Test the software and AI workflows your enterprise customers rely on. Get scoped findings, remediation evidence, and clear triggers for renewed testing.
Customer data & business actions
Identity · permissions · approval
Test what an agent can access, remember, and do.
Enterprise reviews
Web & API
LLM & RAG
Agents & MCP
Ongoing assurance
Two product lanes. Clear buying triggers.
Built for your next
enterprise security milestone.
01 / ENTERPRISE B2B SAAS
Your buyer requires a pentest. Define the evidence first.
For CTOs and engineering or security leads with a customer pentest request. Confirm the reviewer, report criteria, product scope, and evidence deadline before testing.
Your AI can access customer data.
Now it can take action, too.
For product and engineering teams whose production AI can read sensitive information or perform consequential actions. Test the full workflow and its permission boundaries.
Production agents, RAG, MCP, or tool calling
New model, provider, connector, or permission
Major AI architecture change or enterprise AI review
Keep ownership of the SOC 2, ISO, or GRC program. Agree report quality, review steps, delivery dates, and retest responsibilities for each authorized client.
Explore compliance partnerships ↗
AI & product development agencies
Plan independent testing before client handoff. Confirm project volume, scope, client ownership, and how findings return to the engineers implementing fixes.
Explore agency partnerships ↗
Trust is in the delivery
Know how the work will be done.
Scope and rules of engagement
Agree assets, roles, tenants, environments, test windows, exclusions, stop conditions, and escalation contacts before access.
NDA and data handling
Agree confidentiality, authorized data, evidence sharing, approved tooling, access handling, and retention requirements during scoping.
Reporting and retesting
A coverage matrix, buyer evidence summary, reproducible findings, and scoped fix verification. Agree report requirements and engineering workshop time before delivery.
Define the host, server, tool, and authorization boundaries that matter.
Practical answers
Before we start.
Who is the best fit for DevBrows?
We work best with a named engineering or security owner, a defined system, and a buyer requirement or material risk. Our focus is SaaS and production AI; we also accept suitable work across industries and through GRC, vCISO, and product partners. We confirm expertise, budget, authorization, and sector requirements during scoping.
How do we start?
Share the system, buyer requirement, reviewer, and deadline in a short scoping conversation. If the required testing is clear, we scope it directly. The $2,500 Security Gate Sprint is a paid review for an unclear procurement request; it is not a prerequisite for testing.
How is AI security priced?
AI Application & Agent Security Assessment has a starting engagement range of $12,000–$20,000 USD, depending on scope. Workflows, model/provider boundaries, tools, MCP servers, roles, memory, and tenants determine the quote. Expanded engagements can exceed that range.
What does Continuous AI Assurance include?
Start with a baseline assessment and review the findings, release cadence, and next-quarter changes. Where recurring work is justified, an annual plan defines quarterly testing, change and permission reviews, a versioned regression record, questionnaire support, and annual reassessment. Capacity and response windows are agreed in writing.
Start with a scoped conversation
Bring the requirement.
We’ll define the right scope.
Share your product, buyer requirement, and target date. We’ll confirm the engagement, deliverables, and commercial terms before work begins.