The questions every serious investor asks, answered without hedging.

SAFE (Simple Agreement for Future Equity) with a post-money valuation cap of US$ 2.0M and MFN (most-favored-nation) clause. No discount. Conversion at the next priced round, or at the cap if the next round is above it. Standard SAFE template; we're happy to send the executed template document for legal review on signed NDA.

US$ 20,000. This is a deliberate floor — we want investors who can write a meaningful check, attend quarterly updates, and add value beyond capital. Below US$ 20,000 we point individual supporters toward the platform itself and our community.

The floor (US$ 100K) is what the 18-month plan needs. The ceiling (US$ 150K) gives us a 50% buffer for opportunistic hires or pilots without diluting more than necessary. If we are oversubscribed past US$ 150K we either close at the cap or take additional capital only at the same terms with explicit founder consent.

At the US$ 2.0M post-money cap: US$ 20K minimum = ~0.99% post-money; US$ 100K = 4.76%; US$ 150K = 6.98%. These are conversion-equivalent at the cap; actual cap-table dilution materializes only at the next priced round.

Q3 2026, no later than September 30. We will close earlier if we hit the ceiling.

Three anchors. (1) Replacement cost: ~24 months of focused engineering, product, design, and AI-integration work shipped end-to-end including i18n, deployment, content, and standards integration. At market rates this is US$ 600K–1.2M of work alone. (2) Comparables: post-MVP, pre-revenue AI-HR-tech raises typically cap at US$ 1.5M–5M depending on team and traction; we sit at the lower end because of the pre-revenue status and the upper end because of the platform breadth and standards depth. (3) Round economics: dilution of 5–7% at the floor and ceiling respectively is the right shape for an angel round; that math drives the US$ 2.0M cap.

Because we already have a built platform. The raise extends focus to GTM and a small first hire wave — that work doesn't need US$ 1M. Raising more would mean either taking on hires we can't productively absorb in 18 months or pre-spending against a revenue trajectory we haven't validated yet. We'd rather price the next round from real ARR than over-raise now and price the next round defensively.

Not in this round. We'll do a priced Series Seed 12–18 months from now once there's ARR to anchor the valuation conversation. SAFE keeps this round simple and cheap from a legal-fees perspective on both sides.

Mechanical Layer: hundreds of evaluation profiles across dozens of sectors and multiple levels · thousands of multilingual competency questions · cognitive / personality / DISC / aptitude tests · CV evaluator + creator + translator · salary aspiration estimator · interview simulator · recruitment 7-step end-to-end (Define · Open · Score · Rank · Simulate · Prep · Decide, audit-logged and ISCO-mapped) · candidate pipeline · job-fit scoring · climate surveys · 360 reviews · ISCO-08/ESCO crosswalk · public job board · certificate issuance.

Transformative Layer: Personal Growth Plan (12/24/36-month) · AI-Readiness Assessment (individual + organizational) · Career Path Navigator (ISCO-grounded) · Org Transformation Plan (CHRO-grade) · Scenario Simulators (Committee Defense, AML Triage, Cash Crisis, Variance Investigation, Skill Simulator) · Smoother Experiences integration with branded Custom Academies / Digital Learning Divisions · Unified Activity dashboard · Communities of Practice.

Operational stack out-of-the-box: HRIS · ATS · payroll & accounting · SSO/identity (Google/Microsoft/Okta) · calendars & messaging (Outlook/Slack/Teams/Google) — open APIs, webhooks, SCIM, SAML. Standards: ILO · ISCO-08 · ESCO · GDPR. Built around your criteria, your priorities, and your values.

Two things. (1) The two-layer framing requires editorial commitment, not engineering — incumbents have spent a decade selling “your HR suite, but with AI bolted on,” and the Transformative Layer requires the opposite framing (humans first, AI as instrument). They can't pivot the narrative without contradicting their own marketing. (2) Trilingual + ISCO/ESCO native + LATAM-first is a structural commitment they would have to retrofit. We started here. The platform is built around it.

None of that means incumbents won't encroach. It does mean we have a real 24–36 month head start in the markets we've chosen to win first.

They under-serve HR specifically because HR sales cycles are long, taxonomies are complex, and the buyer is a CHRO not an engineer. Generic AI startups optimize for engineering-led adoption (the ChatGPT/Cursor playbook). HR doesn't buy that way. We do.

It was attempted. Most attempts foundered on one of three rocks: (1) building only the Mechanical Layer and competing as “cheaper Workday”; (2) building only the Transformative Layer and being unable to sell it without a Mechanical Layer foothold; (3) launching English-only and missing the LATAM / francophone / Iberian markets that are the most underserved. We routed around all three.

It would be at a Series A. At an angel round of this size, the question is whether the founder can credibly deliver 18 months of focused execution with the raise — and the evidence is the existing platform. The first two hires post-raise are engineers; a GTM lead follows within 6 months. We're not asking investors to fund a team that doesn't exist; we're asking them to fund the expansion of execution that has already been demonstrated.

No formal board at this stage (SAFE round, single founder). Advisor slots reserved for HR-tech veterans, AI-ethics academics, and LATAM/Iberian channel leaders. Strategic advisor positions (0.25–0.50% equity each, 2-year cliff-free vesting) available for the right people; investors are welcome to propose names.

Two paths. (1) Strategic acquisition by an HR-suite incumbent (Workday, SAP SuccessFactors, Personio, Sage, BambooHR) at US$ 50M–250M, 5–7 years out, at 8–15× ARR. (2) Acquisition by a learning / certifications platform (Coursera, Pluralsight, Multiverse) or a labor-data / classification platform (Lightcast, similar) at similar multiples. We are not optimizing for either specifically; the strategy is to build the business that's worth acquiring at multiple natural endpoints.

IPO is a stretch from here but not excluded. Three Year-3 base-case ARR of US$ 6–8M sustained through Year 5 at 30%+ growth puts a public listing on the table in the right macro window.

Indicative, not promised: at a US$ 50M acquisition 5 years out, the cap entry returns roughly 25× pre-dilution from this round. At US$ 100M, ~50×. At US$ 250M, ~125×. These are gross of subsequent dilution (which will reduce the multiplier roughly 30–50%). The realistic angel-round expectation: 5–15× net of dilution at the median outcome; 0× at the failure tail; 50×+ at the upside tail. Standard angel power-law.

Under signed NDA: cap table, founder agreement, code repository access, customer pilot artifacts, financial model with monthly cohort projections, technical architecture review document, IP assignment confirmation, executed SAFE template. Available within 24 hours of NDA signature.

Email invest@skaills.ai with check size and a preferred 30-minute call window. We respond same business day. After the call, we send the diligence pack under NDA. From signed NDA to signed SAFE is typically 7–14 days.