Modern application breaches are increasingly caused by business logic, authorization, and multi-tenant access control flaws, not by classic vulnerabilities like SQL injection or XSS.

However, existing Static Application Security Testing (SAST) tools rely on generic rule-based analysis and lack understanding of a company’s business logic, domain entities, and authorization models. As a result:

• Critical authorisation bugs (e.g., missing tenant or ownership checks) go undetected
• Multi-tenant SaaS applications leak data across customers
• Payment, refund, and workflow logic flaws bypass security controls
• Security teams receive thousands of low-confidence findings with high false-positive rates

This forces teams to depend on manual reviews and periodic penetration tests, which do not scale with fast-moving engineering teams and leave long exposure windows.

Spotter is an Adaptive AI-SAST platform that learns your codebase architecture, generates custom security analyzers for your tech stack, and detects the vulnerabilities others can’t, like an Order endpoint missing organization_id checks, or payment flows without audit logs.

Instead of applying generic rules, Spotter:

• Learns application structure and domain entities
• Models authentication, authorization, and tenant boundaries
• Detects business logic and access-control violations
• Prioritizes findings based on exploitability and business impact

We deliver high-precision, context-aware analysis integrated directly into developer workflows. This allows teams to identify and fix real security risks directly from code, early in the development lifecycle.

[click here to be first to try when we launch]

[talk to founders]
for tech/research
for business/funding

[click here to email] [updates]