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Sellavie.ai Technical Case Study

Multi-tenant AI social sales platform that automates connected customer conversations and connects them to order, invoice, and payment workflows through controlled server-side flows.

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Tech At A Glance

Production backendWeb dashboardMobile appTenant-scoped dataConversation automationAI response orchestrationCommerce workflowsOperational deploymentAccount controlsConfiguration protection

Problem

Small and mid-size online businesses lose revenue when social DMs are answered late, handoffs are inconsistent, and payment follow-through is manual. They need one system that can route conversations, keep tenant data isolated, and execute commerce side effects safely.

Architecture

  • Backend service coordinates account access, tenant management, inbound event processing, AI response generation, and commerce workflows.
  • Tenant isolation is enforced with business-scoped records and role-aware access checks.
  • Inbound customer events are validated, routed by business context, and dispatched through controlled workflows.
  • AI orchestration includes fallback behavior and safeguards for customer-facing responses.
  • Server-side routing separates customer-visible text from business workflow execution.
  • The dashboard and backend are deployed with separated public and private operational boundaries.

Key Engineering Highlights

  • Implemented tenant-scoped auth with layered account protection and controlled session handling.
  • Built deterministic tenant routing for inbound customer events using connected business context.
  • Designed workflow routing that separates customer-visible messages from server-side business actions.
  • Integrated commerce workflows through validated provider events and order/invoice/transaction synchronization.
  • Added background processing for notifications and commerce side work without blocking the customer flow.
  • Hardened reliability with fallback behavior, duplicate-order guards, bounded input handling, and abuse controls.

Security & Privacy

  • Validated inbound events before processing downstream actions.
  • Layered authentication and account-protection controls for business users.
  • Protected sensitive configuration fields in storage and responses.
  • Request hardening, abuse throttling, and bounded payload handling.
  • Audit-oriented activity logs and generic client error responses to reduce data leakage.
  • Consent withdrawal, data export, account deletion, and platform deauthorization/data-deletion flows.

Architecture Diagrams

Mermaid runtime rendering is not configured in this portfolio codebase, so the diagrams below are static SVG assets derived from public-safe architecture summaries.

Sellavie architecture diagram showing customer surfaces, backend service, data layer, and external service boundaries.
System component architecture: customer surfaces, backend runtime, data layer, and external service boundaries.
Inbound event sequence diagram showing message ingestion, validation, tenant routing, AI generation, and reply dispatch.
Inbound message flow: event validation, tenant context loading, controlled workflow routing, and reply.

Build Timeline

  • Defined the core multi-tenant account model and access boundaries.
  • Shipped inbound customer event ingestion and workflow routing for connected messaging surfaces.
  • Built tenant-scoped AI context loading and response fallback behavior.
  • Added commerce workflows for purchase detection, checkout handoff, invoice support, and payment status updates.
  • Implemented analytics, activity logging, moderation handoff, and customer data controls.

Future Work

  • Expand shared infrastructure for abuse controls and session governance.
  • Standardize the long-term production data path and migration workflow.
  • Add more resilient background processing for outbound messaging and invoice/email jobs.
  • Split the backend into bounded modules to reduce coupling and improve testability.