Services / Blue Team

Defend AI products with evidence your business can use.

Defensive AI security for products that need inventory, threat modeling, guardrails, logging, evaluation, and evidence-backed remediation before enterprise risk becomes customer pressure.

Start with a Discovery Call Benchmark Your Program Explore SecEng Runtime Proxy

Product SecurityAI InventoryRAG AuthorizationAgent HardeningSecure SDLCLogging & TelemetryDetection CoverageGovernance Evidence

Inputs & context

AI Features & Copilots

Inventory features, copilots, and AI touchpoints.

Agents & Workflows

Map actions, tool authority, and approvals.

RAG & Knowledge

Validate retrieval, tenancy, and provenance.

APIs & Integrations

Trace connectors, webhooks, APIs, and dependencies.

Cloud & Infrastructure

Review runtime, secrets, cloud services, and exposure.

+ Identity & Access

Defensive

Control Plane

AI product
hardening layer

InventoryControlsTelemetry

Outcomes & value

Backlog

Prioritized remediation

Controls

Designed & mapped

Telemetry

Logs & signals ready

Evidence

Audit-ready artifacts

Architecture Findings

Roles & trust boundaries

Risk Narrative

Executive summary

Surfaces Services Flow Outputs System Next Step

Defensive surfaces

AI products need controls across architecture, data, agents, logs, and operations.

Defensive AI security is not one guardrail or one policy. It is the operating layer around AI-enabled products: what exists, what is connected, how it behaves, what gets logged, what gets detected, and what evidence proves the controls are working.

Defensive

Inventory & Architecture

AI features, models, vendors, APIs, data flows, and trust boundaries.

Defensive

RAG & Data Authorization

Tenant boundaries, retrieval permissions, context leakage, and provenance.

Defensive

Agentic Workflows

Tool permissions, approval gates, delegated actions, and blast radius.

Defensive

Product Security Controls

AuthN/AuthZ, tenancy, APIs, admin surfaces, integration checks, and secrets.

Defensive

Logging & Detection

Prompt events, tool calls, retrieval events, alerts, and SOC handoff.

Defensive

Governance Evidence

Control maps, customer trust language, audit artifacts, and remediation proof.

Service formats

Defensive work for AI-native and SaaS teams.

The page is organized like the mockup: flagship work up top, then the broader blue-team service line beneath it.

Flagship

Blue TeamAvailable

assessment

AI Product Security Assessment

A focused review for LLM-powered features, RAG systems, copilots, model integrations, evals, guardrails, data flows, logging, and customer-facing AI surfaces. The output is a prioritized security backlog, control gaps, launch risks, and evidence product and engineering teams can act on.

Outcome

4 deliverables

Best for

CISO, Head of Product Security, VP Engineering, AI Product Lead

•AI system inventory, data-flow, and trust-boundary review
•RAG authorization, prompt injection, guardrail, and eval coverage review
•Model/vendor, logging, telemetry, and evidence gap review

Duration: 2-4 weeksScoped in discovery call

View service Scope AI product review See people fit

Flagship

Blue TeamAvailable

assessment

Agentic Workflow Hardening

Assessment and hardening for AI systems that can call tools, send messages, query data, update records, trigger workflows, browse, code, or operate across business systems. The work focuses on permission design, approval boundaries, blast-radius reduction, logging, rollback, and abuse resistance.

Outcome

4 deliverables

Best for

AI Platform Lead, Product Security, Security Architect, Automation Lead

•Tool permission and action-boundary review
•Approval, escalation, least-privilege, and kill-switch design
•Workflow abuse cases, audit logging, and rollback requirements

Duration: 3-6 weeksScoped in discovery call

View service Scope agent hardening See people fit View proof

Specialized sprints

Standard

Blue TeamAvailable

project

Product Security Baseline

A senior product-security engagement for SaaS and AI-native teams. It covers architecture, authn/authz, tenancy, APIs, admin surfaces, integrations, cloud/IAM, CI/CD, logging, detection coverage, vulnerability workflow, and high-risk feature review, then converts findings into an engineering backlog.

Outcome

4 deliverables

Best for

CTO, VP Engineering, Product Security Lead, AppSec Lead

•Architecture, auth, tenancy, API, integration, and admin-surface review
•Cloud/IAM, secrets, CI/CD, vulnerability workflow, and logging baseline
•High-risk feature and launch-gate review patterns

Duration: 4-8 weeksScoped in discovery call

View service Scope product baseline See people fit

Delivery flow

Structured like an assessment. Delivered like a remediation system.

This is the work sequence the page is selling: no vague advisory loop, just a repeatable control and evidence path.

Scope the product

Define the product, AI features, systems, data, stakeholders, and evidence requirements.

control step

Map the architecture

Inventory models, vendors, APIs, RAG paths, tools, identities, logs, and trust boundaries.

control step

Identify control gaps

Review authorization, tenancy, approval gates, logging, detection, secure SDLC, and operational abuse paths.

control step

Prioritize the backlog

Rank findings by business impact, exploitability, customer pressure, and engineering effort.

control step

Package the evidence

Deliver architecture findings, control recommendations, and public-safe evidence artifacts.

control step

Outputs

Leave with artifacts product and engineering teams can use.

The deliverables are operational: inventory, findings, control recommendations, telemetry mapping, and evidence pack artifacts.

usable

AI System Inventory

Features, models, vendors, data flows, integrations, and customer-facing AI surfaces.

usable

Architecture Findings

Trust boundaries, control gaps, approvals, and exposure concerns.

usable

Control Recommendations

Guardrails, approval gates, logging requirements, and secure SDLC actions.

usable

Remediation Backlog

Prioritized engineering tasks with owners, sequencing, and follow-through.

usable

Detection & Telemetry Map

Events, logs, thresholds, dashboards, and SOC handoff guidance.

usable

Evidence Pack

Screenshots, traces, findings, controls, and audit-ready proof.

Assessment outputs are scoped to the systems, artifacts, access, and evidence reviewed. They do not prove the absence of vulnerabilities or replace formal audit/certification.

Connected system

Blue-team work connects into the workbench.

The service line should point directly into the products and evidence surfaces teams use after the assessment.

SecEng Surface Scanner

Discover and inventory every AI surface before it becomes an attack surface.

Explore Surface Scanner

SecEng Runtime Proxy

Capture AI runtime behavior, prompts, logs, tool calls, and evidence.

Explore Runtime Proxy

SecEng Authority Graph

Map AI action paths, approval boundaries, and blast-radius risks.

Explore Authority Graph

AI Security Scorecard

Benchmark program posture and compare evidence maturity against the field.

Benchmark Your Program

Evidence Packs

Convert findings into governance- and sales-support evidence artifacts.

View Evidence Packs

Workshops

Use jumpstarts to scope, execute, or operationalize the work.

View Workshops

Next step

Start with the AI surface your business depends on.

Bring one product, feature, agent workflow, RAG path, or platform surface. We will scope the risk, map the system, identify the defensive gaps, and leave you with a backlog and evidence your teams can use.

Start with a Discovery Call Benchmark Your Program Explore SecEng Runtime Proxy