Built RealGround's AI-Native Cybersecurity Platform in 14 Weeks — 80+ AI Security Assessments in 6 Months
RealGround — AI-Native Cybersecurity Platform
“Foreignerds understood that AI security isn't traditional cybersecurity with an AI label. They built a platform that evaluates the risks that actually matter — prompt injection, agent permission sprawl, embedding data leakage. The daily threat intelligence alone has become essential reading for our clients. We went from concept to 80 assessments in 6 months.”
— Founder & CEO, RealGround (CISSP, CEH)
The Background
RealGround is a US-based AI cybersecurity company founded by a CISSP- and CEH-certified security veteran with 25+ years of experience. The company focuses on SMBs and AI startups deploying AI agents, providing services including AI red teaming, agent security audits and LLM hardening.
Foreignerds built the complete RealGround platform to productize those security workflows into a single SaaS environment covering AI security assessment, threat intelligence, security policies, AI CISO guidance and risk-posture monitoring.
| Team Size | 4-member development team |
|---|---|
| Volume | 80+ AI security assessments completed within 6 months; beta deployed across 10 clients |
| Engagement | Full platform development + $5,000/month retainer |
| Platform Access | Live product at realground.com — assessment demo available on request |
The Challenge
- AI systems introduced new security considerations — the project brief identified risks such as prompt injection, unauthorized tool execution, embedding-related data leakage and unmanaged AI supply-chain exposure, requiring the platform to assess AI systems across architecture, permissions, data flows and external integrations.
- Agent permissions could create significant exposure — AI agents with write access to production databases, CRM systems and financial tools could create significant security exposure if compromised, making permission analysis and integration review important parts of the assessment process.
- SMBs and AI startups needed an AI-specific security workflow — the project brief identified a need for a platform that could assess AI-specific risks, generate security policies and provide ongoing risk visibility for organizations that did not necessarily maintain large internal security teams.
- Threat intelligence needed to become operational — RealGround needed to ingest AI-security news, CVEs and emerging attack patterns continuously enough to publish useful daily intelligence rather than rely on periodic manual research.
- Security guidance needed to be available on demand — the platform needed an AI-assisted security guidance layer for questions involving AI-agent security, compliance-related topics and security best practices.
RealGround needed to turn its expertise into a repeatable product workflow: assess, score, prioritize, remediate, monitor, advise.
Our Approach & Technical Decisions
AI Security Assessment Engine
Choice: AI-specific assessment and scoring engine. Why: Securing an AI agent requires examining more than the underlying model. The engine evaluates agent architecture, permissions, data flows and integration points against RealGround’s proprietary risk framework and produces prioritized remediation plans. The framework is not claimed to be industry-certified or independently benchmarked, since the source does not establish that.
Multi-Source Threat-Intelligence Pipeline
Choice: Automated intelligence ingestion. Why: AI security changes quickly, requiring a repeatable way to monitor new developments. The pipeline ingests AI-security news, CVEs and attack patterns from 50+ sources, uses LLMs to analyze relevance, and produces daily briefings with RealGround analysis.
AI CISO Assistant
Choice: Conversational security-guidance layer. Why: Smaller organizations may need on-demand access to AI-security expertise without a dedicated security executive available for every question. The AI CISO assistant answers questions about AI-agent security, compliance-related topics and security best practices — positioned as an on-demand security guidance layer, not a replacement for qualified security leadership.
Organization-Specific Security Policy Generation
Choice: AI-assisted policy generator. Why: Security policies need to reflect an organization’s actual architecture and risk profile. The platform generates customized AI-security policies, data-handling procedures and incident-response plans based on the organization’s technology stack and assessed risk profile.
Risk-Posture Monitoring Dashboard
Choice: Centralized security dashboard. Why: Assessments become more useful when organizations can track their risk posture over time. The dashboard tracks AI-agent risk posture, flags newly identified vulnerabilities and surfaces prioritized remediation recommendations — described as risk-posture monitoring, without implying a specific real-time monitoring SLA.
Challenge Encountered
The supplied project documentation does not record a specific production failure, major architecture reversal or material mid-project technical setback. The documented engineering complexity was bringing several security functions together as one operating platform: assessment, risk scoring, threat intelligence, policy generation, AI guidance and risk monitoring. The system also needed to convert technical findings into prioritized remediation actions rather than stopping at a static assessment report. No fictional security incident, model failure or architecture pivot has been added because the source does not document one.
Implementation Timeline
RealGround’s platform was developed over 14 weeks across five implementation phases. The source establishes this plan but does not provide planned-versus-actual schedule variance.
Measurement & Attribution
The problem section is deliberately qualitative rather than quantified: the source does not supply baseline figures such as assessment time, cost per assessment, security-team hours, or consultant spend before RealGround, so none are invented. The 340+ figure is described consistently as AI-specific risks identified, never as vulnerabilities, attacks prevented or breaches detected. The 2,500+ monthly AI CISO queries are reported as usage evidence, not as a measured reduction in consultant cost or hours. The 3 enterprise advisory contracts are reported as a direct assessment-to-advisory result with no invented conversion percentage. AWS is described only as cloud infrastructure and data storage — no SOC 2, encryption-certification or other regulatory/security certification claim is made, since the source does not provide sufficient evidence for one. The source’s pricing comparison to Palo Alto and CrowdStrike is not used, since no pricing research was supplied.
Competitive Benchmarking
No independent competitor benchmark or verified market comparison was supplied in the project source. The strongest defensible comparison is the change from a fragmented AI-security workflow to an integrated platform — see the Competitor / Market Benchmarking section below.
The Takeaway
RealGround is an AI-security operating platform, not simply a cybersecurity product. It turns AI-agent risk assessment into a repeatable workflow of identify, prioritize, remediate and monitor. Within six months of launch, the platform completed 80+ AI security assessments, identified 340+ AI-specific risks, handled 2,500+ monthly AI CISO queries, and converted assessment engagements into 3 enterprise advisory contracts.
Implementation Timeline
Technology Stack
Measurable Results
- 80+ AI security assessments completed within six months of launch across SMBs and AI startups in healthcare, fintech and SaaS
- Threat-intelligence pipeline automated across 50+ sources, publishing daily threat-intelligence briefings with RealGround analysis
- 340+ AI-specific security risks identified across client assessments, with prioritized remediation plans attached (reported risk findings, not a claim of independently confirmed exploitable vulnerabilities)
- 2,500+ monthly AI CISO queries handled, providing on-demand security guidance (no measured reduction in consultant hours or security spend is claimed)
- 3 enterprise advisory contracts signed directly from assessment engagements, evidencing an assessment-to-advisory expansion model (no conversion rate calculated, since the denominator is not supplied)
- Assessment findings connected to an ongoing workflow of prioritized remediation, security policies, data-handling procedures, incident-response plans and risk-posture monitoring
Post-Launch & Ongoing Engagement
Foreignerds continues as RealGround’s platform engineering partner on a $5,000/month retainer. The ongoing engagement covers new assessment modules (expanding the types of AI systems and risk scenarios the platform can assess), threat-pipeline expansion (adding new intelligence sources and improving AI-security analysis workflows), and enterprise feature development (extending platform capabilities for larger security and advisory engagements).
