HoundDog

Privacy Code Scanner and API Context Engine for AI Coding Agents Detect PII leaks, automate GDPR data mapping with RoPA, PIA, and DPIA, and provide AI coding agents with continuously updated API context. Try Privacy Code Scanner Try API Context Engine Now available: HoundDog.ai API Context Engine for AI Coding Agents Learn more Trusted By Two Products. One Platform. Comprehensive visibility into privacy risks in your application code with automated GDPR data mapping and real time insight into API dependencies for AI coding agents across your services. Privacy Code Scanner Embed privacy into development to detect privacy risks early and automate GDPR data mapping, RoPA, PIA, and DPIA reporting. No surveys. No spreadsheets. No relying on memory. Learn about Privacy Code Scanning → New API Context Engine Provide AI coding agents with continuously updated API dependency graphs and service context across large monorepos and complex microservice architectures. Safe API changes. Faster development. Lower AI token costs. Explore the Context Engine Powering AI Coding Agents API Context Engine for AI Coding Agents HoundDog.ai API Context Engine provides multiple ways to integrate with your existing AI agents: CLI, local MCP and Skills. Identify which downstream services are affected by API changes Understand where specific fields are ingested by each service Map cross-service dependencies before generating code Reduce token burn and eliminate repetitive file scanning Export API graphs locally for documentation and collaboration Learn More → Privacy Code Scanner Problem: Privacy Risks Start in Code - Not After Deployment Traditional privacy tools detect problems too late, when data is already in motion, pushing teams into remediation rather than prevention. Sensitive Data in Logs & Local Storage Sensitive data appearing in logs or local storage forces organizations into reactive cleanup. DLP tools surface problems only after exposure, sending teams into weeks of tracing data paths, cleaning up logs, and rewriting code. Incidents often start with simple oversights like printing full user objects or passing tainted variables into logging functions. As applications scale and code paths multiply, these mistakes become harder to catch and more frequent. Shadow AI & Third-Party Integrations Data shared with third party or AI integrations must align with Data Processing Agreements and your privacy notice. Silent code changes can redirect sensitive fields to analytics platforms, observability pipelines, or LLM prompts. These hidden shifts erode user trust and increase regulatory exposure long before privacy teams are aware. Hidden Cross-Service Flows Sensitive data flows between microservices and APIs in ways teams cannot easily track or document. Cross repo dependencies over REST, GraphQL, or gRPC and complex code transformations defeat traditional scanning approaches. As a result, sensitive data exposed through these API protocols often goes undocumented or poorly understood, creating hidden privacy and compliance risk. Sensitive Data in AI Prompts AI usage is accelerating, increasing the risk of unintentionally sharing sensitive data with external models. Many companies restrict AI services, yet scans routinely uncover AI SDKs like LangChain or LlamaIndex. Current privacy tooling is either too reactive, discovering these flows after the fact, or completely blind to them. Privacy teams scramble to understand what data is sent to AI systems and whether user notices and legal bases cover those flows. Why Existing Tools Fail Regulations like GDPR and US privacy frameworks require accurate data maps and reports such as RoPA, PIA, and DPIA. In fast moving engineering environments, those maps quickly fall out of date. Most data privacy solutions fall into two buckets. Governance, Risk, and Compliance Platforms GRC platforms provide blank templates for RoPA, PIA, and DPIA, like this one from Vanta, and ask privacy teams to do the heavy lifting. This usually means interviewing application owners, manually reconstructing data flows, and updating reports, only to repeat the process every time systems change Production focused Privacy Platforms Traditional privacy platforms operate only after applications are live. They attempt to infer data flows from information already stored in production systems, which leads to partial automation and limited visibility. These tools also rely on predefined knowledge of third party services, leaving them blind to shadow AI and new third party integrations introduced directly in code How Privacy Code Scanning Works Detect sensitive data flows, prevent PII leaks, and automate GDPR data mapping directly in your development workflow. Scan Code as It’s Written HoundDog.ai integrates directly into your development workflow to scan code in IDEs (VS Code, IntelliJ, Cursor) and in CI pipelines as it is written or generated. Trace Sensitive Data Flows Automatically map sensitive data flows directly from source code across functions, APIs, third party services, and AI integrations to detect privacy risks and support GDPR data mapping. Enforce Privacy Rules Before Deployment Apply allowlists to define which data types are permitted in LLM prompts and other risky sinks, and automatically block unsafe pull requests to maintain compliance. Build Customer Trust with Transparent Data Handling and GDPR Data Mapping Automatically generate GDPR data mapping and data flow maps directly from source code to show where sensitive data is collected, processed, and shared across functions, APIs, third party services, and AI integrations. Auto generate audit ready Records of Processing Activities (RoPA), Privacy Impact Assessments (PIA), and Data Protection Impact Assessments (DPIA) pre populated with detected sensitive data flows and privacy risks aligned with GDPR, CCPA, HIPAA, and other regulatory frameworks. Detect sensitive data flows using privacy code scanning to give privacy and security teams continuous visibility into processing activities without surveys, spreadsheets, or manual discovery. No production monitoring required. No retroactive cleanup. No guessing. Detect privacy risks early in development before code reaches production. Key Differentiators What Makes HoundDog.ai Different Purpose built for engineering teams that need to detect sensitive data flows and automate GDPR data mapping directly from source code. Code-Level Data Flow Intelligence Detect and map sensitive data flows directly from source code across APIs, services, and third party integrations without relying on surveys, spreadsheets, or privacy tools that miss hidden integrations and SDKs. Built for AI & LLM Workloads Discover AI SDKs embedded in code and detect sensitive data flows to LLM prompts and external AI APIs before your apps go live. Prevent Risk Before Deployment Catch PII leaks and risky data flows during development and code review, not after data has already been logged, shared, or leaked. Compliance from Real Data Flows Automatically generate GDPR data mapping along with audit ready RoPA, PIA, and DPIA documentation directly from detected code level data movement so compliance stays up to date as systems evolve. Enabling PII Leak Detection & GDPR Data Mapping Across All Stages of Development IDE Plugins Detect sensitive data leaks directly in your IDE as you write code. Catch privacy risks early before they reach production. Learn more → Managed Scans Offload scanning to HoundDog.ai with direct source control integrations. Automatically analyze repositories for privacy risks. Learn more → CI/CD Integrations Use HoundDog.ai source control integrations to auto configure CI. Block risky pull requests before they are merged. Learn more → DIY PII Detection Doesn’t Scale Hardcoded RegEx rules break easily and are a nightmare to maintain. Most DIY efforts stall before they scale Built for Enterprise-Grade Security Designed to meet the requirements of large, security-conscious organizations. Built for Enterprise Teams Trusted by Replit, running 10,000+ privacy scans per day to help 45M creators bake privacy into the earliest stages of prototyping and app creation Used by Fortune 1000 companies across technology, healthcare, and finance SOC 2 compliant, with a transparent Trust Center offering access to the latest SBOM and penetration testing reports Hands on, highly responsive customer support Secure by Default No production data or runtime ingestion required Runs locally in your environment or CI pipelines Secure broker for self hosted source control systems that meets strict network and data handling standards Transparent Trust Center with up to date SBOM and penetration testing reports Return On Investment ROI for Proactive Sensitive Data Protection For Every1mLines of Code Time Saved 4,000Hours Productivity Gain2Full-Time Employees (FTEs) ROI for Automated Privacy Compliance For Every200Code Repositories Time Saved3,200Hours Productivity Gain1.5Full-Time Employees (FTEs) Check out our ROI calculator for an estimation tailored to your organization's inputs.Go to ROI Why Shift-Left Privacy Matters Stop privacy risks at the source — while code is being written, not after it reaches production. AI Exposure Happens Fast Sensitive data can be exposed to AI tools within minutes of code changes. Post-Production Tools Are Too Late Fixing leaks after release doesn’t prevent real damage. Compliance Requires Prevention Modern privacy programs must prevent risks, not just report them after exposure. Trusted by Replit to detect privacy leaks across AI generated applications built by more than 45 million creators. Make Privacy-by-Design a Reality in Your SDLC Shift left on privacy with code scanning. Detect PII leaks, map sensitive data flows, and generate GDPR data maps, RoPA, PIA, and DPIA before code reaches production. Start Free Book a Live Demo --- Providing a lens into PII data handling and third-party data flows early in developmentPricing Plans FreeStart Free $0 /mo Sensitive Data Leak Detection(trace sensitive data flows across transformations in code to catch PII and PHI leaks in risky data sinks such as logs, files, local storage, third-party SDKs, and AI integrations before code is pushed to production) [limited to specific programming languages and data sinks - see details] Sensitive Data Mapping and Data Flow Visualization(automatically map and visualize where sensitive data is stored, processed, and shared across third-party services, AI SDKs, and APIs, using source code as auditable evidence for early risk detection) [limited to specific programming languages and data sinks - see details] Shadow AI Discovery(uncover hidden or undocumented AI SDKs and abstractions in code and see exactly what sensitive data is being sent to them, even through complex transformations, to catch risks before data starts flowing) Limited to OpenAI, Anthropic, and Gemini IDE Plugins(embed privacy in the earliest stages of development and catch sensitive data leaks as code is being written. Supports VS Code, Cursor, and IntelliJ) CI/CD Integration(e.g. GitHub Actions, GitLab CI/CD) Support GitHub Issues StarterSign Up $100 /yr per developer Sensitive Data Leak Detection(trace sensitive data flows across transformations in code to catch PII and PHI leaks in risky data sinks such as logs, files, local storage, third-party SDKs, and AI integrations before code is pushed to production) Sensitive Data Mapping and Data Flow Visualization(automatically map and visualize where sensitive data is stored, processed, and shared across third-party services, AI SDKs, and APIs, using source code as auditable evidence for early risk detection) Shadow AI Discovery(uncover hidden or undocumented AI SDKs and abstractions in code and see exactly what sensitive data is being sent to them, even through complex transformations, to catch risks before data starts flowing) Third Party Data Flows(track sensitive data shared with more than 600 supported third party SDKs, regardless of how deeply nested the data flows are) Automated Privacy Reporting(generate RoPA, PIA, and DPIA reports that are pre-populated with real data flows and identified risks) Compliance FrameworksGDPR, CCPA, ISO 29100, NIST 800 53, HIPAA Alerts & Issue Tracking(get alerts in Slack or email for new sensitive data leaks, DPA violations, or when sensitive data elements are added to the codebase, and automatically create issues with full context in Jira or Linear) IDE Plugins(embed privacy in the earliest stages of development and catch sensitive data leaks as code is being written. Supports VS Code, Cursor, and IntelliJ) CI/CD Integration(e.g. GitHub Actions, GitLab CI/CD) Security Dashboard Integrations(e.g. GitHub Advanced Security Dashboard, GitLab Vulnerability Report) Support Dedicated support: 8x5 Email EnterpriseSign UpContact Us Sensitive Data Leak Detection(trace sensitive data flows across transformations in code to catch PII and PHI leaks in risky data sinks such as logs, files, local storage, third-party SDKs, and AI integrations before code is pushed to production) Sensitive Data Mapping and Data Flow Visualization(automatically map and visualize where sensitive data is stored, processed, and shared across third-party services, AI SDKs, and APIs, using source code as auditable evidence for early risk detection) Shadow AI Discovery(uncover hidden or undocumented AI SDKs and abstractions in code and see exactly what sensitive data is being sent to them, even through complex transformations, to catch risks before data starts flowing) Third Party Data Flows(track sensitive data shared with more than 600 supported third party SDKs, regardless of how deeply nested the data flows are) Automated Privacy Reporting(generate RoPA, PIA, and DPIA reports that are pre-populated with real data flows and identified risks) Compliance FrameworksGDPR, CCPA, ISO 29100, NIST 800 53, HIPAA Alerts & Issue Tracking(get alerts in Slack or email for new sensitive data leaks, DPA violations, or when sensitive data elements are added to the codebase, and automatically create issues with full context in Jira or Linear) IDE Plugins(embed privacy in the earliest stages of development and catch sensitive data leaks as code is being written. Supports VS Code, Cursor, and IntelliJ) CI/CD Integration(e.g. GitHub Actions, GitLab CI/CD) Security Dashboard Integrations(e.g. GitHub Advanced Security Dashboard, GitLab Vulnerability Report) Automated CI Configurations(integrates with GitHub, GitLab, and Bitbucket (cloud and enterprise) to push CI configurations, with support for self-hosted runners and granular controls for scan frequency, pull request comments, and blocking) Managed Scans(integrates with GitHub, GitLab, and Bitbucket (cloud and enterprise) to offload scanning to HoundDog.ai, with on-premises scans handled through the secure HoundDog.ai Broker) Support Priority support with SLA: Email and dedicated private Slack channel FreeStart Free $0 /mo StarterSign Up $100 /yr per developer EnterpriseSign UpContact Us Sensitive Data Leak Detection(trace sensitive data flows across transformations in code to catch PII and PHI leaks in risky data sinks such as logs, files, local storage, third-party SDKs, and AI integrations before code is pushed to production) [limited to specific programming languages and data sinks - see details] Sensitive Data Mapping and Data Flow Visualization(automatically map and visualize where sensitive data is stored, processed, and shared across third-party services, AI SDKs, and APIs, using source code as auditable evidence for early risk detection) [limited to specific programming languages and data sinks - see details] Shadow AI Discovery(uncover hidden or undocumented AI SDKs and abstractions in code and see exactly what sensitive data is being sent to them, even through complex transformations, to catch risks before data starts flowing) Limited to OpenAI, Anthropic, and Gemini Third Party Data Flows(track sensitive data shared with more than 600 supported third party SDKs, regardless of how deeply nested the data flows are) Automated Privacy Reporting(generate RoPA, PIA, and DPIA reports that are pre-populated with real data flows and identified risks) Compliance FrameworksGDPR, CCPA, ISO 29100, NIST 800 53, HIPAA Alerts & Issue Tracking(get alerts in Slack or email for new sensitive data leaks, DPA violations, or when sensitive data elements are added to the codebase, and automatically create issues with full context in Jira or Linear) IDE Plugins(embed privacy in the earliest stages of development and catch sensitive data leaks as code is being written. Supports VS Code, Cursor, and IntelliJ) CI/CD Integration(e.g. GitHub Actions, GitLab CI/CD) Security Dashboard Integrations(e.g. GitHub Advanced Security Dashboard, GitLab Vulnerability Report) Automated CI Configurations(integrates with GitHub, GitLab, and Bitbucket (cloud and enterprise) to push CI configurations, with support for self-hosted runners and granular controls for scan frequency, pull request comments, and blocking) Managed Scans(integrates with GitHub, GitLab, and Bitbucket (cloud and enterprise) to offload scanning to HoundDog.ai, with on-premises scans handled through the secure HoundDog.ai Broker) Support GitHub Issues Dedicated support: 8x5 Email Priority support with SLA: Email and dedicated private Slack channel Offering Details HoundDog.ai CLI Scanner(available on GitHub) FreeStart Free HoundDog.ai Cloud Platform StarterSign up EnterpriseSign Up Sensitive Data Leak Detection(catch PII and PHI leaks in risky data sinks such as logs, files, local storage, third-party SDKs, and AI integrations before code is pushed to production) Extensive pre-defined sensitive data definitions covering PII, PHI, CHD, and auth tokens. See the full list here Free Starter Enterprise Comprehensive rules that detect sensitive data exposures across logs, files, local storage, APIs, third-party SDKs, and AI abstractions, no matter how deeply nested the data flows are. Free [limited to specific programming languages and data sinks - see details] Starter Enterprise Define custom sensitive data types for your organization and adjust the sensitivity levels of built in definitions. Free Starter Enterprise Apply precise allowlists across logs, files, local storage, 600+ third-party SDKs, and AI integrations to enforce your organization’s privacy policies and Data Processing Agreements. Block risky code in your CI pipeline before it is pushed to production and before any data starts flowing. Free Starter Enterprise Sensitive Data Mapping and Data Flow Visualization(evidence-based data maps that show where sensitive data is collected, processed and shared, including through third-party SDKs and AI integrations) Evidence-based Sensitive Datamap Automatically map and visualize where sensitive data is stored, processed, and shared across third-party services, AI SDKs, and APIs, using source code as auditable evidence for early risk detection Free Point-in-time view in the Markdown file Starter Continuously updated with code changes Enterprise Continuously updated with code changes View evidence-based sensitive data maps by code repository, by data element (for example, all code repositories processing Social Security numbers), or by data sink (all code repositories exposing sensitive data in LLM prompts) Free Starter Enterprise Set up alerts when new data elements are introduced based on their sensitivity levels Free Starter Enterprise Sensitive Data Flow Visualization Visualize sensitive data flows across databases, logs, local storage, third party services, AI SDKs, and APIs with direct links to the exact lines of code where risks are detected Free Point-in-time view in the Markdown file Starter Continuously updated with code changes Enterprise Continuously updated with code changes Proactive Privacy Compliance Generate RoPA, PIA and DPIA Generate audit ready Records of Processing Activities (RoPA), Privacy Impact Assessments (PIAs), and Data Protection Impact Assessments (DPIAs), pre-populated with detected data flows and privacy risks aligned with GDPR, CCPA, ISO 29100, NIST 800 53, and HIPAA Free Starter Enterprise Proactive Alerts Receive proactive Slack or email alerts for new sensitive data leaks in risky sinks or when third party and AI data sharing violates your DPAs or privacy notice, all caught in development before code reaches production and before data starts flowing Free Starter Enterprise Receive proactive Slack or email alerts when code changes introduce new sensitive data types based on their sensitivity level Free Starter Enterprise CI/CD Integration GitHub Actions Free Starter Enterprise GitLab CI/CD Free Starter Enterprise CircleCI Free Starter Enterprise Azure Pipelines Free Starter Enterprise Jenkins Free Starter Enterprise Bitbucket Pipelines Free Starter Enterprise Request Other Integrations Security Dashboard IntegrationsSurface findings in existing security dashboards GitHub Advanced Security Dashboard Free Starter Enterprise GitLab Security Dashboard Free Starter Enterprise Request Other Integrations Other Single Sign On (SSO) Free Starter • SAML SSO • Okta, Microsoft Entra ID, and others Enterprise • SAML SSO • Okta, Microsoft Entra ID, and others Audit Logs Free Starter Standardized audit logs for consumption in SIEM Enterprise Standardized audit logs for consumption in SIEM Alerts & Notifications Free Starter Get alerts based on the severity of detected issues in email or on Slack Enterprise Get alerts based on the severity of detected issues in email or on Slack Issue Tracking Free Starter Take actions on detected issues by automatically submitting tickets on Jira, Linear and other issue tracking platforms Enterprise Take actions on detected issues by automatically submitting tickets on Jira, Linear and other issue tracking platforms Automated CI Configurations Free Starter Enterprise Integrate with GitHub, GitLab, and Bitbucket (cloud and enterprise) to push CI configurations, with support for self-hosted runners and granular controls for scan frequency, pull request comments, and blocking Managed Scans Free Starter Enterprise Integrate with GitHub, GitLab, and Bitbucket (cloud and enterprise) to offload scanning to HoundDog.ai, with on-premises scans handled through the secure HoundDog.ai Broker Support Free Starter Dedicated support: 8x5 Email Enterprise Priority support with SLA: Email and dedicated private Slack channel Offering Details HoundDog.ai CLI Scanner(available on GitHub) FreeStart Free HoundDog.ai Cloud Platform StarterSign up EnterpriseSign Up Sensitive Data Leak Detection(catch PII and PHI leaks in risky data sinks such as logs, files, local storage, third-party SDKs, and AI integrations before code is pushed to production) Extensive pre-defined sensitive data definitions covering PII, PHI, CHD, and auth tokens. See the full list here Comprehensive rules that detect sensitive data exposures across logs, files, local storage, APIs, third-party SDKs, and AI abstractions, no matter how deeply nested the data flows are. [limited to specific programming languages and data sinks - see details] Define custom sensitive data types for your organization and adjust the sensitivity levels of built in definitions. N/A Apply precise allowlists across logs, files, local storage, 600+ third-party SDKs, and AI integrations to enforce your organization’s privacy policies and Data Processing Agreements. Block risky code in your CI pipeline before it is pushed to production and before any data starts flowing. N/A Sensitive Data Mapping and Data Flow Visualization(evidence-based data maps that show where sensitive data is collected, processed and shared, including through third-party SDKs and AI integrations) Evidence-based Sensitive Datamap Automatically map and visualize where sensitive data is stored, processed, and shared across third-party services, AI SDKs, and APIs, using source code as auditable evidence for early risk detection Point-in-time view in the Markdown file Continuously updated with code changes Continuously updated with code changes View evidence-based sensitive data maps by code repository, by data element (for example, all code repositories processing Social Security numbers), or by data sink (all code repositories exposing sensitive data in LLM prompts) N/A Set up alerts when new data elements are introduced based on their sensitivity levels N/A Sensitive Data Flow Visualization Visualize sensitive data flows across databases, logs, local storage, third party services, AI SDKs, and APIs with direct links to the exact lines of code where risks are detected Point-in-time view in the Markdown file Continuously updated with code changes Continuously updated with code changes Proactive Privacy Compliance Generate RoPA, PIA and DPIA Generate audit ready Records of Processing Activities (RoPA), Privacy Impact Assessments (PIAs), and Data Protection Impact Assessments (DPIAs), pre-populated with detected data flows and privacy risks aligned with GDPR, CCPA, ISO 29100, NIST 800 53, and HIPAA N/A Proactive Alerts Receive proactive Slack or email alerts for new sensitive data leaks in risky sinks or when third party and AI data sharing violates your DPAs or privacy notice, all caught in development before code reaches production and before data starts flowing N/A Receive proactive Slack or email alerts when code changes introduce new sensitive data types based on their sensitivity level N/A CI/CD Integration GitHub Actions GitLab CI/CD CircleCI Azure Pipelines Jenkins Bitbucket Pipelines Request Other Integrations Security Dashboard IntegrationsSurface findings in existing security dashboards GitHub Advanced Security Dashboard N/A GitLab Security Dashboard N/A Request Other Integrations Other Single Sign On (SSO) N/A • SAML SSO • Okta, Microsoft Entra ID, and others • SAML SSO • Okta, Microsoft Entra ID, and others Audit Logs N/A Standardized audit logs for consumption in SIEM Standardized audit logs for consumption in SIEM Alerts & Notifications N/A Get alerts based on the severity of detected issues in email or on Slack Get alerts based on the severity of detected issues in email or on Slack Issue Tracking N/A Take actions on detected issues by automatically submitting tickets on Jira, Linear and other issue tracking platforms Take actions on detected issues by automatically submitting tickets on Jira, Linear and other issue tracking platforms Automated CI Configurations N/A N/A Integrate with GitHub, GitLab, and Bitbucket (cloud and enterprise) to push CI configurations, with support for self-hosted runners and granular controls for scan frequency, pull request comments, and blocking Managed Scans N/A N/A Integrate with GitHub, GitLab, and Bitbucket (cloud and enterprise) to offload scanning to HoundDog.ai, with on-premises scans handled through the secure HoundDog.ai Broker Support N/A Dedicated support: 8x5 Email Priority support with SLA: Email and dedicated private Slack channel Frequently Asked Questions Sign Up Now What programming languages does HoundDog.ai support? The scanner supports Java, C#, JavaScript, TypeScript, Python, Go, SQL, GraphQL, and OpenAPI / Swagger How can I trust your scanner? Visit our Trust Center to view our latest SOC2 report, penetration testing results, and SBOM details. How are the number of developers measured? A developer is someone who made a commit to your organization's code repository scanned by HoundDog in the past month. Is private source code shared with HoundDog.ai, Inc? No. The HoundDog.ai scanner runs either locally or fully in your CI pipeline, and your source code never leaves your computer or CI environment. If you use our cloud platform, only metadata related to privacy findings will be sent to the HoundDog.ai cloud service. However, this is also optional, as many customers can integrate the scanner into their CI pipelines and surface the security findings on security dashboards without sending any metadata to the HoundDog.ai Cloud Platform. How is your scanner different from Semgrep or CodeQL? DIY SAST tools like Semgrep and CodeQL are powerful and highly customizable, but their rules need significant upfront investment to learn and maintain, especially as the target codebases evolve. HoundDog.ai is a turnkey solution that provides broad, high-quality coverage of data elements and sinks out of the box, greatly reducing the rule authoring burden. It is designed specifically for inter-file data flow analysis, scaling efficiently to large codebases, and detecting complex data flows that general-purpose solutions miss. --- A Proactive Approach to Preventing PII Data Leaks and Automating Privacy Compliance Workflows About UsHoundDog.ai helps organizations proactively detect and prevent the overexposure of sensitive data in high risk mediums that could lead to privacy violations. By embedding detection, enforcement, and audit ready reporting directly into the development process, HoundDog.ai streamlines privacy compliance from day one. Its domain specific static code scanner analyzes code from IDE to CI, identifying sensitive data handling risks before code is deployed. Designed to catch unintentional mistakes by developers or AI generated code, the scanner flags exposure of PII, PHI, CHD, and authentication tokens across often overlooked surfaces such as logs, files, local storage, third party SDKs, and AI specific mediums like LLM prompts and embedding stores, enabling true privacy by design at the code level. Our Mission HoundDog.ai’s mission is to operationalize Zero Trust through proactive data minimization by detecting and eliminating sensitive data risks early in development to prevent privacy violations and costly incidents. As AI and continuous delivery reshape software development, we provide a privacy focused static code scanner that embeds privacy by design into the development workflow. By tracing over 150 sensitive data types from IDE to CI/CD and enforcing allowlist based policies, HoundDog.ai helps organizations prevent exposure across overlooked surfaces such as logs, local storage, third party SDKs, LLM prompts, and embedding stores. The Founding Team Amjad Afanah Amjad Afanah is a serial entrepreneur with a rich background in cybersecurity. He led his first company, DCHQ, a cloud management startup, to acquisition, and later founded APISec.ai, which developed one of the first API security scanners. Before founding HoundDog.ai, Amjad served as the VP of Product at Cyral, a data security platform that implements security controls on production data. His experience at Cyral, coupled with significant feedback from security and privacy teams frustrated by the prevalent reactive approach to data security and privacy—which often remains unaligned with evolving codebases—inspired him to start HoundDog.ai. Joohwan Oh Joohwan Oh is an experienced engineering leader skilled in both scaling services for millions of users and developing new software from scratch. Before joining HoundDog.ai, he was a founding engineer at Aktos, a FinTech startup focused on modernizing the accounts receivable management industry. Joohwan has also led key projects at prominent companies like Facebook, Amazon, and Instacart. Currently, he oversees the development of HoundDog.ai’s cloud platform and the essential AI workflows that significantly enhance our scanner’s accuracy and coverage. Make Privacy-by-Design a Reality in Your SDLC Shift left on privacy with code scanning. Detect PII leaks, map sensitive data flows, and generate GDPR data maps, RoPA, PIA, and DPIA before code reaches production. Start Free Book a Live Demo --- Book a Live DemoComplete this form to set up a quick meeting with us. With HoundDog.ai, you can Embed privacy across all stages of development (from IDE to CI) and catch privacy leaks before any code is pushed to production. Say goodbye to data flows missed by your privacy platform and the endless chasing of app owners to backfill data flows to hidden third-party and AI integrations embedded in code. Maintain a live data flow map for compliance at the speed of development and generate audit-ready RoPA, PIA, and DPIA reports. Finally, data flow mapping that works. At development speed. With no blind spots. Backed by Incredible Investors