Enterprise Security First

Enterprise AI.
Zero Data Retention.

Your IP is yours. We build ephemeral, secure, and compliant AI systems for regulated industries. No training on your data. Ever.

Global Compliance Standards

SOC 2 Type II

HIPAA Ready

ISO 27001

OWASP Top 10

How We Protect Your IP from "AI Slop"

Our Zero-Trust Factory ensures that generated code is secure, compliant, and isolated from external training sets. We treat your intellectual property with the highest grade of digital sovereignty.

.cursorrules Firewall

We enforce strict context boundaries. Our firewall intercepts prompts to ensure AI models only access explicitly allowed code segments, preventing accidental IP leakage to public models.

Active Protection

01 import tensorflow as tf

03 def train_model(data):

04 # Sensitive IP Block

05 model = tf.keras.models.Sequential([

06 tf.keras.layers.Dense(128, activation='relu'),

07 tf.keras.layers.Dropout(0.2)

08 ])

ACCESS DENIED

TTL: 0ms

Ephemeral Context

Sessions are instantaneously destroyed upon completion. No chat history or code snippets are retained on our servers or sent to model providers for training.

Agentic QA

AI agents run comprehensive test suites and security scans on every generated PR before a human ever reviews it.

Scanning pull request...

Industry Specific

Built for Regulated Environments

Healthcare (HIPAA-Ready)

Our architecture ensures PHI never leaves your secure environment. We deploy local LLMs or use zero-retention APIs to process medical data, ensuring full HIPAA compliance.

BAA Signed with all providers
End-to-end Encryption

Fintech (PII Masking)

Automated PII masking ensures that no sensitive financial data (credit card numbers, SSNs) is ever exposed to the model.

Real-time PII Redaction
Audit Logs for every prompt

Frequently Asked Questions

AI security in delivery means using AI-assisted workflows in a controlled way that protects sensitive data, enforces safe engineering practices, and reduces risks related to code generation, access, and deployment.

Zero-retention processing refers to workflows designed so sensitive data is not unnecessarily stored or retained beyond what is operationally required. It supports stronger privacy and compliance practices.

Compliance-heavy work requires structured controls such as access governance, secure architecture, review workflows, testing standards, and documentation discipline. The delivery process has to support both speed and accountability.

Yes. Healthcare and other regulated industries require stronger controls around data handling, privacy, auditability, and operational safeguards. These expectations must be built into the delivery model from the beginning.

It can be, when it is governed properly. Safe enterprise use depends on policies, oversight, secure workflows, review checkpoints, and careful handling of code, infrastructure, and sensitive business data.