compliant-llm
ActiveDetect every data leak into third-party GenAI tools
About
CompliantLLM detects every data leak into third-party GenAI tools used in your company by monitoring employee interactions. Security and tech leaders get visibiliity and control over the data flowing into various Gen AI apps used in their organizations.
compliant-llm provides AI security and compliance solutions for enterprises using GenAI, offering real-time risk assessment, data risk observability, and automated governance to enforce policies and assess vendors. It targets enterprise-level organizations requiring regulatory alignment and threat detection for GenAI usage.
The product offers data-risk observability to gain visibility into GenAI usage, third-party risk management to assess embedded AI vulnerabilities, AI governance to enforce policies across employees and tools, real-time detection of GenAI data exfiltration, adversarial AI risk assessments including multimodal red-teaming, and automated compliance assurance against NIST AI-RMF and ISO 42001 with audit-ready reports.
Who it’s for: Enterprises and large organizations that deploy GenAI tools and need governance, risk management, and compliance across internal and third-party AI usage.
- Data-Risk Observability across GenAI usage
- Real-time data-exfiltration detection
- Automated AI governance across employees and tools
- Vendor risk assessment and insights
- Adversarial AI risk assessment and red-teaming
- Automated compliance testing against NIST AI-RMF and ISO 42001
- Audit trails and compliance reports
Hiring/traction mentioned (enterprise security, automated tests, and governance features); mentions partnerships and demos suggesting active product deployment and sales efforts.
Founders · 2
Building CompliantLLM - Preventing data exfiltration into Gen AI apps. Built AI Customer Support at Uber.
Working on preventing data leaks into Gen AI apps. Was previously building payment systems at Google Pay and AI customer support at Uber.
Launch
Create high-quality datasets for fine-tuning and reinforcement learning.
FiddleCube automates generation of fine-tuning datasets from user data, enabling annotated, augmented, and quality-evaluated datasets for fine-tuning and reinforcement learning of LLMs. It targets users who fine-tune models (e.g., LLaMa, MPT, Falcon) to improve performance, personalization, API/code tasks, and efficiency.
From the original launch (Jul 2023) — may be outdated.
Website over time
Formerly “ZKomm”, “Devpod”, “FiddleCube” · why startups rename →
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