Process
Security-First AI Development Process
We don't just build features; we build trust. Our process integrates rigorous security testing into every stage of development, ensuring your AI platform is enterprise-ready from day one.
Multi-Tenant Architecture That Actually Works
Real tenant isolation means more than filtering queries by user_id. Row-level security in Supabase, isolated schemas, per-tenant
connection pooling, and API layers that enforce boundaries before
application code runs.
RAG pipelines get tenant-specific embeddings in pgvector. Prompt templates can't bleed across organizations. LLM routing respects tenant boundaries even when batching for efficiency. We've built 37 multi-tenant platforms; the ones that fail treat isolation as a feature request instead of a foundational requirement.
System Integrity Backbone
Every decision—stack, RAG retrieval, agent tool binding, deployment—gets evaluated for performance, security, and tenant boundaries. We decide once and enforce it everywhere so you don't accumulate invisible risk.
Architecture
Clear trust boundaries, Diagram-first RACI, and approvals on how agents and RAG can touch data.
Implementation
Schema validation, typed tool calls, tenant-aware retrieval filters, and CI gates that block unsafe merges.
Operations
Observability, incident playbooks, and regression suites for prompt injection, RAG leaks, and agent abuse.
AI-Specific Security Testing
Standard penetration testing misses the weird stuff that breaks AI platforms. We secure "vibe coding" workflows (Cursor/Claude) and combine OWASP methodology with AI-specific attacks: prompt injection, context poisoning, jailbreak attempts, and retrieval exploits. Our RAG security testing documents lineage so you know which documents influenced each answer.
- Extract embeddings from other tenants' document collections.
- Bypass content filters through prompt engineering.
- Exploit RAG retrieval to access unauthorized knowledge bases.
- Inject malicious instructions into system prompts.
- Escalate privileges through conversational manipulation.
Each test includes reproduction steps and mitigation code. You get the penetration testing report plus the fixes committed to your codebase.
Platform Layers Ship Together
We don't just build "the app." We build the platform. Tenant isolation stays aligned across identity (Clerk with SCIM), billing (Stripe organizational hierarchies), observability (per-tenant metrics), and AI workloads. Penetration testing happens the same sprint features go live. Observable AI telemetry tracks retrieval paths and LLM routing so you can audit tenant access.
Production Security Operations
Security testing doesn't stop at launch. Monitoring alerts on cross-tenant query patterns, unauthorized API calls, and LLM responses referencing outside data. CI/CD pipelines run tenant boundary tests and prompt injection suites on every deploy. Observability dashboards highlight response times and resource usage per tenant to detect anomalies.
Ready to Build a Secure Platform?
Share your tenant isolation requirements, compliance needs, and AI capabilities. We scope, build, and launch platforms with security built in-not retrofitted later. Book a security consultation or explore our AI platform architectures for implementation details.