa, a leader in AI data security and governance, has been included in the 2025 Gartner Market Guide for AI Trust, Risk & Security Management (AI TRiSM) for the AI Governance and Runtime Inspection and Enforcement use case.” | press | 2026-07-03 |
| s10 | Daxa joins the NVIDIA Inception program “DAXA has joined the NVIDIA Inception program, bringing the company into the ecosystem where the enterprise agentic AI stack is being built” | official | 2026-07-03 |
| s11 | Daxa homepage, HPE partnership headline “HPE and DAXA Partner to Build Secure AI Factories” | official | 2026-07-03 |
| s12 | Daxa homepage footer, SOC 2 badge “636a5c651c7417e9ef7672d4_soc2.webp” | official | 2026-07-03 |
| s13 | Probe of Daxa trust surfaces (trust. and security. subdomains, no DNS; /security and /trust paths, 404); footer shows a self-displayed SOC 2 badge, 2026-07-03 | other | 2026-07-03 |
| s14 | Daxa homepage, Postman testimonial “Sam Chehab CISO Postman” | official | 2026-07-03 |
| s15 | Daxa homepage, SAP testimonial “Ryan Tolentino Global Head of Multi cloud security, SAP” | official | 2026-07-03 |
| s16 | Daxa homepage, Proxima launch headline “DAXA.ai Launches Proxima: The Secure AI Knowledge Engine for Regulated Industries” | official | 2026-07-03 |
| s17 | Daxa homepage footer, competitor comparison link “Daxa vs. Glean” | official | 2026-07-03 |
| Id | Source | Tier | Accessed |
|---|---|---|---|
| s1 | Daxa homepage “one governance layer that reasons over data, identity, and agent action in real time” | official | 2026-07-03 |
| s2 | Daxa about page, leadership “DAXA was founded by data, security, and AI industry leaders from Cisco, McAfee, F5, and Trend Micro.” | official | 2026-07-03 |
| s3 | Daxa about page, advisors “Nico Popp Former Chief Product Officer, Tenable & ForcePoint” | official | 2026-07-03 |
| s4 | Pebblo product page “Pebblo's permissions and semantic aware AI data ingestion layer sets the stage for secure, compliant, and role aware access to enterprise data for AI apps and agents.” | official | 2026-07-03 |
| s5 | GitHub: daxa-ai/pebblo repository metadata “{"full_name": "daxa-ai/pebblo", "description": "Pebblo enables developers to safely load data and promote their Gen AI app to deployment", "archived": false, "stargazers_count": 150, "forks_count": 44” | other | 2026-07-03 |
| s6 | Pebblo documentation overview “Pebblo Safe DataLoader currently support Langchain framework.” | other | 2026-07-03 |
| s7 | SEC Form D, Cloud Defense, Inc. (filed 2022-04-06) “Total Offering Amount $ 3,500,000 USD or Indefinite Total Amount Sold $ 3,125,000 USD” | regulatory | 2026-07-03 |
| s8 | SEC Form D, Cloud Defense, Inc. (Huseni Saboowala, officer and director), year of incorporation “Year of Incorporation/Organization Over Five Years Ago X Within Last Five Years (Specify Year) 2019” | regulatory | 2026-07-03 |
| s9 | Silicon UK (Business Wire): Daxa recognized in the 2025 Gartner AI TRiSM Market Guide “Daxa, a leader in AI data security and governance, has been included in the 2025 Gartner Market Guide for AI Trust, Risk & Security Management (AI TRiSM) for the AI Governance and Runtime Inspection and Enforcement use case.” | press | 2026-07-03 |
| s10 | Daxa joins the NVIDIA Inception program “DAXA has joined the NVIDIA Inception program, bringing the company into the ecosystem where the enterprise agentic AI stack is being built” | official | 2026-07-03 |
| s11 | Daxa homepage, HPE partnership headline “HPE and DAXA Partner to Build Secure AI Factories” | official | 2026-07-03 |
| s12 | Daxa homepage footer, SOC 2 badge “636a5c651c7417e9ef7672d4_soc2.webp” | official | 2026-07-03 |
| s13 | Probe of Daxa trust surfaces (trust. and security. subdomains, no DNS; /security and /trust paths, 404); footer shows a self-displayed SOC 2 badge, 2026-07-03 | other | 2026-07-03 |
| s14 | Daxa homepage, Postman testimonial “Sam Chehab CISO Postman” | official | 2026-07-03 |
| s15 | Daxa homepage, SAP testimonial “Ryan Tolentino Global Head of Multi cloud security, SAP” | official | 2026-07-03 |
| s16 | Daxa homepage, Proxima launch headline “DAXA.ai Launches Proxima: The Secure AI Knowledge Engine for Regulated Industries” | official | 2026-07-03 |
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