Faster, more consistent claims decisions with tamper-aware spatial evidence.
After a severe storm, a policyholder submits vehicle-damage images and location evidence. The insurer must guide capture, detect missing or contradictory context without overclaiming authenticity, run model-locked vision triage with human review, dispatch scarce assessors by eligibility and ETA, join hazard exposure, and retain explainable evidence through settlement and appeal.
Compose multiple capabilities while the application owns user intent, policy, and continuity.
Owns policy, claimant, incident declaration, coverage, reserves, decisions, settlement and appeal.
Claim ↔ declared incident place and policy coverage snapshot
GETReturns the details of provided model/models/{api_model_key}This is a supporting operation from the selected product stack, not proof of an exact provider contract for this stage. Resolve the stage through its product source or adapter boundary before live implementation.Record stage 1 with the application identity, source fingerprint, request or aggregate identity, timestamp, and observable outcome.
Use per-object hashes and a submission manifest; keep the claim incomplete until all required evidence commits.
Collects guided media, device/location accuracy, timestamps, hashes, capture policy and disclosure; an entitled SkyDNN adapter locks model identity, validates bounded derived geometry and confidence, and never treats metadata or inference as proof by itself.
Evidence submission ↔ immutable media hashes, consent, times, accuracy, device/source
GETRouting API/{REST_KEY}/{resources}/{profile}/{geopositions}This is a supporting operation from the selected product stack, not proof of an exact provider contract for this stage. Resolve the stage through its product source or adapter boundary before live implementation.Record stage 2 with the application identity, source fingerprint, request or aggregate identity, timestamp, and observable outcome.
Preserve model and input identities, route to an independent reviewer, and prohibit automatic settlement or fraud decisions.
Normalizes incident place, joins versioned hazard/catastrophe layers and links every feature to its source and observation window.
Vision attempt ↔ model fingerprint, asset hash, bounded detections, confidence, review policy
GETTo get the task details for the given task id./tasks/{taskId}This is a supporting operation from the selected product stack, not proof of an exact provider contract for this stage. Resolve the stage through its product source or adapter boundary before live implementation.Record stage 3 with the application identity, source fingerprint, request or aggregate identity, timestamp, and observable outcome.
Preserve both sources, lower automation confidence and route to review rather than silently choosing one.
Routes incomplete, uncertain, sensitive, or high-risk claims to independent review and capable assessors, ranks eligible teams by network ETA and tracks field-task proof.
Hazard feature ↔ dataset/version, geometry relation, observation date
GETRouting API with driving profile/{REST_KEY}/{resources}/driving/{geopositions}This normalized operation matches the stage intent and remains subject to its source, lifecycle, authentication, entitlement, host, and regional gates.Record stage 4 with the application identity, source fingerprint, request or aggregate identity, timestamp, and observable outcome.
Publish a new dataset/version and derived claim revision without rewriting the evidence used in the original decision.
The recipe starts from the normalized GET /models/{api_model_key} contract. Execute six deterministic fixture outcomes before an issued account is involved.
https://ai.mappls.com/models/vidteq-ods-9curl --request GET \
--url 'https://ai.mappls.com/models/vidteq-ods-9' \
--header "Accept: application/json" \
--header "Authorization: Bearer ${MAPPLS_AI_TOKEN}"Credential-safe by constructionSet MAPPLS_AI_TOKEN only in your trusted runtime. Code generation stays local. Sandbox execution sends only bounded fixture inputs to this developer platform and never reads a credential or calls Mappls.
These controls are required at this operating depth; deeper recipes add durable truth rather than merely more API calls.
Every capability has one owner, bounded input, explicit timeout, and useful unavailable state.
Application intent survives refresh, back navigation, duplicate callbacks, and partial capability failure.
Provider identities, source fingerprints, request identities, and application decisions remain attributable.
Accessibility, privacy, quota, observability, support, and rollback evidence cover the complete user flow.
/models/{api_model_key}GETTo get the list of tasks and their details/tasksGETRouting API/{REST_KEY}/{resources}/{profile}/{geopositions}GETReturns the details of all the models/modelsGETTo get the task details for the given task id./tasks/{taskId}GETRouting API with driving profile/{REST_KEY}/{resources}/driving/{geopositions}GETReturns the current models in port/server/whoamiPOSTTo create new Task/tasksCorrelate an outage, govern independent switching approval, dispatch an assigned crew, preserve rework, and reconcile restoration from telemetry and customer-impact evidence.
This recipe composes source-derived contracts, application architecture, fixtures, and maintained learning evidence. It does not prove package availability, provider payload shape, account entitlement, regional behavior, production compatibility, or release approval.