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Multi-tenant operations SaaS with an in-product AI assistant

From prototype to a multi-tenant SaaS with usage-based billing, dashboards and a permission-aware AI assistant.

Illustrative scenario. Fictional logistics software startup. A fictional composite of the kind of work we do — not a real client engagement. Results marked [METRIC TO CONFIRM] are placeholders.

Client problem

An early product built fast couldn't support larger customers: no tenancy model, slow dashboards and no audit trail.

Existing environment

  • Single-tenant Node.js prototype
  • One shared database
  • Manual deployments

Challenge

Introduce tenancy, performance and AI features without stopping feature delivery.

Solution

Incremental re-architecture to multi-tenant Next.js + Node services, a reporting layer for fast dashboards, and an AI assistant that answers questions using only data the user may see.

Architecture

  1. 01Tenant-aware API layer
  2. 02PostgreSQL with row-level security
  3. 03Reporting tables + caching
  4. 04RAG over tenant data
  5. 05CI/CD with preview environments

Technology

  • Next.js
  • TypeScript
  • Node.js
  • PostgreSQL
  • Redis
  • Vector database
  • LLMs
  • AWS

AI integration

Retrieval-augmented assistant scoped by tenant and role, with citations to source records and usage metering.

Workflow

  1. User asks a question
  2. Permissions applied
  3. Relevant records retrieved
  4. Answer drafted with citations
  5. User drills into source

Result

  • [METRIC TO CONFIRM] dashboard load time improvement
  • Enterprise customers onboarded with tenant isolation
  • AI feature usage and cost visible per tenant

Technical highlights

  • Row-level security
  • Strangler-pattern migration
  • Per-tenant AI cost metering

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