Noma

A security platform for the full AI lifecycle that prioritizes visibility and risk mitigation across data, models, and code—best for enterprises governing fragmented AI usage.

Excellent for security teams needing to map shadow AI and secure model supply chains, weaker for developers seeking a simple, plug-and-play prompt firewall.

Cybersecurity Ai Governance Compliance Llm Security Mlops Risk Management Enterprise

Analysis based on product data, pricing structure, traffic signals, and public user sentiment.

Visit Website

Share this tool

Facebook X

LinkedIn Reddit

WhatsApp Telegram

Who Should Use Noma?

Typical users

Security engineers, CISOs, and DevSecOps teams at mid-to-large enterprises with multiple AI initiatives across different departments.

Maturity fit

scaling to advanced

Choose this if…

Your priority is securing the entire pipeline from training data to production
You need to discover 'shadow AI' assets hidden across your cloud environment
You must comply with the EU AI Act or NIST AI Risk Management Framework

Skip this if…

You only use a single managed LLM service like OpenAI and don't build custom pipelines
You require a low-cost, self-serve tool for a small-scale project
Your workflow is strictly limited to basic chatbot wrappers without complex data integrations

About Noma

Noma is an AI Security Posture Management (AI-SPM) platform designed to protect the complete AI development lifecycle. It addresses the security gaps created by the rapid adoption of LLMs and machine learning models within enterprise environments. The platform focuses on identifying risks in data, models, and infrastructure before they reach production.

Official profiles

X (Twitter) LinkedIn

What it actually does

It automatically discovers AI assets across an organization's ecosystem, including models, datasets, and applications. Once discovered, it scans for vulnerabilities such as prompt injection, data leakage, and supply chain threats, while providing continuous monitoring and compliance reporting.

What makes it different

Unlike many competitors that focus solely on the 'firewall' layer of LLM prompts, Noma secures the underlying supply chain. It treats AI security as a holistic problem involving data integrity and model provenance, rather than just a runtime filtering task. This architectural choice makes it more relevant for teams building their own models or fine-tuning existing ones.

Automated AI asset discovery Model supply chain vulnerability scanning PII and sensitive data detection in training sets Real-time prompt injection and jailbreak protection Compliance mapping for EU AI Act and NIST Risk prioritization based on business context Integration with CI/CD pipelines for secure ML development

Key Features

Shadow AI Discovery

Finds undocumented AI models and tools used by employees without IT approval.

Data Leakage Prevention

Identifies and masks sensitive information before it is ingested by models.

Supply Chain Protection

Scans third-party models and libraries for malicious code or hidden vulnerabilities.

Threat Detection

Monitors live AI applications for adversarial attacks and anomalous behavior.

Governance Dashboards

Provides a centralized view of AI risk posture for executive reporting.

Automated Remediation

Suggests specific fixes for identified security gaps in the AI stack.

Pricing

Popular

Enterprise

Custom Annual

Full AI asset discovery
Supply chain security scanning
Real-time threat protection
Compliance reporting
Dedicated support

Pricing checked 4 months ago

Pricing guidance

Best plan for most users: The Enterprise plan is the only option, making it a high-intent purchase for organizations with significant AI investment.

Free plan enough? No — there is no public free tier or self-serve trial available.

Upgrade when:

When moving from AI experimentation to production
When facing an external audit or compliance deadline
When the number of internal AI projects exceeds manual tracking capabilities

Watch out for:

Pricing likely scales based on the number of models or data volume
Custom integrations may require professional services fees

Premium enterprise positioning justified by the breadth of the security coverage.

Pros & Cons

Strengths

Full-lifecycle visibility
By covering data, models, and code, Noma prevents security silos that occur when teams only protect the application layer.
Regulatory readiness
Built-in frameworks for the EU AI Act help legal and compliance teams manage new requirements without manual auditing.
Supply chain focus
Addresses the specific risk of poisoned models or malicious packages in the ML stack, which standard cloud security tools often miss.

Weaknesses

High implementation overhead
The depth of the platform requires significant integration effort across cloud providers and development environments.

Affects: Small teams with limited DevOps resources
Opaque pricing model
Lack of public pricing or a self-serve tier makes it difficult for teams to evaluate the tool without a lengthy sales process.

Affects: Early-stage startups and individual developers
Potential for alert fatigue
Broad discovery tools can flag numerous low-risk assets, requiring careful tuning to avoid overwhelming security analysts.

Affects: Security Operations Center (SOC) teams

Real User Sentiment

Early feedback from security professionals is positive regarding the platform's ability to provide visibility into 'shadow AI' that other tools miss.

Users tend to like

Comprehensive visibility across the ML stack
Strong focus on the EU AI Act compliance
Ability to find hidden AI usage in cloud environments

Users commonly complain about

Lack of transparent pricing
Complexity of initial setup
Enterprise-only focus

Recurring tradeoffs

Users trade simplicity for depth; it is more complex than a basic LLM firewall but offers much more data protection.

Happiest users

CISOs at regulated companies who need a single pane of glass for all AI-related risks.

Often frustrated

Developers looking for a quick API to block prompt injections on a weekend project.

Use Cases

Shadow AI Discovery

Finding and securing unauthorized LLM usage across a 5,000-employee company.

Compliance Auditing

Generating reports to prove adherence to the EU AI Act for a fintech application.

Secure Model Fine-tuning

Scanning training datasets for PII before fine-tuning a proprietary model.

Supply Chain Hardening

Verifying that open-source models downloaded from Hugging Face do not contain malicious code.

Production Monitoring

Blocking adversarial attacks and prompt injections on a customer-facing AI agent.

Frequently Asked Questions

How does Noma compare to Wiz?

Wiz is a broad Cloud Native Application Protection Platform (CNAPP) that has added AI security features. Noma is a specialist tool that goes deeper into the AI lifecycle, specifically focusing on model supply chains and training data integrity that broad tools may overlook.

Does Noma offer a free trial?

Noma does not offer a public, self-serve free trial. Interested users must request a demo through their website to discuss enterprise requirements and potential POC (Proof of Concept) arrangements.

What integrations does Noma support?

Noma integrates with major cloud providers (AWS, Azure, GCP), code repositories (GitHub, GitLab), and ML platforms like Hugging Face and Databricks to monitor the full development pipeline.

Can Noma prevent prompt injection?

Yes, Noma includes a runtime protection layer that monitors inputs and outputs for prompt injection, jailbreaking, and other adversarial techniques designed to bypass LLM safety filters.

Is Noma suitable for small startups?

Probably not. Noma is built for enterprise-scale problems like shadow AI and regulatory compliance. Small startups with simple AI implementations may find the platform's complexity and cost exceed their current needs.

How does Noma handle data privacy?

Noma identifies and redacts sensitive data (PII, PHI, PCI) within the datasets used for AI training and fine-tuning, ensuring that sensitive information is not memorized by the model.

Why trust this page?

This evaluation combines product positioning, pricing analysis, traffic and market signals, and public user sentiment into a single decision-support page. Content is generated editorially — not copied from the vendor's website.

Funding & Company

Founded

2023

Stage

Series b

Total Raised

$132M

Latest Round

Series B (Jul 2025)

Notable Investors

Evolution Equity Partners Ballistic Ventures Glilot Capital Partners Databricks Ventures SVCI - Silicon Valley CISO Investments

Noma Security has raised a total of $132 million across three disclosed funding rounds, culminating in a significant $100 million Series B in July 2025. This substantial backing from cybersecurity-focused investors like Evolution Equity Partners and Ballistic Ventures provides a long runway for product development and market expansion in the AI security sector.

Full funding report high confidence

Market Signals & Traffic

Estimated visits, global rank, geography, traffic sources, monthly visit trends, and organic search keywords (Similarweb)—on a dedicated page built for depth and search.

Estimated visits: 46,858
Global rank: #664,103
Snapshot: Apr 2026
Traffic trend: Steady