SaaS engineered for the day your first enterprise buyer asks hard questions

A focused MVP with authentication, core workflows, subscription billing, and basic admin tooling typically takes 8-14 weeks. The variable that matters most is requirements clarity — not features. A well-scoped product with a clear ICP and validated workflow can ship in 8 weeks; an exploratory MVP where the team is still learning what to build often takes 14+ because of mid-sprint pivots. We will surface that risk during the architecture phase.

From sprint one. The cost of building multi-tenancy in later is far higher than building it in early, even if you only have one customer at first. We use row-level tenant isolation with Postgres RLS or NestJS guards as the default — gives you single-tenant simplicity in code, multi-tenant correctness in data. The one exception is genuinely high-touch enterprise SaaS where every customer is single-tenant by contract; that has its own architecture.

Concrete things: audit logs are first-class data (not console.log), secrets are in a vault not env files, access control is RBAC with quarterly review processes, dependency CVEs are monitored automatically (we patched the Next.js GHSA-26hh-7cqf-hhc6 advisory in 90 minutes across 8 deployments in May 2026), backups are tested with restore drills, and breach-notification runbooks exist before they are needed. None of these are retrofits — they are architectural decisions made early. By the time you actually run a SOC 2 audit, the engineering work is mostly done.

We architect for it from the start — every tenant is logically isolatable, so a single-tenant deployment is a configuration choice, not a fork. For the customer side, we provide a Helm chart or Terraform module for their Kubernetes/cloud, signed releases via container registry, and a documented upgrade path. We have shipped to enterprise self-hosted environments and we know what the customer security team will ask for.

Three patterns work in 2026, depending on your product: (1) include AI usage in tier pricing with a hidden fair-use cap, (2) per-seat with metered AI events visible to customers, (3) hybrid — base subscription + per-AI-token overage. We instrument AI cost per tenant from day one so unit economics are visible before pricing is decided. We will also tell you when an AI feature is unit-economically unviable — that conversation is cheaper before you launch the feature than after.

Often yes — this is increasingly common. We start with a 1-2 week architectural audit: data model, query patterns, missing indexes, deployment infrastructure, security posture, dependency hygiene. Output is a written report with severity-ranked issues and a remediation plan. Most takeovers fall into one of three patterns: hardening in place (cheapest), selective rewrite of specific layers (most common), or full rewrite preserving validated requirements (rarest, but right when the architecture has fundamental problems).

Completely. Code lives in your GitHub organization, infrastructure runs on your cloud accounts (or ours, transferred at handover), no licensing fees, no carve-outs, no vendor lock-in. We deliberately architect engagements so the day we walk away, your team or any other vendor can pick up immediately. Several of our long-term clients moved to internal engineering teams after years; we treat that as a successful outcome, not a loss.

Three options: 30-day hypercare is included in every build engagement at no extra cost, a monthly maintenance retainer for ongoing features and security patching (most common — about 60% of build clients), or full handover with runbooks for self-managed operation. We will recommend the right one based on your roadmap and team capacity, not the one with the biggest line item.