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Agent Memory
Your SKOOR agent remembers every correction, preference, and pattern you teach it. Tell it once that Home Depot purchases go to “Supplies” instead of “Office,” and it remembers permanently. No retraining, no repeated corrections, no forgetting between sessions.
Persistent Across Sessions
Unlike chatbots that forget everything when you close the window, your SKOOR agent maintains a persistent memory store. Corrections you made three months ago still apply today. Preferences you set during onboarding carry forward through every future interaction. The agent builds a cumulative understanding of your business that deepens over time.
Context Compaction
As your interaction history grows, SKOOR's AI summarizes older context into compact representations. A year of transaction corrections is distilled into preference rules. Six months of vendor interactions become reliability patterns. This compaction keeps the agent fast and responsive regardless of how long you have been using the platform. Nothing important is lost — it is just stored more efficiently.
Preference Learning
SKOOR learns both explicit and implicit preferences. Explicit: “Always code Staples to Office Supplies.” Implicit: you consistently approve fuel purchases under $100 but review anything above $200. The agent detects these patterns and adjusts its confidence thresholds accordingly. Over time, it handles routine decisions the way you would, freeing you to focus on exceptions.
- Corrections carry forward permanently across sessions
- Context compaction summarizes long histories efficiently
- Learns explicit rules and implicit behavioral patterns
- Agent performance improves continuously without retraining
Try it now
Make a correction on any transaction. Your agent will remember it for every future occurrence.
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