Enterprise Security & Compliance Standards
Bank-grade security controls, zero-retention AI boundaries, and isolated VPC architecture built for highly-regulated startup and enterprise industries.
Our Core Security Pillars
We embed security, isolation, and automated scanning into every phase of our architecture and code management.
Zero-Data Retention (ZDR) AI Policies
We enforce strict compliance when integrating LLM endpoints. All inference calls utilize enterprise API tiers (such as AWS Bedrock, GCP Vertex AI, or Anthropic Enterprise) which explicitly guarantee that client prompts, outputs, and embeddings are never stored or used to train foundational public models.
- Opt-out of telemetry and logging
- Data transmission encrypted via TLS 1.3
- Strict zero-data-retention (ZDR) policy enforcement
VPC Network Isolation & Data Cryptography
Your data is locked within your perimeter. For companies in high-compliance sectors, we deploy database layers (like pgvector) and model serving systems inside private Virtual Private Clouds (VPC). Under this model, data is completely isolated, preventing external network leakage.
- AES-256 encryption at-rest / TLS 1.3 in-transit
- Customer-managed KMS keys supported
- Zero public endpoint Exposure options
Secure Software Development (SDLC)
We leverage GitHub's Advanced Security (GHAS) ecosystem to protect our repository integrity. Every commit undergoes automated linting, security audits, and dependency scanning before entering testing cycles, ensuring that vulnerabilities are remediated before code ever hits production.
- Static CodeQL analysis in CI/CD pipeline
- Dependabot automated vulnerability scanning
- Signed commits & strictly enforced branch protection
Governance & 100% IP Handover
Our engineering processes are fully transparent and customer-owned. We sign comprehensive mutual NDAs before engagement starts. Once engineering milestones are reached, 100% of the codebase, system schemas, training weights, and parameters are legally transferred to your entity.
- Comprehensive Mutual NDA protection
- Clean intellectual property transfer protocols
- No vendor lock-in or proprietary runtimes
Regulatory Compliance Readiness
Our code patterns, data flows, and infrastructure models are designed to align with major regulatory frameworks.
Security & Privacy Criteria
We structure your development environment, serverless computing functions, and databases to meet SOC 2 Trust Services Criteria. Our architectures include comprehensive audit trails, strict access request processes, and centralized monitoring dashboards so that your compliance auditor gets everything they need.
Protected Health Info (PHI)
For healthcare systems, we ensure PHI isolation by setting up strict VPC firewalls, zero-caching databases, and secure audit logging. We leverage AWS Bedrock and Vertex AI with HIPAA BAA compliance, guaranteeing that sensitive patient data stays secure and compliant.
Privacy & Data Portability
We implement custom hooks for right-to-be-forgotten requests, semantic data deletion pipelines, and encrypted cookie consent frameworks. Your user database architectures are designed with fine-grained column encryption, ensuring user data privacy by design.
Information Security Mgmt
We integrate security management controls directly into your engineering workflows. This includes configuring continuous vulnerability monitoring, enforcing zero-trust SSH/VPN accesses, defining role-based environments (dev, staging, production), and maintaining strict secret key vaults.
Secure Development Lifecycle
Security is not a checkbox added before launch; it is the foundation of our engineering execution. We follow a strict SDLC (Secure Software Development Lifecycle) methodology on every project.
01. Scoping, NDAs & Data Flow Mapping
Before writing any code or accessing repositories, we sign strict mutual NDAs. We audit your existing tech stack and diagram exact data flows, identifying where LLMs call endpoints or store variables to prevent accidental exposure.
02. DevSecOps & Automated Code Auditing
Development occurs in secure environments. GitHub Advanced Security hooks scan code push attempts for hardcoded credentials. Pre-commit hooks verify formatting, while static analyzers (CodeQL) evaluate code paths for injection vulnerabilities.
03. AI Safety Audits & Adversarial Red Teaming
We stress-test model deployments in our AI Labs. This involves running adversarial prompt injection attacks to verify that system prompts and guardrails hold, testing constitutional AI pipelines, and benchmarking output schemas.
04. Secure Deployment & VPC Handover
All resources are packaged as Infrastructure-as-Code (Terraform or CloudFormation). We execute final deployment directly into your secure VPC, hand over full credential ownership, audit the settings, and delete development environments.