Original assumption
The forecast relied on a particular event occurring before the deadline.
Keep sources, forecasts and outcomes together. Let research agents revisit earlier assumptions as new evidence arrives.

Forecasting is a sequence of updates. Preserve the sources, assumptions and revisions behind each forecast so a research agent can explain what changed between sessions.
New evidence has arrived. What should we revisit in this forecast?
The forecast relied on a particular event occurring before the deadline.
Keep the publication date and reference behind that assumption.
Record which evidence changed the last assessment.
A probability without its assumptions is hard to revisit when new evidence appears.
Research notes spread across sessions, making the origin and age of an observation difficult to follow.
Without a recorded history, teams cannot easily compare what they expected with what actually happened.
Keep source references, publication dates and research notes together. Recall the evidence behind a forecast instead of relying on an unsupported summary.
Write the conditions that support a forecast as explicit records. A later session can retrieve them when a related event or observation arrives.
Persist each assessment with its timestamp and rationale. Your application can compare revisions while retaining a reference to earlier content.
Link the outcome to earlier assumptions and evidence. Use your own scoring and review process to decide what the team should carry into future research.
Record source references, timestamps, market tags and the assumptions they inform.
Retrieve related evidence and previous assessments when new information arrives.
Record the resolved outcome and review it against the research history.
Lighthouse preserves the research record. Source accuracy, forecast scoring and market actions remain part of your application.
Connect the memory runtime to the moments your application needs to write, recall and review context.
Explore memory documentation ↗Choose an event or market identifier that stays consistent across sessions.
Store observations separately from the agent’s interpretation.
Timestamp each forecast and record the resolution criteria.
Implement forecast scoring and market actions in your own application.
No. It provides a way to persist and recall the research context your forecasting application uses. The model and application produce the assessment.
A stored reference helps trace a claim back to its source. Evaluating source reliability and factual accuracy remains part of the research workflow.
Your application can use namespaces and tags to organise records by event, market or topic, then query the relevant context.
Persist the forecast, timestamp, rationale and source references. Your application can retrieve these records alongside the resolved outcome for comparison.