.svg)
Security for the way software gets built now.
Eight issues security leaders are measured on in the AI SDLC. Pick yours and see how Heeler handles it.
Start from the outcome you are measured on.
Enable AI-driven development safely
Capture AI's productivity within an agreed risk tolerance, without making security a bottleneck.
Explore →visibilityMaintain visibility and control over software creation
Know how software is built, which AI agents build it, and where it runs.
Explore →trending_upScale security with development output
Cover more code, applications and releases without growing security headcount or manual review to match.
Explore →account_balancePrevent and reduce security debt
Burn down the backlog you have. Keep agents from adding to it.
Explore →shieldReduce business exposure before attackers exploit it
Out of thousands of findings, fix the few an attacker can actually reach. First.
Explore →lockProtect sensitive data and intellectual property
Find the customer data in your code and APIs, see what agents touch, and fix its risks first.
Explore →linkEstablish trust in the expanded software supply chain
Know what you depend on, keep bad components out, and respond fast when one turns bad.
Explore →fact_checkDemonstrate accountability, resilience, and measurable risk reduction
Owners, controls and evidence on record. Ask for any report.
Explore →Every solution runs on Prevent, Fix and Operate.
All three read from the Context Engine, so each solution gets the same picture of your code, cloud, business and people.
Risk never lands.
Security guidance inside the coding agent as it writes, guardrails on the developer's pull request, and a gate on both before anything merges.
How Prevent works →Burn the backlog down.
Every finding autotriaged by real exposure. Fixes computed, validated in your CI, opened as merge-ready PRs.
How Fix works →Keeps pace with AI.
Findings route themselves, fixes ship, and closure is confirmed in production, at the speed agents write code and attackers move.
How Operate works →Review a design before implementation. Verify it after deployment.
AppSec and architects review proposed endpoints, integrations and data stores before development. Engineering teams retrieve applicable requirements while coding. Security reviewers compare the result with code and deployment evidence.
Threat modeling workflows
