Product memo
AI developers building production agents need reliable memory. Aurra provides agents with persistent, source-cited, and auditable recall. It targets teams shipping production-ready agents that require reliable recall and debuggability, preserving source timestamps and a full audit trail. This approach keeps API costs on the user's bill, with an optional add-on for memory extraction.
For who
AI developers building production agents
Solves what
Provides AI agents with persistent, source-cited, and auditable memory.
- Source-cited memory
- Audit trail per memory
- Python & JS SDKs
In their own words
Memory for AI agents that _tells the truth._
Every memory traces back to its source. Every extraction has an audit trail. Drop into your stack in five lines — Python or TypeScript.
Memory infrastructure with receipts.
Commercial cues
Model
usage based
Free tier
Yes
Trial
14d
Pricing Strategy
- • 14-day trial lowers adoption risk.
- • Free tier lowers testing friction.
- • Usage-based pricing follows actual activity.
Operator context
Operating setup
Team
Indie / lean
LLM classification
Founded
May 2026
HQ
United States
Platform
API
Audience
Developers
Social footprint
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Bootstrapped Lean
- Effort
- Solo Buildable
About Aurra Expand
Aurra offers a specialized memory layer for AI agents, designed for developers building production-ready systems. It provides agents with persistent, source-cited, and auditable recall, which is crucial for reliability and debugging.
The platform includes a Python SDK and JavaScript SDK, making it accessible for integration into various development workflows. By focusing on transparent data handling and an audit trail, Aurra serves as a trustworthy component for critical AI infrastructure, helping developers ensure their agents operate with verifiable and traceable information.