Software agents
Persist selected text events, retrieve related retained records, and pass returned context to a model managed by your application.
Scope
Use cases and research boundaries
The current API supports a deterministic text-memory workflow. The examples below show where that workflow can be integrated now and where the Palo Bloom architecture may lead later. A use case is not a product guarantee. Each section names its implementation status and the missing evidence.
Current integration patterns
Project and support context
Use namespaces and idempotency keys to keep a text history inspectable across sessions and safe to retry.
Operational analysis
Inspect request quality, usage, charge state, events, health, and anomaly signals for the API path.
Research directions
These directions depend on a deployed learned runtime and reproducible evidence. The current API does not provide them merely because it has names or response fields for them.
Experience-aware retrieval
A learned representation could test whether retrieval improves when an event is considered in relation to prior experience, time, and identity. The required model, baselines, dimensions, quality threshold, and cost are not yet established.
Personalization
Applications may eventually evaluate learned episodic structure for continuity and personalization. Current lexical results must not be described as learned user modeling or prediction.
Traversal and mapping
The contract can identify these stages, but a useful distinction between retrieval, traversal, and mapping still needs an executable research definition and independent evaluation.
Recommendations and forecasting
Recommendation and forecasting are possible application research areas. No current Mpalo API claim establishes predictive behavior, real-time adaptation, or a performance advantage.
Multimodal and physical inputs
The public v1 memory schema is text-only. Images, audio, sensor streams, and other physical inputs are research and planning topics. They require a capture boundary, subject and bystander consent, reliable provenance, raw-data retention rules, redaction, deletion, asynchronous processing, and modality-specific evaluation before they can become API capabilities.
Robotics boundary
Memory may eventually inform an embodied application, but it cannot become an unverified source of truth for physical action. Authoritative control state must remain separate from probabilistic memory. Missing, stale, contradictory, or uncertain memory must lead to a safe application-defined fallback.
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