What does an AI SaaS architect do?
An AI SaaS architect designs how AI features work inside a multi-tenant product: how each tenant's data is kept separate in prompts and retrieval, which models run where, how AI usage is metered and billed per tenant, and how new AI features are evaluated and rolled out to customers safely.
What is multi-tenant RAG?
Multi-tenant RAG is retrieval-augmented generation in a product that serves many customers, where each tenant's documents must only ever be retrieved for that tenant. It is done by partitioning the index or using a separate store per tenant, and always filtering by tenant before retrieval rather than relying on the prompt.
How do you stop an AI feature leaking data between tenants?
Scope every AI request to a tenant before it reads any data, filter retrieval by tenant before search, apply user permissions inside the tenant, and keep tenant data out of shared caches, logs and fine-tuning sets. Never rely on the model to ignore other tenants' data because a prompt told it to.
How do you control AI cost per tenant?
Meter every model call to a tenant and feature, set quotas by plan, rate-limit heavy tenants so they cannot slow others, cache repeated work, and route simpler tasks to cheaper models. With cost per tenant visible, AI usage can be priced into plans or billed by use instead of eroding margins.
Should a SaaS product use a self-hosted LLM?
Use a self-hosted LLM when some tenants require their data to stay in your environment, when volume is steady enough to justify the hardware and operations, or when purpose-specific models matter. Many products combine both: a self-hosted model for sensitive tenants or core workflows, and hosted APIs with a fallback for the rest.
What AI and SaaS systems has Muzammil built?
As CTO he built Peaches, a self-hosted, OpenAI-compatible model service that routes four production workflows with a configured fallback, and Pulse / MyOmniHub, a modular multi-tenant platform that uses it for AI workflows. He also led Omnitech CRM, a multi-tenant CRM with fail-closed isolation and 126 permissions across 22 modules.
How is this different from your AI/ML architecture consulting?
AI/ML architecture consulting answers whether and how to use AI in any product. The AI SaaS architect service focuses on the multi-tenant case: tenant isolation in prompts and retrieval, cost per tenant, tiered access and rollout across customers. Many clients need both, and the same assessment can cover them.
What does an AI SaaS assessment cost?
The AI Feasibility & Architecture Assessment costs from $5,900 for up to three use cases, over two to three weeks, and covers tenancy, retrieval isolation, hosting and AI cost per tenant. A single question can start with a $300 Decision Diagnostic. If tenancy needs fixing first, the Platform & Integration Review also starts from $5,900.
Will you build the AI features?
If you want. Many teams build from the design with their own engineers. Hands-on development by Muzammil runs on the CTO + build plan, 80 hours a month for $4,800, or the Full-time equivalent plan, 160 hours for $8,000. Prototypes are quoted once the assessment shows a feature is worth building.
Can an AI SaaS architect help when customers ask where their data goes?
Yes. The design records which customer data reaches which model provider, where models run and what is logged, and gives regulated tenants options such as a self-hosted LLM or their own store. It is technical evidence for your compliance review, not a certification.
