Investment & budget · Prepared for Eden Women's Health

Two honest options — priced straight, so you can pick on the actual trade-off.

A Foundation build that answers your six questions directly, at the lowest cost. Or an AI-enhanced build that costs more up front but makes a meaningfully stronger case for EDG grant funding — which can bring its net cost below the Foundation build's full price. Neither is the "wrong" choice; it depends on whether you want to deal with a grant application.

See the numbers Compare the grant math → ← Back to proposal

~40% faster

delivery timeline vs. a typical custom-build agency (5–7 weeks vs. 9–11), from AI-assisted engineering — on either track

2 tracks

Foundation build (lower cost) or AI-enhanced build (stronger EDG case) — your call, not ours

Up to 50%

of eligible cost potentially offset via Enterprise Singapore's EDG grant (client-applied, not guaranteed)

The estimate

Pick a track. Both answer your six questions — one just goes further.

The Foundation build covers everything you actually asked about: inventory/COGS reporting, visit and referral tracking, revenue breakdowns, and the OB/GYN split, all mapped into Xero — no AI required. The AI-enhanced build adds automated invoice reading, smarter classification, a natural-language reporting assistant, and anomaly detection on top — features that go beyond what you originally asked for, but that also happen to be what makes this build a strong fit for EDG funding (see below).

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Investment

Why we deliver faster

We build this the same way we're proposing to automate your reporting: SkubbsMate handles the repetitive part, and a person checks the part that matters.

A project scoped like this typically runs 9–11 weeks with a conventional custom-build agency. Built on our SkubbsMate development platform, we're usually looking at closer to 5–7 weeks — without cutting corners on anything that touches your financial data.

Where SkubbsMate's AI-assisted engineering actually saves time

Boilerplate extraction/transformation code, API client scaffolding, and UI screens — the bulk of the raw coding hours
First-pass data mapping between Plato's report fields and Xero's chart of accounts
Test scaffolding and documentation, generated alongside the code instead of after it

Where we don't cut a single hour

Classification rule design (OB/GYN, Procedures vs. Doctor's fees) — this needs your judgment, not just a model's
Financial reconciliation logic — COGS and GST handling get manually reviewed line by line before anything posts to Xero
Client validation checkpoints at the end of every phase, before the next one starts

The AI-enhanced build — what it adds

Where artificial intelligence actually earns its place, if you choose that track.

Not "AI" as a buzzword bolted on for the pitch — these are the specific places a model does something a static rules engine can't. None of this is required to answer your six original questions; it's what you'd be paying the extra S$8,075 for, and it's also the piece that makes EDG's "Automation" criteria a strong fit rather than a stretch.

AI-powered invoice extraction

Reads unstructured lab/radiology invoices — the cost data that lives outside Plato entirely — and pulls out structured line items automatically, instead of the manual upload-and-parse step in the Foundation build.

AI-assisted OB/GYN & procedure classification

Trained against your locked classification ruleset once it's stable, with a confidence score on every line and a human-review queue for anything it's not sure about — never a silent guess on financial data.

"Ask your numbers a question" assistant

A natural-language query layer over the canonical data model — e.g. "how did GYN revenue compare to last quarter" — without needing to open a spreadsheet or wait for a report to be built.

Anomaly & variance detection

Automatically flags the kind of thing you currently catch by hand — the refund/MC-visit variance, or a GST-inclusive figure slipping in next to exclusive ones post-March 2026 — before it reaches your bookkeeper.

Note: the Foundation build's vendor-discount matching stays a deterministic reconciliation step, not an AI feature — it doesn't need to be one to work well.

Handled carefully — PDPA and patient data

Patient visit records, procedure classification and referral data are personal — and in this case health-related — data under Singapore's PDPA. If you go with the AI-enhanced track, feeding that into an AI layer isn't something to gloss over, so here's how we'd approach it:

Data minimisation: classification and matching prompts reference patient/invoice IDs, not names, wherever the workflow allows it — the model only sees what the specific task actually needs.
AI provider selection: enterprise-tier providers only, with contractual no-training-on-your-data terms and defined data residency/retention — confirmed and documented before the AI layer goes live, not assumed.
Roles under PDPA: we'd operate as your data intermediary, processing on your behalf under a written agreement. Your practice remains the data controller and stays responsible for patient consent and notification — we build to support that obligation, not replace it.
Access & retention: full audit trail and access controls on every record the AI layer touches, with a retention/deletion policy agreed during scoping rather than indefinite storage by default.

This isn't a substitute for your own PDPA compliance review or legal advice — happy to work with your compliance advisor on the specifics before this layer is built.

Grant support — Enterprise Development Grant (EDG)

Higher base cost, stronger grant case — here's the actual math.

Enterprise Singapore's EDG is the most relevant scheme for a bespoke build like this — it's project-based (not restricted to a pre-approved vendor list, unlike the Productivity Solutions Grant, which explicitly excludes customised work). The Foundation build could still cite EDG's "system integration" criteria, but the AI-enhanced build is a noticeably stronger case for the "sophisticated software solution" / Automation language the grant is actually looking to fund.

Up to 50%of qualifying project cost, for eligible local SMEs

Base rate confirmed current

Track

Base cost

If EDG approved

Grant fit

Foundation build

—

Possible — weaker case

AI-enhanced build

—

Strong fit — Automation criteria

The trade-off in plain terms: the AI-enhanced build costs more up front, but if EDG approves it, its net cost can land below the Foundation build's full price — while giving you more than you originally asked for. If you'd rather not deal with a grant application at all, the Foundation build stands on its own as the lower-cost, lower-risk starting point. Both figures are illustrative and not guaranteed — see the caveats below.

What it covers: EDG's "Innovation & Productivity" pillar, Automation sub-category, explicitly names "adoption/development of sophisticated software solutions" and "system integration" — a reasonable textual fit for this project.
Who applies: The clinic applies directly via the Business Grants Portal — as the vendor, we can supply the quotation and scope documentation, but we cannot apply on your behalf or manage the grant relationship.
Not guaranteed: Approval is discretionary, case-by-case, and disbursed as reimbursement after project completion and audit — typically 8–12 weeks to process. Treat the 50% figure as a planning ceiling, not a committed discount.
Eligibility, as far as we could confirm: ≥30% local (Singapore Citizen/PR) shareholding, and standard SME thresholds (group turnover ≤S$100M or ≤200 employees) — worth double-checking directly with Enterprise Singapore or a grant consultant before you commit budget.
One thing to watch: Enterprise Singapore has signalled a consolidated "EDGE" grant (merging EDG, PSG and Market Readiness Assistance) targeted for later in 2026. It hadn't launched as of this proposal — terms could shift mid-engagement, so we'd recommend applying under current EDG terms sooner rather than later if this is something you want to pursue.
Productivity Solutions Grant (PSG) — not applicable here. PSG is restricted to pre-scoped packages from pre-approved vendors with no customisation permitted, which structurally excludes a bespoke build like this one.