Built it with AI?
Get a precise A–F grade in 30 minutes — free.
Drop your saas repo. An A–F Code Health Score lands in your inbox in 10–30 minutes. Zero cost. Zero obligation.
Results in your inbox · No obligation · Your repo is never shared or resold · Response within 1 business day
Not ready to share a repo? Book a free 20-minute code health call first.
— Below: how the next 30 minutes save you from production fires.
Start with a Free AI Health Scan.
Drop your repo URL. We return an A–F scorecard in 10–30 minutes. Zero cost. Zero obligation.
Get your free Adoption Score in 10–30 minutes.
We scan your repository against 8 dimensions — security, authentication, data integrity, performance, scalability, error handling, observability, code quality. You get an A–F grade per dimension plus the top 3 blockers, in plain English, by email.
- What we look at — 8 dimensions, weighted by your stack.
- What you get back — A–F scorecard PDF + 3 prioritized fixes.
- What it costs — Nothing. Not now, not later. The scan is genuinely free.
Your repo is never shared or resold. NDA on request. SOC2-aligned handling.
Permanent engineers. NDA-first. Region-fluent.
We are not a freelance broker. ~20 engineers on permanent contracts in Malaysia, a talent pipeline from 4 universities, and the same business hours as Singapore.
Your Code Health Score, in 30 Minutes.
Here's what lands in your inbox after the scan. No PDF download, no login wall — just the report.
Sample report. Real grades and findings vary by repo.
What "Working" AI Code Actually Looks Like Under Load.
Six failure patterns we see weekly in repos generated by Cursor, Copilot, or solo-vibes-coded.
Session tokens never expire. Anyone with a leaked token gets in forever.
Code works in dev (10 rows), dies in prod (10K rows). No indexes, no pagination.
No transactions on multi-step writes. Half-written records, no rollback.
TypeScript turned off at the API edge. Runtime errors that should be compile-time errors.
No logs, no traces, no alerting. When it breaks, you find out from users.
API keys in the repo. Stripe live key committed to git history.
Three SaaS Realities. Three Answers.
Each pain is what we see weekly in rescue scans. Each answer is what we actually deliver.
Cursor / Copilot-built SaaS auth lets stale tokens in for months — and you only learn from a user complaint.
→Free A–F scan flags auth, session, and token-expiry issues by name. Hotfix in 2 weeks, same engineers.
AI-generated billing code "works" in dev with 10 customers and corrupts data in prod with 10K.
→We rebuild the data layer with proper transactions and idempotency — code yours from Day 1.
Your previous vendor disappeared, the repo has no docs, and your runway is shrinking.
→Detailed scoping before code. Documented handover. Your future hires can take it over without us.
You shipped a SaaS feature with AI tools — and now nobody knows what's in it.
Cursor, Claude, or ChatGPT wrote 70% of the auth layer. It worked in dev. It worked in staging. It works in prod — most of the time. Last week a customer reported a state leak that no one on the team can reproduce. The original author is your AI tool. The reviewer is you. And you're not sure where to look.
What we flag for SaaS: churn-driving bugs, MRR-impacting outages, trial-to-paid conversion blockers, subscription billing edge cases, and onboarding-completion drop-offs.
- You can't explain the auth flow line-by-line, only at a high level.
- Test coverage is patchy — your AI tool wrote happy paths only.
- A security review is overdue but nobody wants to be the first to read 4,000 lines of generated code.
Get a second pair of eyes — for free, in 30 minutes — before it breaks under real load.
From Free Scan to Fully Rebuilt.
You start at SGD 0. You only escalate if you want to. Most teams stop at one of the lower tiers.
We run our own production SaaS — the same way we run yours.
Three internal products live in production under the same quality controls we apply to client work — GitHub-visible delivery, AI + human PR review, weekly demos, monthly retros.
Not products you can buy — listed here as evidence of our own production-ops experience.
One Funnel. No Lock-in at Any Step.
You pay only for the tier you actually want. Nothing is bundled. Nothing is required.
- A–F evaluation score across 8 dimensions
- Top 3 blockers, in plain English
- Delivered to your inbox · No commitment
- Detailed technical report with code snippets
- Risk register prioritized by business impact
- Written fix plan, scoped by tier
- Top blockers patched, working code Day 1
- Fix-code samples committed to your repo
- Daily GitHub review, AI + human PR review
- Hotfix + observability + tests + CI/CD
- DIY guide so your team can keep it going
- Documentation + 1 walkthrough call
- Full rebuild on production-grade architecture
- Keep your business logic, replace brittle plumbing
- Full repair plan, documented handover
Ready to Move?
Get a 2 weeks delivery scope + fixed price within 24 hours. No obligation.
30-minute call · No obligation · English PMs, GMT+8
— Now let's look at what we actually do — and what you decide tier-by-tier.
Compare Your Options
A transparent look at what each path costs, takes, and delivers.
| In-house hire | Big-3 agency | Freelancer | LLL Inc. | |
|---|---|---|---|---|
| Cost | SGD 200K+/yr salary + benefits | SGD 30–80K per project | SGD 5–15K but variable | Free → SGD 6,500 fixed |
| Time to first deliverable | 4–6 months (hiring + ramp-up) | 2–4 months (proposal + discovery) | Unpredictable (sourcing) | 2 weeks |
| Quality control | You manage | Agency process (variable) | None built-in | Daily GitHub review, AI + human PR review |
| Code & IP ownership | You own (employment) | Contract-dependent | Often unclear | 100% yours from Day 1 |
| Communication | Direct (SG local) | Account-manager layer | Timezone gaps (6–12 h) | English PMs, GMT+8, daily |
LLL Inc.
See how this compares to other optionsIn-house hire · Big-3 agency · Freelancer
Freelancer
Big-3 agency
In-house hire
How Long Until You Have Something Real
Four paths every Singapore SaaS team evaluates — measured in time-to-working-code, not slideware.
Why This Honest Diagnosis Is Possible.
Structural reasons. Not promises — process.
In-house Malaysia team
~20 full-time engineers. Zero freelance outsourcing. Day-1 live capacity, no formation lag.
AI-augmented development
Internal use of Claude / Cursor / Cowork compresses implementation hours, with human PR review.
Reusable architecture templates
Sharpened across 50+ client engagements — auth, billing, RBAC, observability already in place.
Japanese-rooted QA process
Detailed scoping, rigorous QA cycles, clear documentation, predictable communication.
Initial Call
Response within 24 h. 30-minute consult and current-state interview.
Scope & Quote
Fixed-scope, fixed-price proposal by the next business day.
Kickoff & Sprint Start
NDA signed → repo invite → Sprint 1 begins.
Build & Demo
2 weeks of build, daily GitHub progress, weekly demo.
Handover
Working code + documentation + 1 walkthrough call.
Frequently Asked Questions
Why scan this week, not next month?
AI-built code degrades fastest in the first 90 days.
Edge cases that didn't surface in dev compound under real traffic. The cost of fixing climbs 3–5× after launch.
Free. 30 minutes. Zero login wall.
Drop a repo URL. Get an A–F grade in your inbox. No call, no contract, no obligation — ever.
You walk away with the report — even if you never engage us.
The findings are yours. Hand them to your team, your auditor, your next vendor. We never share or resell your code.
Tell Us About Your Product.
30-minute call. No obligation. You'll receive a delivery scope and timeline within 24 hours.
Thanks — Auto Scan starting.
An engineer (not a sales rep) will reply within 1 business day with your A–F evaluation and top 3 blockers.