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    Service

    Automation & AI Workflows

    Idempotent edge-function pipelines for webhooks, email, reports and AI-assisted classification — verified, logged, repeatable.

    Problem

    Manual hand-offs between systems are the most common source of errors: duplicate records, forgotten reminders, dropped webhooks. A clean automation layer eliminates this entire class of bugs.

    Architecture

    Input
    Trigger (Webhook, Cron, UI-Event)
    Processing
    Edge Function (validate + idempotent)
    Data
    Postgres Mutation
    Intelligence
    AI-Layer (optional, strukturierte Outputs)
    Output
    Notification (E-Mail / Push / Realtime)
    Observability
    Structured Logs

    Stack

    Edge Functions (Deno)PostgresCron SchedulerWebhooks (HMAC)Gemini 2.5 / OpenAIResend

    Example flow

    1. 01Trigger arrives → verify signature & idempotency key
    2. 02Validated payload → atomic Postgres insert
    3. 03Optional AI classification with structured output
    4. 04Follow-up actions: email, push, realtime update, scheduled job
    5. 05Structured log entry for observability & retry audit

    Deliverables

    • Idempotent webhook handlers with HMAC verification
    • Cron-based reminders, reports, cleanups
    • AI classification with structured schemas (not free text)
    • Retry strategy & dead-letter handling
    • Structured logs for debugging & compliance

    Related case study

    My Green Forest

    FAQ

    Why not Zapier or Make?
    Fine for simple connections. For transaction-safe, idempotent, logged flows with data integrity, dedicated edge functions are cheaper and more stable.
    How is AI used?
    Only where structured outputs deliver clear business value (classification, routing, suggestions) — never as a free-text black box in the production path.

    Book a strategy call

    30 minutes, concrete, no sales pressure. We check whether a system of this kind makes sense for your situation.

    Request a slot
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