AI AGENT MEMORY USE CASES

What an agent’s brain
can remember.

Give your agent lasting context for research, decisions and operations.
See what to save, how to retrieve it and where to start.

01 / Trading agents
Example agent workflow

Trading agents.
Strategy and decisions.

Save strategy, constraints and decisions for the next review.

Explore the workflow
02 / Prediction markets
Example agent workflow

Prediction markets.
Evidence and forecasts.

Keep the evidence and reasoning behind each forecast connected.

Explore the workflow
03 / Tokenised assets
Example agent workflow

Asset research.
Documents and updates.

Document versions, issuer updates and the history behind an asset.

Explore the workflow
04 / Physical AI
Proposed reference integration

Physical AI.
Site and device records.

A proposed memory foundation for robots, devices and fleets.

Explore the workflow
34,000Builders on Lighthouse

Saved context.
Available to connected applications.

SAVE, RETRIEVE, REVIEW

Three steps.
A record to return to.

01

Remember

Keep useful observations, decisions and source references.

02

Recall

Bring relevant context into the next session.

03

Review

Trace the records behind a response.

BUILD WITH LIGHTHOUSE

Start with the SDK.
Connect through MCP.