HyperQ AI Vision pattern inspection takes 30 minutes to configure and 30 minutes of training before a line is live. Enterprise Singapore's Enterprise Development Grant approval, on the pre-approved route, takes 4 to 8 weeks. That gap -- 1 hour of deployment time versus 4 to 8 weeks of administrative lead time -- is the central planning constraint for Singapore manufacturers who want to use EDG funding for an AI inspection pilot. The grant window shapes the pilot calendar. Production schedules do not.
This post is not a restatement of what the EDG is. Enterprise Singapore publishes the programme overview, and the EDG guide for Singapore SMEs covers the programme structure and eligibility basics. What this post addresses is the applied layer: how to structure an AI inspection pilot scope so it fits the grant criteria, what documentation the vendor must supply before you submit, and why the grant application and the site acceptance test plan share roughly 70% of their paperwork -- which means you can write them together.
What EDG covers for AI inspection projects
Enterprise Development Grants support Singapore-registered companies in building capabilities in three broad areas: core capabilities, innovation and productivity, and market access. AI vision inspection projects typically qualify under the innovation and productivity pillar, specifically for automation of quality control processes.
Qualifying costs under a well-structured AI inspection project proposal typically include:
- Hardware: industrial cameras, lighting systems, industrial PCs, mounting hardware
- Software: AI model licences, inspection platform subscriptions
- System integration: wiring, network configuration, PLC interface work
- Training: operator and maintenance staff upskilling on the new system
- Project management and consultancy: if the project uses a registered system integrator
The grant covers a percentage of qualifying costs. The exact support level is confirmed during the application review and depends on company size, project type, and current grant utilisation. Manufacturers should obtain a current confirmation from Enterprise Singapore or a qualified grant consultancy rather than planning to a fixed percentage, because support levels are periodically revised.
What the grant does not cover: production downtime during commissioning, staff time for sample preparation during training, or any costs already invoiced before grant approval. The last point is the most common disqualifier for manufacturers who move fast -- if the vendor has already invoiced and work has already started, the project is ineligible for EDG funding retrospectively.
The pre-approved route vs custom application
Enterprise Singapore maintains a list of pre-approved solutions under various productivity and innovation programmes. A pre-approved solution has had its technical scope, vendor credentials, and cost structure reviewed in advance. When a manufacturer applies using a pre-approved solution, the documentation burden is lower and the approval timeline is compressed -- typically 4 to 8 weeks versus 8 to 16 weeks for a fully custom project.
Custom AI inspection projects -- where the solution is not on a pre-approved list -- require a full technical proposal: detailed scope of work, itemised cost breakdown, expected productivity outcomes with baseline data, implementation timeline, and vendor qualification evidence. These applications involve more back-and-forth with the portal review team and more risk of queries that extend the timeline.
The practical implication: if a manufacturer is targeting a Q1 production pilot, the application needs to be submitted by October at the latest on the pre-approved route, or August at the latest on the custom route. Most manufacturers who miss their funding window did not run out of time -- they started the application too late because they assumed the technical work (selecting the system, specifying the pilot) was the long-lead item. It is not. The approval process is.
The 70% paperwork overlap
The most actionable structural insight for a manufacturer planning an AI inspection pilot with EDG funding is this: the grant application and the site acceptance test (SAT) plan describe the same project. Roughly 70% of the documentation is shared.
The SAT plan for an AI vision system requires:
- Equipment specifications (camera model, lighting type, IPC hardware)
- Inspection scope (part types, defect classes, throughput rate)
- Performance criteria (target detection rate, false-positive ceiling, cycle time requirement)
- Test conditions (sample size, lighting configuration, part orientation)
- Acceptance thresholds (pass/fail criteria that trigger sign-off)
The EDG application requires:
- Project scope and description (same as inspection scope above)
- Equipment list with costs (same list, with vendor quotations attached)
- Expected productivity and quality outcomes (derived directly from the SAT acceptance criteria)
- Implementation timeline (same as the SAT schedule)
- Vendor qualifications (company registration, relevant deployments, technical credentials)
The additional documentation the grant application needs beyond the SAT plan: itemised vendor quotes, company financial statements, baseline productivity data (the current defect rate or manual inspection throughput to measure improvement against), and a brief statement linking the project to the company's business strategy.
Writing the SAT plan first and then using it as the source document for the grant application is faster than writing them independently and more accurate than writing the grant application from memory after the SAT is complete. The grant reviewer and the factory sign-off team are essentially evaluating the same project scope -- one from a funding-eligibility perspective and the other from a technical-performance perspective.
The site acceptance test framework is covered in the vision system acceptance test post, which lists the 12 SAT line items relevant for AI vision -- including the detection-rate targets and false-reject budget that translate directly into the "expected productivity improvement" field of the EDG application.
Vendor eligibility: what the AI vision vendor must provide
Enterprise Singapore requires that the grant applicant submit documentation from the vendor demonstrating that the vendor is qualified to deliver the project. For an AI inspection pilot, the vendor documentation package typically needs to include:
- Company registration certificate (ACRA registration or equivalent for Singapore-registered entities)
- Relevant project references (anonymised or named deployment case studies showing comparable applications)
- Technical proposal describing the specific system to be deployed, not a generic product brochure
- Itemised quotation covering all qualifying cost categories
- ISO or industry certification relevant to the system type, if applicable
A vendor that cannot supply an itemised quotation against a defined scope of work cannot support an EDG application, regardless of technical capability. The grant application is project-specific, not product-specific. "We will install our AI vision platform" is not sufficient. "We will deploy a two-camera global-shutter inspection cell with HyperQ AI Vision at 270 items per hour, configured for three defect classes on part type X, with a target detection rate of 99% and a false-reject ceiling of 5%" is sufficient.
For Singapore manufacturers, the vendor's local invoicing capability also matters. If the vendor invoices in a foreign currency from a foreign entity, the grant reimbursement process becomes more complicated. A local Singapore entity or a vendor with a Singapore-registered office simplifies the documentation path significantly.
What a strong vendor evidence pack looks like in practice: the reference deployments section should cite specific, measurable outcomes from comparable production applications, not generic capability statements. For an AI inspection pilot, that means documented throughput, detection rate, training data requirements, and commissioning time — the same figures that will appear in the SAT acceptance criteria. As a concrete illustration of the class of evidence that supports a reviewable outcome claim: 270 items per hour sustained in production, 99% defect detection across 8,000+ product variants, 1,000 training images to reach that rate (approximately 10 times fewer than a rule-based alternative requires on the same part families), and a commissioning profile of 30 minutes for pattern-inspection setup and 30 minutes of model training before the line is live. Forty-seven production contracts across semiconductor, automotive, display-panel, and PCB applications represent the reference base behind those figures. These are SAT-documented results, not product specifications — which is exactly what gives a grant reviewer the confidence to approve an outcome claim rather than flagging it as unsubstantiated. A vendor evidence pack built around this class of evidence translates directly into the "expected productivity improvement" field: if the applicant's current manual throughput is 40 items per hour, a vendor reference at 270 items per hour gives the reviewer a concrete magnitude of improvement the funded project is expected to deliver. Vague reference lists do not support quantified outcome claims and typically generate reviewer queries that extend the approval timeline.
Grant disqualifiers
An honest account of where the EDG route does not apply:
- Project already started: if any vendor invoice has been issued or work has commenced before grant approval, the project is ineligible for retrospective EDG funding. This is the most common disqualifier.
- No measurable productivity baseline: the application requires a before-measurement. If the manufacturer has no documented baseline for current defect rate, throughput, or manual inspection cost, the application reviewer has no way to evaluate the expected improvement. No baseline, no qualifying outcome.
- Vague scope: a grant application for "AI deployment across the production facility" without a defined project boundary (specific line, specific part family, specific defect classes) will receive queries that extend the approval timeline and may result in rejection.
- Manufacturer not the primary beneficiary: distributors, resellers, and third-party logistics providers are typically not eligible for the production automation pillar. The manufacturer operating the inspection line must be the grant applicant.
- Vendor not able to deliver a qualifying invoice: a foreign vendor invoicing without a Singapore entity does not produce a qualifying cost claim under most EDG project types.
- Duplicate funding: a project scope already funded by another Enterprise Singapore grant or another government funding scheme in the same period is not eligible for EDG support for the same costs.
Eligibility and evidence-pack checklist
Use this before submitting to the Business Grants Portal.
Company eligibility
| Criterion | Check |
|---|---|
| Company registered with ACRA and operating in Singapore | Required |
| Not a shell, holding company, or investment vehicle | Required |
| Prior EDG utilisation below annual cap for the period | Confirm with Enterprise Singapore or grant consultancy |
| Project not yet started (no vendor invoices issued) | Required |
Project scope documentation
| Document | What it must contain |
|---|---|
| Technical proposal from vendor | Specific system spec (camera model, frame rate, field of view, defect classes, target detection rate) |
| Itemised quotation | Hardware, software, integration, training broken out by line item |
| Baseline data | Current defect rate, manual inspection throughput, or quality cost -- measured, not estimated |
| Expected outcomes | Quantified improvement tied to the SAT acceptance criteria (e.g., 99% detection rate, 60% reduction in false-reject rework) |
| Implementation timeline | Week-by-week schedule from PO to SAT sign-off |
| SAT plan | Acceptance criteria, test conditions, sample plan -- this is the performance contract between manufacturer and vendor |
Vendor documentation
| Document | Purpose |
|---|---|
| ACRA business profile or equivalent registration | Confirms Singapore-registered entity or local representative |
| Reference deployments (minimum 2) | Demonstrates experience in comparable inspection applications |
| Staff credentials (lead engineer) | Supports vendor qualification claim |
| ISO or industry certifications | Relevant where EDG project type requires quality-management evidence |
Submission readiness check
- Grant application references the same inspection scope as the SAT plan
- All cost claims use SGD invoices from Singapore-registered entities
- Baseline measurement is documented and dated before project start
- Project start date is after the anticipated grant approval date, with buffer for delays
Stacking EDG with SkillsFuture Enterprise Credit
EDG and SkillsFuture Enterprise Credit (SFEC) can be applied to the same project where costs fall under different qualifying categories. EDG covers hardware, software, and integration. SFEC applies specifically to workforce training costs -- operator upskilling on the new inspection system, maintenance staff training on camera and lighting hardware, and quality engineer training on AI model management. These are separate qualifying cost categories and are not double-counted.
The practical implication: the "training" line item in the AI inspection project budget -- typically 10 to 15% of total project cost -- can be ring-fenced for SFEC rather than included in the EDG claim. This reduces the EDG claim size (keeping it within project caps) and applies a separate funding source to the workforce cost. Manufacturers who plan both claims from the start during the scope definition exercise avoid the administrative complexity of restructuring a submitted application later.
Timing the application to the pilot
The single most common planning mistake is treating grant application as a parallel workstream to system selection and vendor engagement. In practice, the application cannot be completed without the vendor quotation and technical proposal, which means the vendor must be selected before the application is submitted. And the application must be approved before the vendor starts work.
The correct sequence:
- Define the inspection scope and SAT criteria (this is also the application's "expected outcomes" section)
- Obtain vendor technical proposal and itemised quotation
- Measure the production baseline (defect rate, throughput, or quality cost)
- Submit the grant application via Business Grants Portal
- Receive approval (4-8 weeks pre-approved; 8-16 weeks custom)
- Issue purchase order to vendor
- Deploy, train, and execute SAT
- Submit reimbursement claim with SAT sign-off as supporting evidence
Steps 1 through 3 take 2 to 4 weeks with an organised vendor engagement. Adding the approval window: a manufacturer who begins the scope definition exercise in September can realistically start a funded pilot in January on the pre-approved route, or in February on the custom route. A manufacturer who starts in November is looking at March or April at the earliest.
Grant windows govern this calendar. Production priorities do not.
What the SAT plan produces that the grant application needs
The SAT plan is not just a post-deployment validation exercise -- it is the technical specification that makes the grant application reviewable. A grant application without a SAT plan is an application without measurable outcomes. An EDG reviewer cannot approve "AI inspection platform deployed on line 3" without a stated detection rate, a baseline for comparison, and a defined test plan that will confirm the outcome.
When the SAT plan is written first -- as the technical contract between the manufacturer and the vendor -- the grant application becomes a financial and eligibility wrapper around a project that is already fully defined. This is why the 70% paperwork overlap is not an approximation. The scope, the performance criteria, the timeline, and the equipment list are identical documents. Only the financial annexes and the company eligibility section are unique to the grant submission.
HyperQ AI Vision provides SAT plan templates as part of project scoping, covering detection rate targets, false-reject budgets, and sample plan structures that translate directly into the EDG "expected outcomes" fields.
Send your current inspection scope, the production baseline you want to improve against, and your target pilot start date. We will produce a vendor technical proposal and itemised quotation structured for EDG submission, commit to the SAT acceptance criteria before the purchase order, and deploy within the grant window once approval is confirmed.