Add a connected AI security delivery layer to your consulting practice.
Use selected Workbench experiences, M.A.D.E. delivery patterns, evidence structures, and partner enablement to expand AI product security, adversarial testing, agent authority, remediation, and evidence services under an explicit operating and quality boundary.
Related partner paths
Use consulting for practice enablement and project delivery. Move to private label for branded service delivery or MSSP for recurring managed services.
Keep the advisory relationship. Add the specialist AI security delivery layer.
The consulting partner retains the client relationship, strategic context, account ownership, and broader transformation program. AI Security LLC supplies bounded AI security engineering, testing, evidence, and specialist escalation behind that relationship.
- Consulting partner owns
- Business context
- Stakeholder alignment
- Change management
- Implementation support
- Budget and procurement
- SecEng supplies
- Authority mapping
- Assessment workflows
- Evidence discipline
- Attack-path analysis
- Retest and closure
The joint offer should extend the partner's existing advisory work without forcing the client into a disconnected specialist engagement or transferring account ownership.
Three ways to build the practice
Consulting partners need engagement modes, delivery assets, QA, escalation, and a path from one-time assessments to managed service.
Co-Delivery
The consultancy owns the client and commercial relationship. AI Security LLC supports specialized delivery, review depth, QA, or expert sessions where the engagement needs deeper AI security coverage.
Workbench-Enabled Delivery
The consultancy uses licensed tooling, methods, templates, labs, and evidence structures independently, with defined escalation for product and methodology questions.
Practice Launch
Enablement covers service design, scoping, sales assets, practitioner training, delivery QA, and initial engagements so the firm can launch a repeatable practice.
Carry the engagement through remediation and retest.
A credible joint offer should not stop when findings are delivered. The operating model must preserve ownership, evidence, remediation state, retest results, residual risk, and the next customer decision.
- 1Discovery and context
- 2Scope and evidence plan
- 3Assessment and validation
- 4Findings and path analysis
- 5Remediation roadmap
- 6Implementation support
- 7Retest and verify
- 8Close with residual risk
- Remediate and retest
- Accept documented risk
- Escalate critical issue
- Close with evidence
This creates a repeatable advisory motion in which the consulting partner keeps program continuity while AI Security LLC supports the technical evidence required to validate progress.
Define who delivers, reviews, signs, and communicates.
The consulting partner remains the client-facing advisor and commercial owner. AI Security LLC can support selected technical analysis, evidence production, methodology, review, or productized capability without displacing the advisory relationship.
Client relationship
Owned by the consulting partner.
Engagement scope and commercial terms
Owned by the consulting partner unless jointly contracted.
Technical analysis
Performed by the consulting partner, AI Security LLC, or both as defined in the SOW.
Report authorship
Named explicitly; no silent attribution assumptions.
Finding disputes and retest
Handled through the agreed escalation and validation process.
Client communication
Led by the consulting partner unless direct AI Security LLC participation is approved.
How AI Security LLC shows up behind the engagement
Private-label delivery does not transfer ownership of the OEM Engine, methods, source, internal prompts, detector logic, or unrelated intellectual property.
Visible specialist
AI Security LLC is disclosed as a specialist contributor or subcontractor.
Partner-led delivery
The partner leads the engagement and client communication while AI Security LLC provides approved technical work behind the delivery.
Private-label output
Selected outputs may use the partner brand when the agreement defines attribution, review, quality, and reuse rights.
What the launch pack includes
The route-specific asset is the AI Security Practice Launch Pack, focused on profitable repeatable delivery.
Consultant curriculum
Role-specific training for AI product review, RAG, agents, MCP, evidence generation, report language, and claim-readiness.
Practice launch checklist
Checklist for offer design, sales motion, scope boundaries, delivery roles, QA, escalation, and conversion to recurring services.
Service catalog and SOW templates
Reusable offer descriptions, scoping questionnaires, statements of work, assumptions, exclusions, and acceptance criteria.
Report and evidence-pack examples
Examples for executive summaries, technical findings, remediation plans, evidence packs, and buyer-questionnaire support.
QA and escalation rules
Rules for when partner findings require review, what evidence must not be altered, and how technical escalations are handled.
Path to MSSP
Guidance for converting repeatable consulting demand into customer-org reporting, recurring retainers, and managed-service packaging.
Prove one joint engagement before scaling the offer.
Start with one representative client profile, one bounded service motion, one responsibility model, and one evidence package that both teams can support.
The pilot should prove delivery fit, customer value, handoff quality, support boundaries, commercial coordination, and the ability to move from findings into remediation and retest.
Turn one-off AI reviews into a repeatable practice
Start with the launch pack or scope a co-delivery engagement where AI Security LLC supports specialized delivery behind your client relationship.