Aurora is the first unified AI ecosystem that solves both the enterprise security crisis and the user productivity gap without compromise.
Today's AI has created two critical, interconnected problems that threaten both productivity and security
AI tools are trapped in silos, blind to your broader workflow, forcing manual copy-paste and destroying productivity
Employees are pasting sensitive company data into public AI models. Unaudited, uncontrolled, and impossible to retract
These aren't two separate problems. They're symptoms of one foundational flaw: the lack of a unified, secure, universal context layer.
A unified ecosystem that serves both users and enterprises without compromise
The Application
The user-facing co-pilot designed for extreme ease of use. An intelligent, context-aware interface that manages your entire workflow, built on top of Aurora Nexus.
The Engine
The secure, industrial-grade, model-agnostic engine. Manages security, context, integrations, and AI model abstraction. Can be deployed 100% on-premise.
This separation allows each component to be optimized for its primary function without compromise. Enterprises get total security and control, while users get extreme ease-of-use.
The innovative technologies that power the Aurora ecosystem
The magic behind Aurora's seamless experience: a local, client-side service that understands your entire workflow without manual input.
Create powerful AI agents without writing a single line of code using simple "Trigger → Action" logic.
A unified abstraction layer that eliminates vendor lock-in and gives you access to any AI model: public, private, or local.
How Aurora handles: "Summarize my Notion notes from the 10am meeting and draft an email to the team"
Security is not a feature. It's the foundation. Built to eliminate Shadow AI and protect your data sovereignty.
Every layer of Aurora is built on battle-tested security standards that enterprises demand.
User-Controlled Intelligent Scrubbing
The AI Data Scrubber provides intelligent scrubbing suggestions with full transparency and user control. Before sending prompts to external LLMs, it analyzes content using pattern matching (for structured data like SSNs and credit cards), Named Entity Recognition (for people and organizations), and custom enterprise dictionaries. You choose your scrubbing level—Light (structured data only), Moderate (balanced), or Aggressive (maximum anonymization)—and review detected entities with confidence scores before sending. Manually add entities the system missed or remove false positives. The pre-send review interface shows exactly what will be scrubbed and the expected quality impact, letting you make informed security-quality trade-offs for each prompt. An encrypted session map enables re-hydration of responses while maintaining your chosen level of anonymization.
"Email Sarah about Phoenix: $2.5M"
"Email [PERSON_1] about [PROJECT_1]: [AMOUNT_1]"
You control what gets scrubbed. Best-effort detection with human verification for maximum security.
Application-Level Ingestion Control
The Context Fence provides application-level control over what Aurora Cortex can index. Toggle specific desktop applications on or off with simple allowlist/blocklist rules. Block sensitive apps like Telegram or Signal to prevent those communications from being indexed. For enterprises, IT administrators can define baseline application policies. Important limitations: web applications running in browsers (like Gmail or Google Sheets) are treated as part of the browser process—you can block all of Chrome or none of it. For maximum control when working with sensitive information, use the manual "Pause Indexing" button, which immediately stops all context capture until you resume. This simple approach is the most reliable way to ensure sensitive moments aren't captured.
Simple application blocking plus manual pause button for sensitive moments. On-premise deployment provides complete control.
Client-Side Content Encryption
Aurora uses a hybrid encryption model that balances strong security with practical functionality. All raw content—your documents, emails, and sensitive text—is encrypted client-side using AES-256 with a unique key generated in your device's Secure Enclave (iOS/macOS) or TPM (Windows/Linux). This key never leaves your device. The encrypted content is stored on Aurora Nexus, which cannot decrypt or read it. For semantic search to function, vector embeddings (mathematical representations of content meaning) are stored with limited encryption that enables similarity matching. These embeddings reveal topic categories but not actual content. For organizations requiring maximum security, the on-premise deployment option keeps all data—content, embeddings, and encryption keys—inside your firewall, providing architectural data sovereignty.
Your raw content remains encrypted. For complete data sovereignty, deploy Aurora Nexus on-premise.
For maximum security, deploy the entire Aurora Platform 100% on-premise in your private cloud. No data ever leaves your firewall.
Your data is never used to train AI models. When you use public LLMs through Aurora, your anonymized queries are sent with opt-out flags to prevent model training.
We don't sell your data. We don't share it with advertisers. We don't give it to partners. Your data stays with you, under your control.
Request complete deletion of your data at any time. We'll purge it from all systems within 30 days and provide cryptographic proof of deletion.
Access complete audit logs of every API call, every data access, and every action taken on your behalf. No hidden processes.
We don't access any client data without your explicit permission. This commitment is legally binding in our Terms of Service. It's not just a promise, it's a contract.
Regular third-party penetration testing and security audits by leading cybersecurity firms. We publish audit summaries and maintain continuous security validation.
Aurora creates a flywheel where each part drives value for the others
Aurora Cortex
Freelancers and consultants live in digital chaos, juggling dozens of apps without a unified way to manage context.
Freemium model builds massive user base beachhead, Pro subscription unlocks premium features
Aurora Nexus
The "Shadow AI" crisis: employees exfiltrate data to remain competitive, creating existential risk for the enterprise.
High-margin annual revenue per-seat licensing for on-prem platform and enterprise support
The Developer Ecosystem
SaaS companies need to extend AI functionality but building secure, context-aware features takes months.
Transaction fees/revenue share on marketplace + API licensing creates defensible network effect
Each component strengthens the others, creating a self-reinforcing network effect
Build custom agents
Agents shared & sold
Build integrations
Deploy platform
Join the waitlist to experience Aurora: the dual-architecture solution that ends Shadow AI and delivers true AI productivity.