Practical notes from the engineers who build agents, copilots and AI products.
Meter events per tenant, aggregate to billing periods and expose usage in the admin so AI and API features can be priced. The pipeline is small and boring: an immutable event log, idempotent ingestion, periodic aggregation and a reconciliation job that proves the invoice matches the events before it goes out.
The strangler pattern wraps the legacy system with a façade and replaces modules one at a time behind it, each with rollback. Traffic for each module is switched to the new implementation only after it has run in parallel and matched the old one, so the business never stops and no single cutover can take it down.
A semantic layer defines metrics, joins and time periods once so natural-language questions map to correct, governed queries. Without it the model guesses which column is revenue and which join is right; with it the model picks named metrics and dimensions, and SQL is compiled from definitions finance has signed off.
The same approach works for MongoDB by generating validated aggregation pipelines over a semantic model of your collections. The model selects governed metrics and dimensions, a compiler emits $match, $group and $lookup stages, a validator rejects writes and unindexed scans, and the pipeline is shown with the answer.
Enterprise buyers ask whether prompts, retrieval and logs are isolated per tenant and whether data trains models; the answer must be yes and no. Tenant isolation for AI in SaaS means every retrieval index, prompt context, cache and trace carries the tenant identity, and no provider is permitted to train on the traffic.
Telehealth platforms need scheduling, video, prescriptions, payments and records, built to healthcare privacy rules. The hard part is not the video call but the consult lifecycle around it: identity, consent, the prescription record, refund rules, and an audit trail the regulator and the quality team both accept.
Audit architecture, dependencies, secrets, monitoring, backups and, for AI, prompts and evals before accepting responsibility. The audit takes one to two weeks, produces a written risk register and a day-one runbook, and tells both sides what the maintenance contract is actually covering before anyone signs it.
A shell app owns identity, wallet and navigation; verticals are independent modules on a shared microservices backend. The shell stays small, each module ships on its own schedule through a versioned contract, and identity, payments, notifications and orders are backend services every module uses, not rebuilds.
Indian SaaS needs Razorpay or similar for INR with GST invoices, Stripe for USD, and metering that feeds both. The design decision that matters is keeping one internal ledger of entitlements and usage, with payment providers and tax rules as adapters, so a change in either never touches the product.