NEW

Start with the pressure: sales, launch, abuse, agents, data, or guardrails

Platform Partner · White-Label

Your platform trains. We make the training legible to employers.

AI Security Workforce Readiness is a white-label intelligence layer for cybersecurity training platforms, cyber ranges, and enterprise training companies. We provide the role taxonomy, Q&A bank, job-market signals, hiring calibration methodology, and workforce reporting model. Your platform keeps the brand, the learners, and the customer relationship.

The gap training platforms leave behind: practitioners finish labs and certs but don't know which AI security role they're ready for or where to apply. Employers buy training seats but can't build a calibrated hiring process or explain to their board what AI security capability they've built. This fills both gaps — under your brand.

The gap training platforms leave

Lab scores prove performance. They don't explain what the performance is worth.

No AI security role taxonomy

Practitioners don't know which role they're heading toward or what employers call it. Your platform has content, not career destination clarity.

No employer calibration product

Enterprise customers buy seats, complete training, then have no way to design a calibrated AI security interview loop or justify headcount to their board.

No live market intelligence

Practitioners and enterprise buyers don't know what companies are actually hiring for right now — title language, skill demands, or role-market signals.

No AI security knowledge layer

Labs test what practitioners can do. Scenario-based Q&A tests whether they can reason through adversarial AI problems, governance decisions, and evidence calls.

No workforce evidence output

CISOs buying enterprise training plans can't produce a workforce readiness summary or board-facing evidence that shows their AI security capability was built.

First-mover window is closing

AI security as a role category is still being defined. Platforms that own the taxonomy and role intelligence now own the career narrative as the market matures.

Integration architecture

Three platform surfaces. One white-label layer.

The workforce readiness layer activates independently across practitioner, certification, and enterprise surfaces. You can start with one and expand to all three. Each surface has a clear integration seam with existing platform infrastructure.

Practitioner dashboard layer

What does my performance mean for real AI security jobs?

Embed role readiness profiles, live job-market signals, and career path intelligence directly into the practitioner experience. Practitioners see which AI security roles match their current training, which companies are actively hiring, and exactly what skills the market is asking for — without leaving your platform.

Modules included

Job Navigator
NIST NICE Career Explorer
Role Readiness Profile
Training path recommendations

Integration point

Maps to: practitioner home, track completion screens, profile page

Certification and credentialing layer

Can they reason through AI security problems, not just execute labs?

Add an AI security knowledge screen to your certification flow. The Q&A Credential Bank provides scenario-based items across RAG security, agentic workflows, secure AI SDLC, governance, adversarial risk, and evidence handling — testing judgment that labs alone don't surface. Completion of the knowledge screen is a readiness signal, not a formal certification or compliance credential.

Modules included

Q&A Credential Bank (300–500 items)
Domain mapping to NIST NICE + AIPSA
Difficulty banding
Readiness diagnostic

Integration point

Maps to: pre-cert screens, learning path checkpoints, certification exams

Enterprise and admin layer

What AI security capability does our team actually have right now?

Give your enterprise customers a workforce evidence product they can take to their boards. Hiring calibration workshops help their hiring managers define the real AI security role and build a calibrated interview loop. Workforce reports turn training completion data into a skill gap map, readiness summary, and planning document.

Modules included

Hiring Calibration Workshop
Workforce Intelligence Report
Team readiness map
Role architecture + JD rewrite

Integration point

Maps to: enterprise admin portal, L&D reporting, CISO dashboards

Platform fit example

How it maps to a training platform product line

For a platform with Academy (learning paths), competitive labs, certification tracks, and enterprise seats — the integration layer looks like this.

Your platform surface

Our workforce intelligence layer

Academy (learning paths)

Our role taxonomy maps every learning path to AI security job functions. Practitioners finish a track and see exactly which roles they're ready for and what's missing.

Labs and competitive play

Job Navigator shows practitioners which companies hire people with their lab performance profile — live role demand against their specific skill set.

Certifications (CPTS, CBBH, CDSA)

Our Q&A bank adds an AI security knowledge screen before cert issuance — testing reasoning and judgment that lab performance alone doesn't surface.

Enterprise (corporate seats, L&D)

Hiring Calibration Workshop and Workforce Reports become enterprise-tier features. CISOs get role definitions and team readiness evidence; hiring managers get calibrated interview loops.

What partners receive

Eight deliverables. All white-labeled.

AI Security Role Taxonomy

A structured set of AI security role archetypes — AI Product Security Engineer, AI Red Teamer, AI Governance Analyst, RAG Security Specialist, AI Safety Engineer, and more — with NICE-aligned KSA crosswalks, AI security extensions, and market-calibrated skill language. Maps directly onto your existing learning paths.

Q&A Credential Bank

300–500 scenario-based knowledge items across AI security domains: RAG boundaries, agentic workflows, prompt injection, AI SDLC, governance evidence, adversarial risk, and buyer review. Difficulty-banded, domain-mapped, white-labeled. Ready to embed in certification checkpoints, pre-course screens, or standalone assessments.

Job Navigator Data Layer

Live job-market intelligence — title normalization, role archetypes, hiring demand, skill-demand signals — drawn from 300K+ AI security job postings. Practitioner-facing view shows which roles they're ready for and where companies are hiring. Enterprise-facing view shows L&D teams what the market is hiring for.

Readiness Diagnostic Engine

A scored readiness flow that takes practitioners from role target → knowledge check → work-style signal → market calibration → interview practice → training path → evidence portfolio. White-labeled flow, your scoring model, our content. Configurable by role and training track.

Hiring Calibration Methodology

A facilitated workshop model that teaches your enterprise customers how to define the AI security role, rewrite the JD, build a calibrated interview loop, and score candidates consistently. Delivered by aisecurity.llc under your enterprise program brand. New revenue surface for your enterprise tier.

Workforce Intelligence Report

A template and methodology for team-level readiness reporting. Enterprise customers get a role-capability baseline, skill gap map, recommended training priorities, and a readiness summary they can present to their security leadership or board.

Admin and Export Schema

All diagnostic outputs, Q&A results, role profiles, and readiness scores are available in a structured schema your engineering team can ingest, render, and store. API-ready where live data is involved; file-based delivery where content is static.

Partner SOW and Implementation Support

A production-scoped SOW, integration architecture walkthrough, and implementation support for each surface you activate. We handle content delivery and methodology; your team controls the UX and platform experience.

Partner types

Who this is built for

Cybersecurity training platforms

Add an AI security workforce intelligence layer your competitors don't have. Turn training completion into role readiness, career direction, and hiring evidence.

Cyber ranges

Explain what lab performance means for real AI security roles, job-market demand, and enterprise workforce decisions. Close the gap between 'scored well' and 'ready to hire'.

Certification providers

Add an AI security knowledge bank to your certification infrastructure. Scenario-based Q&A items that test judgment, not recall.

Enterprise training companies

Give your corporate customers a hiring calibration product and workforce reporting layer. A new enterprise revenue surface alongside your existing seat-based model.

Talent and hiring platforms

Layer role taxonomy and readiness scoring onto candidate profiles. Show employers what practitioners are actually ready for in AI security.

Partner business case

New features. New revenue surface. First-mover position in AI security workforce.

New enterprise upsell

Hiring Calibration Workshop and Workforce Reports become premium enterprise features. CISOs buy them separately from seat-based training. New ACV line without building new infrastructure.

Certification differentiation

An AI security knowledge screen in your certification process distinguishes your certs from competitors. 'Passed the Q&A screen' is evidence that labs alone can't provide.

Practitioner retention

Role readiness profiles and live job-market signals give practitioners a reason to stay engaged between lab completions. Career direction drives retention.

Enterprise renewal driver

Workforce reports give enterprise customers a board-ready evidence artifact. They come back to renew when they can show their leadership what AI security capability they've built.

AI security category ownership

First platform with a coherent AI security role taxonomy and job-market intelligence owns the category narrative. The window to establish that position is now.

Hiring manager expansion

Hiring managers who calibrate interview loops through your platform become buyers of enterprise seats for their new hires. Workforce intelligence creates a new acquisition loop.

Partner packages

Start with a pilot. Scale to full integration.

Pilot

2 weeks

$25k–$40k

Integration validation and platform scoping before full commitment.

  • 5 AI security role profiles with NICE mapping
  • 100 Q&A items across 3 domains
  • 1 diagnostic flow (practitioner-facing)
  • 1 hiring rubric pack
  • Job Navigator integration architecture spec
  • 1 CORE interview-practice sample set
  • White-label product spec + SOW template

Platform Integration

Most common

4–8 weeks

$180k–$350k+

Full three-surface integration across practitioner, certification, and enterprise layers.

  • Full AI security role taxonomy (12+ role archetypes)
  • 300–500 Q&A items, domain-mapped, difficulty-banded
  • Readiness diagnostic engine (configurable by role/track)
  • Job Navigator data layer integration spec
  • Hiring Calibration Workshop methodology + facilitation model
  • Workforce Intelligence Report template
  • Admin/export schema for all outputs
  • Partner branding on all content and flows
  • Implementation support across all three platform surfaces
  • Enterprise enablement materials for your sales team

Strategic License

By negotiation

By negotiation

IP license, acquisition option, or long-term exclusivity arrangement.

  • Everything in Platform Integration
  • IP license or acquisition option (separately negotiated)
  • Exclusivity window by vertical (cyber range, certification, marketplace)
  • Co-development roadmap for additional AI security workforce modules
  • Named partner co-marketing rights

How it works

You own the platform. We own the content.

The division of labor is clean: aisecurity.llc provides role taxonomy, Q&A content, job-market data, methodology, and implementation support. Your team controls the UX, the platform architecture, and the customer relationship. Nothing about how you build your platform changes — we plug into the surfaces you already have.

01

Platform scoping

We map your platform surfaces — learning paths, cert flows, enterprise admin — to the three integration points. Output: integration spec and SOW.

02

Content delivery

We deliver role taxonomy, Q&A bank, diagnostic flow, and reporting templates in your agreed format. All white-labeled to your brand.

03

Engineering integration

Your team integrates the content and data layer into your platform. We provide schema documentation, sample API calls, and integration support.

04

Go-to-market enablement

We equip your sales team with positioning, enterprise pitch decks, and hiring calibration workshop delivery support for enterprise customers.

The AI security workforce layer. Your brand.

Request the platform partner pack — a scoped proposal covering which integration surfaces apply to your platform and what the implementation path looks like.