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USE-CASE ATLAS

Where SeenRelay may belong — and how strong the evidence is.

Validated means we have domain-specific controlled evidence. Experimental means the structure looks promising but the vertical has not earned a promoted claim. Research means safety/domain validation is still required.

VALIDATED VERTICAL

Retail prices & product monitoring

Avoid repeated paid extraction while the relevant commercial state is unchanged; force new work when the state fingerprint changes.

Native first: Direct product/state signal, provider cache and source validators when sufficient.

Integration: HTTP/extraction wrapper or monitor middleware

Measured proof →
VALIDATED VERTICAL

Weather-driven downstream analysis

Use cheap/native weather state to avoid repeating paid downstream analysis until relevant state changes.

Native first: Weather provider update cadence, cache and push/event mechanisms.

Integration: State fingerprint + downstream analysis guard

Measured proof →
PROVEN MECHANISM APPLICABLE

AI agent search & research

Coordinate compatible top-level paid search/tool executions only when the caller contract explicitly permits shared fresh results; otherwise preserve the required execution multiplicity.

Native first: Provider caching, framework single-flight, provider request coalescing where available, and the caller's required multiplicity/diversity contract.

Integration: Agent/tool middleware, MCP or SDK wrapper

Measured proof →
PROVEN MECHANISM APPLICABLE

Hosted compute, sandboxes & code tools

Avoid allocating multiple billed sessions when compatible callers require one deterministic execution.

Native first: Provider session reuse and local process coordination.

Integration: Tool/runtime wrapper

Measured proof →
PROVEN MECHANISM APPLICABLE

Web scraping, browser & extraction

Single-flight exact compatible extraction/browser work and reuse bounded results where policy permits.

Native first: HTTP validators, provider cache, native browser/session reuse.

Integration: HTTP/provider SDK wrapper

Measured proof →
PROVEN MECHANISM APPLICABLE

Shared generated artifacts

Generate once when all callers explicitly accept one shared artifact and diversity is not required.

Native first: Existing asset cache/content-addressed storage.

Integration: Generation-tool wrapper

Measured proof →
VALIDATED VERTICAL

Inventory & availability monitoring

Avoid repeated paid extraction/analysis while the authoritative inventory state is unchanged; force fresh work when the state token changes.

Native first: Retailer Product API, webhook/feed events and provider cache. If the native state endpoint fully answers the need, SeenRelay should self-reject.

Integration: State monitor + extraction/analysis guard

Measured proof →
VALIDATED VERTICAL

News & event-driven monitoring

Coordinate bursty search/retrieval around the same event and avoid reprocessing an unchanged event state.

Native first: Feeds, webhooks, publisher updates and search-provider cache.

Integration: Search/retrieval middleware

Measured proof →
EXPERIMENTAL

Live sports & broadcast data

Fan out one qualified live-state observation and reduce repeated recovery/polling or downstream analysis.

Native first: Official push feeds and licensed event streams.

Integration: Stream freshness monitor + local fan-out

EXPERIMENTAL

Logistics, tracking & ETA state

Avoid repeated status analysis while shipment/fleet state is unchanged.

Native first: Carrier push/webhook/state feeds.

Integration: Status/state middleware

EXPERIMENTAL

Financial reference, snapshots & derived analysis

Coordinate repeated analysis of the same explicit market/reference snapshot.

Native first: Streaming market feeds, subscriptions and provider-native snapshots.

Integration: Snapshot-aware analysis guard

EXPERIMENTAL

Threat intelligence & reputation

Reduce repeated paid reputation/lookups inside explicit short freshness windows.

Native first: Vendor cache, feeds and local IOC stores.

Integration: Security enrichment middleware

EXPERIMENTAL

Geocoding & enrichment

Coordinate exact stable lookups where provider terms and freshness semantics permit.

Native first: Local/reference caches and provider-native batching.

Integration: API wrapper

EXPERIMENTAL

Web traffic / observability analysis

Avoid repeated expensive query, enrichment or AI analysis of the same traffic window/watermark.

Native first: OpenTelemetry/eBPF collection, materialized queries and SIEM-native aggregation.

Integration: OTel/SIEM/query middleware

EXPERIMENTAL

Large-scale IoT / edge analytics

One expensive downstream analysis per authoritative machine-state version; re-analyze when state changes.

Native first: MQTT, OPC UA PubSub, Sparkplug state/session semantics.

Integration: Edge analysis guard above native state transport

EXPERIMENTAL

Blockchain RPC & agentic chain reads

Coordinate block-pinned compatible reads, simulations and analysis while revalidating changing head state.

Native first: Subscriptions, batching, Multicall and provider-native controls.

Integration: Block-aware JSON-RPC proxy or SDK transport

EXPERIMENTAL

Inter-blockchain status & finality evidence

Coordinate repeated cross-chain status/finality observations above interoperability transports.

Native first: Quant Overledger, CCIP, LayerZero, Hyperlane, IBC events and protocol lifecycle.

Integration: Cross-chain status/evidence guard

RESEARCH

Robotics & autonomous fleets

Share expensive analysis of identical state/frame evidence and enforce decision-time freshness before dependent actions.

Native first: Real-time control loops, sensor fusion, DDS QoS and safety mechanisms.

Integration: Supervisory/analysis layer only

RESEARCH

Spacecraft, satellites & remote operations

Avoid repeated analysis/compute on identical telemetry while respecting scarce communication and mission freshness.

Native first: DTN, mission control and authoritative spacecraft protocols.

Integration: Analysis/evidence layer only

RESEARCH

Medical data & clinical monitoring

Coordinate versioned downstream analysis and detect stale evidence without replacing clinical source-of-truth mechanisms.

Native first: FHIR Subscription, device-native streams and clinical safety controls.

Integration: Tenant-local downstream analysis only

RESEARCH

Aviation situational data

Potential freshness/fan-out coordination for auxiliary state and downstream analysis.

Native first: Authoritative surveillance/weather/operational streams.

Integration: Non-control supervisory layer

RESEARCH

Industrial automation & digital twins

Avoid repeated supervisory analytics on unchanged state; never suppress hard real-time control/safety execution.

Native first: OPC UA, PLC/control loops and safety interlocks.

Integration: Supervisory analytics layer

RESEARCH

Energy grid & critical infrastructure

Coordinate downstream situational analysis with explicit evidence-age constraints.

Native first: Protection systems, SCADA/telemetry and grid-native controls.

Integration: Supervisory evidence layer only

ADOPTION

Start with the mechanism, not the industry label.

Choose a validated or structurally matching read-only path, keep native controls first, and use the narrowest supported integration. Research domains are not an invitation to place SeenRelay inside safety-critical control loops.