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AI dan anomali

Model bekerja untuk proyek di tiga tempat: deteksi yang mengatakan kapan peristiwa meninggalkan garis dasarnya, proposal yang mengatakan apa yang harus dilakukan atas yang dilihatnya, dan Ask, yang mengubah pertanyaan menjadi query. Tidak ada yang bertindak sendiri: proposal menjadi nyata hanya saat seseorang menyetujuinya.

At a glance

Detection
Daily counts against a fourteen-day baseline
Proposals
Origin, rationale, and a recorded human decision
Ask
Question to query, query kept on screen
Model
Chosen by the plan, per tier
Auth
Access token; nothing executes unapproved
  • Deteksi membandingkan hitungan harian dengan garis dasar empat belas hari; deviasinya aritmetika, bukan opini.
  • Setiap proposal membawa asal dan alasannya, dan keputusannya dicatat beserta siapa yang membuatnya.
  • Query terjemahan Ask tetap di layar; model mana yang menjawab adalah pilihan paket.

Cara kerjanya

Detection is arithmetic over the warehouse: a day whose count deviates from the fourteen-day baseline past the threshold is an insight, marked as a spike or a drop. A deviation worth acting on, or a pattern in support threads, becomes a proposal: a cohort to build, a flag to add, a message to send, or a dashboard to create, each carrying what it saw and why it suggests what it does. Proposals queue in the Inbox until a person approves, edits or rejects them, and the decision is stored with its decider. Ask is the third piece: the model emits only the validated query language, never free SQL, and its translation stays on screen beside the answer. The broader model story, entitlements and safety posture live on the AI pillar.

Di mana mengaksesnya

SurfaceOperation
RESTNone
GraphQLaiInsights, aiProposals, aiTranslateQuery, aiAnswer queries · approveProposal, editProposal, rejectProposal mutations
RealtimeaiProposals subscription: new proposals stream as they are raised
MCPNone

Contoh

Bash
curl "https://api.prodantix.com/graphql" \
  -H "Authorization: Bearer $ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "query ($p: String!, $e: String!, $f: String!, $t: String!) { aiInsights(projectId: $p, event: $e, from: $f, to: $t, threshold: 0.3) { bucket kind value baseline } }",
    "variables": { "p": "'$PROJECT_ID'", "e": "signup_completed", "f": "2026-08-01", "t": "2026-08-28" }
  }'