Consulting and Services
We help teams move from AI risk discussion to control implementation, telemetry evidence, and delivery-safe remediation plans.
Architecture-first
Use the service cards when you already know the surface. Use the tracks when you need the right lane first.
Proof-linked
Every lane now links to portfolio proof and people fit instead of stopping at a brochure card.
Operational
Pricing, duration, availability, and case-study references are surfaced where they help a buyer make a decision.
Portfolio proof
A selection of public-safe case studies, research, and implementation proof.
Annual analysis of AI security posture, risks, and controls across 60+ portfolio proofs.
Built and scaled a greenfield product security function into a 90-day delivery cadence.
Trust-boundary, content isolation, and data-path security review for a privacy-first browser.
Service tracks
The top-level tracks are where price bands, availability, duration, and proof links live. The deeper service cards below are for the detailed lane selection.
Architecture Review
Deep-dive product architecture, controls design, telemetry roadmap
Duration
2–4 weeks
Price band
$25,000-$50,000
Proof
Splunk Product Security Program Buildout
Featured proof: Program buildout, control evidence, and execution-grade security proof.
Program Advisory
Ongoing governance, hiring, and operating model support
Duration
Monthly retainer
Price band
$5,000-$15,000
Proof
Splunk Product Security Program Buildout
Featured proof: Program buildout, control evidence, and execution-grade security proof.
Rapid Assessment
1-day to 1-week focused audit or review
Duration
1–7 days
Price band
$8,000-$15,000
Proof
Browser-Native Trust Boundary Security Model
Featured proof: Trust-boundary, permissioning, and product-security proof.
Red Team
Validation before launch or investor/audit readiness
Duration
2–4 weeks
Price band
$20,000-$75,000
Proof
Agentic Browser Security Assessment
Featured proof: Delegated-action and browser-native assessment proof.
Compare options
| Metric | Rapid | Architecture | Engineering | Advisory | Red Team |
|---|---|---|---|---|---|
| Duration | 1-7 days | 2-4 weeks | 4-8 weeks | Monthly cadence | 2-4 weeks |
| Primary output | Findings + priority backlog | Architecture risk map + remediation plan | Implementation-grade controls and telemetry | Operating model + governance loop | Adversarial report + fix verification |
| Best fit | Early-stage launches | Complex AI product systems | Teams shipping controls into production | Program-level maturity | Pre-launch or diligence proof |
| Investment range | $8K-$15K | $25K-$50K | $25K-$60K | $5K-$15K/mo | $20K-$75K |
Service catalog
Focused validation for active AI product timelines.
rapid assessment
Assess a retrieval-augmented generation system across ingestion, indexing, retrieval, permissions, prompt assembly, source attribution, and evidence capture. The output is a practical design review and remediation backlog.
Outcome
7 deliverables
Best for
AI Engineering Lead, Product Security, Security Architect, Platform Security
rapid assessment
A structured threat modeling sprint for LLM apps, copilots, RAG systems, assistants, AI workflows, and AI-enabled product features. The sprint converts ambiguity into concrete abuse cases, controls, and engineering tasks.
Outcome
6 deliverables
Best for
Product Security, AppSec, AI Engineering, Security Architecture
Deep-dive analysis for architecture, controls, and telemetry design.
architecture review
Review an AI-enabled product or feature before it becomes an incident. We map trust boundaries, data flows, model/provider dependencies, authorization paths, abuse cases, logging gaps, and remediation priorities.
Outcome
7 deliverables
Best for
CISO, Head of Product Security, VP Engineering, AI Platform Lead
architecture review
Review agentic workflows where models can call tools, take delegated action, access enterprise systems, or trigger automation. We focus on authorization, approvals, sandboxing, audit trails, rollback, and blast-radius limits.
Outcome
8 deliverables
Best for
CISO, AI Platform Lead, Product Security, Architecture Lead
architecture review
Build the secure development lifecycle for AI products: architecture review gates, threat modeling, eval gates, data and model controls, release criteria, incident hooks, and customer evidence expectations.
Outcome
8 deliverables
Best for
CISO, Product Security Lead, VP Engineering, CTO
Implementation work for teams that need controls, telemetry, and release gates in production.
rapid assessment
Design the telemetry and evidence layer that makes AI security governable. We define prompt, response, retrieval, tool-call, eval, approval, and remediation records that support detection, audit, customer assurance, and operating reviews.
Outcome
8 deliverables
Best for
Security Engineering, Detection Engineering, GRC, AI Platform
Adversarial validation of RAG, agents, tool permissions, and prompt-path abuse cases.
red team
Offensive validation for direct prompt injection, indirect prompt injection, retrieval poisoning, cross-tenant leakage, source spoofing, context manipulation, and unsafe tool-output handling.
Outcome
7 deliverables
Best for
CISO, Red Team, Product Security, AI Engineering
red team
Attack delegated-action AI workflows before they attack your customers, data, or production systems. We test tool misuse, approval bypass, confused-deputy paths, unsafe automation, connector abuse, and recovery controls.
Outcome
8 deliverables
Best for
CISO, Red Team Lead, Product Security, AI Platform Lead
red team
Assess the trust chain behind models, adapters, datasets, notebooks, plugins, containers, and updates. We focus on provenance, unsafe formats, artifact loading, registry controls, and reproducible build evidence.
Outcome
7 deliverables
Best for
ML Platform, Product Security, AppSec, Supply Chain Security
red team
Evaluate how an AI feature can be misused, abused, or steered around intended safety policies. We test harmful automation paths, jailbreak resistance, policy bypass, rate-limit abuse, and customer-facing safeguards.
Outcome
6 deliverables
Best for
Trust and Safety, Product Security, CISO, AI Product Lead
red team
Build a repeatable security regression harness for prompt injection, data leakage, RAG failures, unsafe tool use, hallucination, and policy violations. The goal is to make AI security testable before every release.
Outcome
8 deliverables
Best for
Product Security, AI Engineering, QA Automation, Security Engineering
Operating model, governance evidence, and role-system support.
program advisory
Fractional AI security leadership for organizations building or adopting AI. The retainer covers risk register, roadmap, vendor review, product review, customer assurance, board narratives, and operating-model guidance.
Outcome
8 deliverables
Best for
Startup CISO, CTO, AI-native company, SaaS leadership, Mid-market security team
program advisory
Translate AI risk into execution ownership, decision rights, control evidence, and a quarterly operating review model. The sprint turns scattered AI security concerns into an accountable operating system.
Outcome
8 deliverables
Best for
CISO, CTO, Head of Security, VP Engineering
program advisory
Translate NIST AI RMF, ISO 42001, OWASP LLM Top 10, MITRE ATLAS, customer commitments, and internal AI policies into real engineering evidence: telemetry, evals, approvals, tickets, and audit trails.
Outcome
7 deliverables
Best for
CISO Office, GRC, Security Architecture, Internal Assurance
program advisory
Design the role architecture, hiring reqs, interview loops, scorecards, recruiter enablement, and first-cycle calibration needed to hire real AI security engineers instead of keyword-matched unicorns.
Outcome
8 deliverables
Best for
CISO, Security Hiring Leader, Talent Acquisition, Recruiting Manager
Cross-linked proof
Service fit
Surface the people and proof that most often support this lane.
Advisory fit
Move from operating-model talk to the proof and people that make it real.
Control-plane fit
Connect control-plane work to implementation proof and delivery-grade expertise.
Delivery system
01 Scoping
Threat surface, business timeline, constraints, and claim-risk boundaries.
02 Execution
Hands-on review and testing across controls, architecture, and delegated action risk.
03 Evidence
Findings, severity rationale, telemetry requirements, and control traceability.
04 Operationalization
Backlog tickets, ownership mapping, and quarterly review motion with leadership.
FAQ
Use discovery to scope against your architecture, timeline, and control goals. We will recommend the lightest path that still produces defensible outcomes.
Yes. The model is intentionally tiered: short-cycle validation for fast teams and program-level advisory for larger organizations.
Yes. Engagement outputs are delivered directly to your team and are not published.
Yes. We can execute under your MSA/NDA or align on standard consulting terms.
Consulting engagements are scoped independently from sponsorship and research outputs. Sponsor support does not influence methodology, findings, or recommendations.
Sponsorship
Sponsor support is separated from methodology, scoring, findings, chart outputs, and editorial conclusions.
