Platform overview

XTrace is a managed memory platform with three layers:

Extraction

When you send conversation turns to the API (or sync them via the Chrome extension), XTrace runs a 3-way parallel extraction pipeline:

• Beliefs (facts) — atomic assertions about the user, their preferences, decisions, and context
• Episodes — structured summaries of what happened in a conversation session
• Artifacts — work products (code, documents, strategies) with version history

Extraction uses specialized prompts for each type, with post-hoc linking between facts and the episodes they came from.

Revision

Extracted knowledge isn’t static. The belief revision engine continuously maintains consistency:

• Supersession — new beliefs replace outdated ones, preserving lineage
• Contraction — beliefs can be retracted without replacement (“we’re NOT doing X”)
• Entrenchment — user-stated beliefs outrank system inferences; core beliefs are protected
• Consolidation — duplicate and near-duplicate facts are merged via text dedup + LLM resolution

Retrieval

When you search or an agent requests context, XTrace assembles the most relevant knowledge:

• Semantic search across beliefs, episodes, and artifacts
• Classifier-gated routing to the right knowledge type
• Iterative reranking for precision
• Character-budgeted context assembly — fits the most relevant information into your token budget

Security

All data is stored in XTrace’s encrypted vector database. Each user’s knowledge is isolated in scoped, permission-controlled stores. API keys are generated per-user with org-level scoping.