Sourcing Secure AI technology - the right way.
The AI stack has created a new attack surface that didn't exist 24 months ago. Over 100 vendors have entered AI security - many with overlapping claims, limited enterprise track records, and marketing that outpaces product reality. Evaluating this market without independent research is nearly impossible. We've already done the work.
AI Security · AI Governance · AI Firewall · AI-SOC · AI Data Security
Questions We Help You Answer
- ?Which AI security vendors are genuinely enterprise-ready vs. pre-production?
- ?How do I build an AI governance program that will hold up under EU AI Act audit?
- ?Should I buy AI Security, AI Governance, and AI Data Security from one vendor or three?
- ?How do I evaluate an AI Firewall without a dedicated AI security team?
- ?What's the right sequence for building out an AI-SOC capability?
The Challenge
Why Secure AI sourcing is harder than it looks.
Vendor proliferation with no differentiation signal
More than 100 vendors now claim to 'secure AI.' Most enterprise buyers can't distinguish between a genuine platform and a point tool with AI branding. Without independent evaluation criteria, every vendor looks plausible in a demo.
No standardized evaluation criteria
Unlike mature markets like SASE or MDR, AI security has no established RFP framework. Buyers are writing requirements from scratch against a landscape they're still learning. Vendors shape that process if given the chance.
Speed pressure creates bad decisions
Boards and regulators are pushing CISOs to 'do something about AI risk' on short timelines. That urgency drives reactive buying - whoever gets to the CISO first with a credible-sounding solution often wins, not whoever has the best product.
Governance and security are converging
AI Security, AI Governance, and AI Data Security are increasingly overlapping. Buying them in silos creates gaps and redundant spend. The right sourcing strategy considers the full AI risk stack - not just one layer.
Categories We Source
What we help you buy - and how.
AI Security
Platforms that detect, prevent, and respond to AI-specific threats - prompt injection, model poisoning, agentic exploit chains, and AI supply-chain compromise.
The Buying Challenge
Claims are easy to make and hard to verify. Most enterprises don't have the internal expertise to run a technical POC that distinguishes real AI threat detection from repurposed endpoint tooling.
How Stackcurve Helps
We shortlist vendors with genuine AI-native detection (not relabeled EDR), run structured POC criteria, and benchmark claims against our CURVE(TM) evaluation data.
Start a AI Security engagement →AI Governance
Platforms that provide model registration, risk classification, bias auditing, explainability, and board-level reporting - covering EU AI Act, SEC disclosure, and NIST AI RMF compliance.
The Buying Challenge
Regulatory requirements are still evolving. Vendors are ahead of the compliance curve on marketing and behind it on product depth. Buyers are at risk of purchasing a compliance checkbox that won't hold up in an audit.
How Stackcurve Helps
We map your specific regulatory exposure (EU AI Act vs. SEC vs. NIST), identify vendors with genuine coverage vs. superficial compliance theatre, and build requirements aligned to your actual audit obligations.
Start a AI Governance engagement →AI Firewall
Purpose-built controls that inspect, filter, and enforce policy on AI inputs and outputs - sitting between users and AI models to prevent data leakage and policy violations.
The Buying Challenge
This is an emerging category with wide quality variance. Some products are mature; many are pre-production. Distinguishing enterprise-ready from lab-stage requires hands-on evaluation the buyer rarely has time for.
How Stackcurve Helps
We maintain current state of the market and shortlist only vendors with enterprise production deployments. We build the evaluation criteria and run structured vendor comparison.
Start a AI Firewall engagement →AI-SOC
AI-native security operations platforms that automate alert triage, threat correlation, and incident response - purpose-built to address analyst capacity constraints.
The Buying Challenge
Every SIEM and SOAR vendor has relabeled their product as 'AI-powered.' Distinguishing native AI operations capability from a marketing overlay requires deep technical evaluation.
How Stackcurve Helps
We separate AI-native platforms from AI-branded legacy tools, run structured capability scoring aligned to your SOC maturity, and benchmark against our CURVE(TM) data.
Start a AI-SOC engagement →AI Data Security
Controls that protect enterprise data as it flows through AI pipelines - training datasets, RAG datastores, inference logs, and output caches - against leakage, poisoning, and unauthorized access.
The Buying Challenge
The boundary between DSPM, DLP, and AI data security is blurring. Many buyers are buying three tools when one well-selected platform could cover all three.
How Stackcurve Helps
We map your AI data flow, identify the specific exposure points, and source a platform that covers the full pipeline - not just the layer the vendor demo focused on.
Start a AI Data Security engagement →The Research Behind the Sourcing
Relevant CURVE(TM) Reports - free to download
AI Security CURVE(TM)
2026 · Secure AI
14 vendors plotted on the CURVE(TM). Frontier leaders, rising challengers, and the vendors building defenses at the speed the threat demands.
AI Governance CURVE(TM)
2026 · Secure AI
Board-level accountability for AI risk. Regulatory wave mapping, governance platform landscape, and CURVE(TM) placements.
Data Security for AI CURVE(TM)
2026 · Secure AI
Protecting the data pipelines that feed the models. From training data to RAG datastores to inference output.
Ready to start a Secure AI sourcing engagement?
Tell us the category and your timeline. We'll ask the right questions and come back with an approach. No obligation - and we respond within one business day.