Build Secure Packages

Compare Launch, Scale, and Enterprise packages. Request custom pricing or book a workshop to find your fit.

Not sure which package fits your team?

Book a Build Secure Workshop

Build Secure Packages

Choose the package that fits your engineering team's stage of growth. Every package is tailored to your needs.

Launch
For startups and single product teams getting security right from day one.
  • Secure engineering foundations (SDLC, code review, threat modeling)
  • Developer enablement to build security habits
  • A practical, prioritized starting roadmap
Most popular
Scale
For growing engineering organizations automating security in delivery.
  • Everything in Launch
  • DevSecOps and release security integrated into CI/CD
  • Continuous secure engineering and supply-chain controls
Enterprise
For multi-team organizations needing governance, AI security, and scale.
  • Everything in Scale
  • AI-assisted development and secure AI systems engineering
  • Security champions, governance, and maturity programs

Which package fits your team?

Enter a few engineering metrics — we map them to Launch, Scale, or Enterprise using the same drivers we use in workshops.

Your engineering context
Fill in what you know. You do not need every field.
Recommendation
Enter your metrics and click Suggest a package.

Pricing driver reference

CapabilityLaunchScaleEnterprise
Applications1–56–2020+
Repositories1–1011–5050+
Developers5–2526–150150+
CI/CD pipelines1–56–2525+

Based on Build Secure pricing drivers. Final scope is confirmed in a workshop or proposal.

Package comparison

CapabilityLaunchScaleEnterprise
Secure SDLC baselineIncludedIncludedEnterprise-wide
Architecture reviewLightPriority systemsArchitecture board support
Threat modelingLightProduct-levelProgram-level
Secure code review processBasicFull workflowEnterprise standard
Developer security enablementBasicRole-basedChampions + continuous enablement
DevSecOps setupBasicAdvancedEnterprise standard
CI/CD pipeline securityBasicAdvancedEnterprise policy
Software supply chain securityBasicIncludedFull governance
AI-assisted development securityOptionalIncludedAdvanced
AI coding policyBasicIncludedEnterprise governance
Secure AI SDLCOptionalOptionalIncluded
Security championsIntroProgram designProgram operation
Secure Engineering as a ServiceOptionalRetainerDedicated model
ReportingSummaryMonthly dashboardExecutive dashboard
Maturity reviewOptionalQuarterlyQuarterly + annual roadmap

What determines your package scope

Final pricing depends on engineering scope — not a fixed price list. We use the parameters below in workshops and proposals.

Number of applications
Customer-facing apps, internal tools, APIs, and microservices in scope for secure SDLC and release controls.

More applications increase design review, threat modeling, and release-gate coverage.

Number of repositories
Active code repositories that need SAST, SCA, secrets scanning, and secure PR workflows.

Repository count drives toolchain rollout, policy-as-code breadth, and supply-chain monitoring.

Developers contributing code
Engineers who commit code regularly — including contractors and platform teams touching application repos.

Developer count shapes training cadence, champions coverage, and coaching capacity.

CI/CD pipelines
Build and deploy pipelines across environments (dev, staging, production) and products.

Pipeline count and complexity determine DevSecOps integration and SLSA maturity effort.

CI/CD platform
GitLab, GitHub Actions, Azure DevOps, Jenkins, Bitbucket, or hybrid/multi-platform setups.

Platform choice affects integration patterns, native security features, and rollout playbooks.

Technology stack
Languages, frameworks, cloud providers, containers, and IaC tools in use.

Stack diversity influences secure coding baselines, scanner selection, and lab design.

System criticality
Business impact, data sensitivity, and exposure (internet-facing vs internal).

Higher criticality requires stronger gates, evidence, and review depth.

AI coding tools in use
Copilot, Cursor, ChatGPT, Claude Code, or internal AI assistants used by developers.

AI tool adoption adds policy, validation, and PR-review scope beyond traditional AppSec.

AI-powered products
LLM features, RAG, agents, or ML pipelines shipped to customers.

AI products require Secure AI SDLC, model/data controls, and agentic security engineering.

Compliance and evidence
Regulatory, customer audit, or certification requirements (ISO, PCI, local standards).

Compliance drives reporting cadence, evidence packs, and maturity program depth.

Existing AppSec capability
Whether you have dedicated AppSec, security champions, or rely on engineering alone.

Existing capability changes how much enablement vs operated service you need.

Engagement model
One-time implementation, ongoing retainer, or dedicated secure engineering pod.

Commercial structure is setup fee + monthly retainer; scope follows support level.

Questions we ask to recommend a package

Share these details in a Build Secure Workshop or your request form so we can map you to Launch, Scale, or Enterprise.

  • How many applications are in scope?
  • How many repositories do you maintain?
  • How many developers contribute code regularly?
  • Which CI/CD platform do you use (GitLab, GitHub, Bitbucket, Azure DevOps, other)?
  • How many CI/CD pipelines need security integration?
  • Do your developers use AI coding tools (Copilot, Cursor, ChatGPT, etc.)?
  • Are you building AI-powered products (LLM, RAG, agents)?
  • Do you need compliance evidence or audit-ready reporting?
  • Do you already have an AppSec team or security champions program?
  • Do you need one-time setup or ongoing support (retainer)?

What affects pricing

We do not publish fixed prices. Your proposal depends on scope and complexity.

Engineering team size

Number of developers, squads, and products in scope affects enablement depth and coaching cadence.

Repository and application count

More repos and apps require broader toolchain integration and governance models.

CI/CD pipeline complexity

Platform choice, number of pipelines, and release frequency drive DevSecOps and release security effort.

AI adoption scope

Use of AI coding tools and AI-powered products determines AI governance and secure AI SDLC depth.

Compliance and evidence requirements

Regulated industries and audit cycles increase reporting, evidence packs, and maturity program scope.

Engagement model

One-time setup vs ongoing retainer vs dedicated pod — each maps to a different commercial structure.

Contact us for a tailored proposal based on your engineering context.

Extend your package

Extend your Build Secure package with specialized services.

Annual Penetration Testing Bundle
Recurring assessment coverage aligned with your release cadence and risk profile.
Learn more
AI Systems Security Assessment
Independent testing of LLM applications, agents, and AI workflows.
Learn more
Dedicated AppSec Engineer
Embedded specialist for high-velocity teams needing daily secure engineering support.
Learn more
Developer Security Workshops
Hands-on secure coding labs tailored to your stack and threat model.
Learn more
Secure AI SDLC Add-on
Extend your package with AI-specific SDLC controls, model governance, and RAG security.
Learn more
Software Supply Chain Deep Dive
SLSA maturity uplift, SBOM program design, and artifact signing hardening.
Learn more
Red Team Readiness Review
Validate detection and response readiness before adversary simulation.
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Security Champions Advanced Program
Scale your champions network with advanced playbooks and executive reporting.
Learn more
Vulnerability Management Integration
Connect pipeline findings to your VM workflow with SLA-based triage.
Learn more
WAF / Runtime Protection Alignment
Align build-time controls with runtime protection and WAF tuning.
Learn more
Not sure which package fits?
Book a Build Secure Workshop. We will map your team to Launch, Scale, or Enterprise in a focused scoping session.