Tiered Memoryv2.2.0

Researchers can use the tiered memory system to automatically ingest daily notes from experiments, extract metadata like URLs and file paths, and consolidate findings into structured memory tiers. This enables efficient retrieval of relevant past work during literature reviews or hypothesis generation, reducing cognitive load and improving research continuity.

Support teams can integrate this skill to maintain hot memory with customer profiles and active issues, warm memory for recent ticket resolutions, and cold memory for historical data. Automatic ingestion of daily support logs ensures up-to-date context, while tree-based search helps agents quickly recall past solutions and personalize interactions.

Development teams can leverage the system to store project details in hot memory (e.g., active tasks), recent decisions in warm memory, and full archives in cold memory. Automatic daily note ingestion from tools like Jira or GitHub bridges gaps, and metadata extraction preserves URLs and commands for traceability, aiding in sprint retrospectives and onboarding.

Healthcare providers can use the tiered architecture to keep critical patient identity and active treatment plans in hot memory, recent observations in warm memory with decay scoring, and full medical records in cold storage. Cloud-first sync ensures data accessibility across devices, while validation checks help flag incomplete daily notes for compliance.

Law firms can apply this skill to organize case details in hot memory, recent rulings or client interactions in warm memory, and extensive legal archives in cold memory. URL preservation and metadata extraction from daily notes aid in citing sources, and tree-based retrieval allows lawyers to efficiently navigate categories for relevant precedents during case preparation.

Offer the tiered memory system as a cloud-based service with tiered pricing based on storage limits (e.g., hot/warm memory size) and sync frequency. Revenue comes from monthly subscriptions, targeting enterprises needing scalable, multi-device knowledge management with disaster recovery features like Turso DB integration.

Sell licenses for on-premise deployment to industries with strict data privacy requirements, such as healthcare or legal sectors. Include support and updates for the memory architecture, with revenue from one-time license fees and annual maintenance contracts, ensuring clients retain full control over their data.

Monetize by providing APIs for developers to integrate the tiered memory skill into existing applications, charging based on API call volume and data ingestion rates. This model appeals to tech companies building AI agents or productivity tools, with revenue streams from pay-per-use pricing and premium support tiers.