The talent infrastructure
for 80 million
blue-collar workers.
An active AI agent that builds the career data blue-collar workers have never had — turning their reliability and skills into social trust, visible to employers for the first time.
Building investor relationships now. Formal Series A process opens September 2026.
Founders and Strong Teams
- Teambox (HR tech) co-founder
$2M ARR · 80% net margin · 5 yrs - Head of Recruiting, Cookpad (world's #1 recipe platform) — 100 hires/yr
- Consulted for:
- Google & Microsoft PhD Fellow (world top 3)
- Former CTO, Teambox (HR tech)
- Anthropic Fellowship (2025)
Research: ML × HCI · human resource development
Two co-founders, 10+ years working together. Keita saw hiring fail to scale from the inside. After relocating abroad, both experienced what it means to be trusted less — not because of ability, but because of background. Meeting a licensed electrician who couldn't find work for lack of verifiable data made the problem concrete. That gap became Blucor.
Empower the hard-working minorities no system has ever recognized.
80 million blue-collar workers power the global economy. They show up every day. They build things, move things, keep factories running. But no system has ever built career data for them.
Their reliability is invisible. Their trust doesn't accumulate anywhere. They're indistinguishable from someone who doesn't show up at all — and they have no way to prove otherwise.
We build the career data blue-collar workers have never had — trust scores that follow them, compound over time, and turn hard work into social and economic recognition.
80M workers have no career data — and both sides pay for it.
LinkedIn can't reach them. Indeed only captures a name and snapshot. Their reliability is invisible. They work hard — but there's no data to prove it.
Without trust data, every hire is a guess. 50% no-show rate. Wrong hires leave in 90 days. The loop repeats at full cost — forever.
An active AI agent that makes
worker trust visible —
for the first time.
Hope proactively reaches out to workers, builds their career data from scratch, and turns reliability and experience into a living trust score. Hard work finally compounds into something visible and socially trusted.
Accumulated automatically. Candidate does nothing.
Verified once. Factual. Durable.
Hope updates this every month. Candidate does nothing.
A trust score that proves reliability. A career that builds toward economic access — bank accounts, credit, social recognition. No longer invisible.
A talent pool with real trust data. The ability to find the reliable workers who were always there — but had no way to be found.
Every existing solution has broken data.
The infrastructure to collect this data never existed — not because the problem was unknown, but because the technology to build it wasn't there. Until now.
| Platform | Who updates data | Freshness | Candidate effort |
|---|---|---|---|
| User (rarely) | Months / years old | Required | |
| Indeed | User (at apply) | Frozen snapshot | Required |
| Staffing | Recruiter (per req.) | Starts from zero | Required |
Worker effort required to stay visible. Most workers don't bother. Trust stays invisible.
| Layer | Who updates | Freshness | Candidate effort |
|---|---|---|---|
| L1 Preference | Hope AI | Every month | Zero |
| L2 Credential | Hope AI | Verified once | Zero |
| L3 Behavioral | Auto-accumulated | Always current | Zero |
Candidate effort: zero. Hope updates automatically. Trust becomes a living score — visible to employers, on demand.
Three forces converged in 2024.
The window is 2–3 years wide.
GPT-4 crossed the voice quality threshold
Before 2024, workers dropped AI calls midway. After GPT-4's production deployment, existing clients told us unprompted: "The voice quality is incredible." We didn't change anything — the technology crossed a threshold.
80M workers have always had zero structured data
LinkedIn can't reach them. Indeed captures a name and phone number. The infrastructure was never built because the technology to build it didn't exist. Now it does.
Demand is spiking without a supply layer
Reshoring, data center construction, and manufacturing expansion are driving unprecedented demand for skilled blue-collar workers. The supply-side data infrastructure doesn't exist yet.
Whoever builds the data layer owns the category.
Indeed tried this in 2023.
They failed. Structurally.
In 2022, Indeed shifted to pay-per-application. SMB monthly spend jumped from $100 to $1,000+. Backlash was immediate. December 2023: fully reversed.
Indeed's revenue is click monetization: better matching = fewer clicks = less revenue. They structurally cannot solve quality matching without destroying their business model.
- Data that doesn't die. Hope's post-placement check-ins keep worker profiles active after hiring. The dataset compounds with every interaction.
- Trust Score network effect. At 100K workers, "Blucor or nothing" becomes the regional norm.
- Fortune Global 500 operational dependency. 300-position annual contracts. Switching cost: rebuild screening from zero.
| Capability | Blucor | Indeed | HireVue | Paradox | |
|---|---|---|---|---|---|
| Blue-collar reach | ✓ | Partial | ✗ | ✗ | ✗ |
| AI voice screening | ✓ | ✗ | ✗ | Video | ✓ |
| Own talent pool | ✓ | ✗ | ✗ | ✗ | ✗ |
| Post-hire tracking | ✓ | ✗ | ✗ | ✗ | ✗ |
| Success fee model | ✓ | ✗ | ✗ | ✗ | ✗ |
Three phases. $91B total addressable market.
Hope's 20-minute call doesn't just fill a position — it builds a worker's career record from scratch. Hiring is how we distribute. The data is why we built this. Detail → A07
$55B hiring market.
Blucor captures it at $4,500/hire.
80M workers × 25% turnover × $2,750 avg. cost
Fortune 500 + large-cap US manufacturers & distributors
2% US share = $900M ARR
The hiring market alone is a large, independent business — and the data we collect here is the foundation for a much larger infrastructure play. See next slide →
Platform fee proves PMF.
Success fee expands TAM 10x.
| Stream | Who pays | Amount |
|---|---|---|
| A — Platform Fee | Enterprise HR (annual) | $30K–$120K/yr |
| B — Success Fee | Enterprise + any SMB | 7% year-1 salary (~$4,500/hire) |
| C — Hope Retention | Platform clients (add-on) | $10/person/month |
Key insight: Stream A = enterprise SAM only. Stream B = every employer in the US with a blue-collar opening — same product, 10× TAM.
22x in 7 months.
Fortune Global 500 signed. $2.76M pipeline.
$12,700 MRR
Aug 2025 → Mar 2026
0 churn · 5mo avg tenure
$1.2M total raised to reach $170K ARR — 1 Fortune Global 500 logo + 9 enterprise/SMB clients, zero churn, 3,000-person talent pool.
$384 in. $4,500 out.
~12x per transaction.
| Candidate acquisition (20 × $19.20 Google Ads CAC) | $384 |
| Total per hire | $384 |
| Success fee (7% × $65K avg salary) | $4,550 |
| Platform fee (annualized per hire) | $600–$800 |
| Total revenue per hire | $4,500–$5,300 |
Fortune Global 500 manufacturer.
Trial to full contract.
Daikin's US manufacturing operations needed a reliable pipeline for blue-collar workers — screened, vetted, and interview-ready. Job boards weren't delivering. Agency fees were compounding.
Hope accessed Blucor's talent pool and proactively screened candidates to Daikin's spec — 24/7, in English and Spanish. No job board postings. No agency markups. Ranked candidates delivered before HR reviewed a single resume.
Pilot SOW signed. April 2026 launch. 70-position trial underway.
Trial converts to full contract at 250 positions. $1.05M+ ARR potential from a single account. Post-Daikin pipeline: Honda.
US manufacturer.
Annual contract. Zero churn.
Twin City Fan needed a consistent pipeline for fan assembly workers across multiple shifts. Traditional recruiting was slow, expensive, and produced candidates who ghosted before day one.
Hope automated first-round screening, reaching candidates within the hour — before they applied elsewhere. Every applicant phone-screened and ranked before HR reviewed a single resume.
Annual contract signed. $54K ARR. Zero churn since onboarding.
"Hope screened 40 candidates in 72 hours. We hired 3."
— Matthew Dillon, Twin City Fan
Recycling plant.
Fully hired in 2 weeks.
Geomet Recycling needed workers for physically demanding roles with high turnover. Every open position meant lost throughput. Standard job boards returned unqualified candidates who didn't show up.
Hope proactively reached candidates in Blucor's talent pool who matched the physical and availability requirements — screened and shortlisted before the client posted a single job ad.
Open positions filled within 2 weeks. Ongoing contract. Reorder within 60 days of first hire.
SMB accounts like Geomet prove the self-serve motion: low CAC, fast close, high reorder rate. The engine that funds enterprise growth.
How we build to $2M ARR.
Two customer categories. One compounding model.
$153K
$512K
$2.82M
Traditional staffing's moat was headcount.
Ours is automation depth.
Built $0 → $170K ARR on $1.2M. Owns enterprise sales and product direction. Japanese enterprise network gave direct access to Fortune Global 500 logo before product was complete.
Built Hope, post-placement check-in system, and candidate data layer in 6 months. All core IP in-house. 8/10 steps of the hiring automation roadmap automated by April 30.
Pre-Series A: AI Outbound Operator (student, AI-native, already validated).
Post-Series A: English-native Enterprise Closer · $120K + incentive.
$1.2M in. Profitable
before we raise.
$1M
10 customers
Channel A live
Series A open
Series A: $10–15M.
First priced round. Angel SAFE + Bridge convert at cap. 10–15% dilution. 22+ months runway post-close.
(pool 3K → 100K)
(Trust Score, API)
(Closer + Sales Head)
Jul 2026 | Break-even. Channel A 100P/month live. |
Sep 2026 | Series A process opens. 20+ customers. |
Dec 2026 | $2M ARR. Trust Score live. Series A closes. |
"The data infrastructure for 80 million blue-collar workers has never existed. We've proven the unit economics on $1.2M. This raise is to own the category."
BlancAI Inc. is the legal entity (Delaware C-Corp). Blucor is the brand and product name (lowercase c — always). The plan is to rename the legal entity to Blucor Inc. post-Series A.
| Stat | Source |
|---|---|
| 30–50% interview no-show rate | SHRM Blue-Collar Hiring Report; Blucor client interviews |
| 6-week avg. time-to-fill | SHRM / LinkedIn Talent Trends 2024 (manufacturing) |
| 25–30% agency placement fee | Industry standard; confirmed by Daikin, TTS procurement teams |
| 80M US blue-collar workers | BLS: Non-supervisory production/transportation workers 2024 |
| 2.7B global deskless workers | McKinsey Global Institute 2023 |
- Before: AI voice calls had robotic pacing. Workers hung up mid-conversation.
- After: Existing clients told us unprompted: "The voice quality is incredible." Same product — technology crossed a threshold.
- 2024 deployment lag: Retell AI's production-grade pipeline + Blucor's prompt engineering reached reliability threshold in mid-2024.
Trust Score not yet implemented. Target: 0.81% conv rate post Trust Score (May 2026).
| Cost per posting | $100 |
| Interviews per posting | ~20 |
| Hires per posting | 1 |
| Revenue per hire | $4,500 |
| Current volume | ~3–5/month |
| Target (July 2026) | 100/month |
Currently measuring. Target: 60%+ of Resume Sent pool. Hope's monthly check-in is the engine.
The 3,000-person pool is a reservoir, not a hiring channel. Google Ads converts anonymous workers into structured, scored profiles. Current hire count (~2) reflects that pool→position matching is not yet automated — it activates when Trust Score goes live (May 2026) and Channel A reaches scale (July 2026). The $3.45/$19.20 CAC is a long-term moat investment tracked separately from per-hire cost accounting.
All current hires and revenue flow through Channel A: post an Indeed job ($100) → Hope screens 20 candidates in 24 hours → 1 interview-ready hire → $4,500 revenue. This channel is fully proven and scales to 100 positions/month by July 2026 via the Indeed Partner API. The pool provides the moat; Channel A provides the revenue. By Series A, both channels converge into a single automated pipeline.
- Keita's Japanese enterprise network gave direct access to Daikin, Itochu, and TTS — including Fortune Global 500 group companies — before having a fully built product.
- Hiromu built Hope in 6 months — AI voice pipeline, post-placement check-in, candidate scoring, and employer portal all in-house.
- Blucor is the only team to have actually completed end-to-end blue-collar AI placements (618 Resume Sent, confirmed hires).
At 10K workers in a region, switching costs make it difficult for a new entrant. At 100K, it becomes near-impossible. We're building toward 100K by Series B.
Window closes when: (1) a funded competitor reaches regional pool density, (2) Indeed/LinkedIn acquires a voice AI company, or (3) labor demand normalizes.
| Client | Contract Status | Position Ramp | ARR Potential | Timing |
|---|---|---|---|---|
| TTS | Annual signed | Ongoing | $3.6M (success fee) | Active now |
| Daikin | Trial SOW signed | 70P trial → 250P full | $1.05M+ (platform + success) | April 2026 |
| Itochu | Annual signed | 300P/year confirmed | $1.26M (success fee) | Active; ramp Q2-Q3 |
| Ricoh | Trial confirmed | TBD | TBD | Q2 2026 |
| Honda | Post-Daikin pipeline | TBD | TBD | H2 2026 |
| Steel-IQ / NMB USA | Follow-up pending | SMB scale | ~$30K each | Q2-Q3 2026 |
US enterprise concentration risk: English-native Sales Head confirmed post-raise. Target: US-native enterprises = 50%+ of customer count by Series A close (Dec 2026).
| Platform fee (MRR × 12) | ~$152K ARR |
| Success fee (YTD 2026) | ~$12–15K |
| Hope check-in (deployed, not yet billed) | ~$0 |
| Total | ~$170K ARR |
| US blue-collar workers | 80M (BLS 2024) |
| Annual turnover rate | 25% (SHRM mfg avg) |
| Annual hires | 20M |
| Avg. hiring cost / placement | $2,750 |
| TAM | $55B |
| SAM (mfg + wholesale) | $15B |
| Blucor SOM (3yr) | $2.6B |
BLS Occupational Employment Statistics 2024 · SHRM Hiring Benchmarking 2023 · IBISWorld Staffing 2024
| US Employment Screening + Verification (2024) | $5.9B |
| └ Equifax Verification Services alone | ~$2.0B/yr |
| └ Equifax market share | ~34% |
| Equifax: 149M verifications in 2024 | 734M records |
| Argyle ($110M raised) · Truework ($400M val) | early comps |
| TAM (US, current) | ~$6B |
| Global by 2033 (14% CAGR) | $16B+ |
| SAM (blue-collar real-time) | ~$2B |
Equifax Q2–Q4 2024 earnings releases (public) · Verified Market Reports 2024 · DataIntelo Income Verification Platform 2024 · Sacra / Argyle/Truework funding disclosures
| US open banking market (2030 forecast) | $31.2B |
| └ CAGR 2024–2030 | 27.6% |
| Alt credit scoring (global, 2033) | $8.7–11.7B (19–23% CAGR) |
| 45M credit-invisible Americans | CFPB + TransUnion confirmed |
| US auto loans outstanding | $1.66T (NY Fed Q4 2024) |
| US personal loans outstanding | $249B (TransUnion 2024) |
| Plaid ARR (2024) · valuation | $390M · $6.1B |
| TAM (US open banking, by 2030) | $30B+ |
| SAM (blue-collar financial identity) | ~$8B |
Grand View Research Open Banking 2024 (CAGR 27.6% confirmed) · CFPB Credit Invisible primary research · TransUnion newsroom 2023 · NY Fed Household Debt Q4 2024 · Sacra / Plaid 2025 funding disclosures
| Competitor | What they do | Why they can't copy Blucor |
|---|---|---|
| Indeed | Job board, click monetization | Revenue model structurally conflicts with matching quality. Proved by Dec 2023 reversal. |
| White-collar professional network | Core product requires self-authored profiles. 80M blue-collar workers can't use it. | |
| HireVue | Enterprise video/AI interview (white-collar) | Built for Fortune 500 corporate roles. No blue-collar voice screening, no talent pool. |
| Paradox (Olivia) | Conversational AI for high-volume hiring | Operates within existing ATS systems. No pool ownership. No post-hire data. |
| Workday / SAP | Enterprise HCM, white-collar ATS | No blue-collar talent pool. No voice AI. Different buyer entirely. |
| Mercor | White-collar freelance talent pool | Global remote white-collar. No blue-collar. No voice. Different data model. |
| Bottleneck | Solution | Deadline |
|---|---|---|
| JD confirmation (45 min/posting) | GPT-4o form → v2 | Apr mid |
| Contract + Stripe (2 hr/client) | DocuSign + Stripe Billing auto | Apr end |
| Indeed posting (60 min/post) | Indeed Partner API + Zapier | May end |
| Role | When | Comp | Profile |
|---|---|---|---|
| AI Outbound Operator | Now | Low base | Student, AI-native. Previous student: outbound → trial in 3 weeks. |
| Enterprise Closer | Post-Series A | $120K + incentive | US-based, enterprise B2B. "Committed pending raise." |
| English-native Sales Head | Post-Series A | $150K+ | US enterprise expansion. Drives 50% US customer target. |
| Platform (signed + Daikin ramp) | ~$0.8M ARR |
| Channel A (100P/month ramp, ~40 hires avg) | ~$0.9M ARR |
| Success fee (existing pipeline) | ~$0.3M ARR |
| Total Dec 2026 | ~$2.0M ARR |
Key dependency: Channel A requires Indeed Partner API live by May 2026.
| Platform only | ~$0.8M ARR |
| Channel A partial (3 months) | ~$0.3M ARR |
| Success fee | ~$0.2M ARR |
| Bear case Dec 2026 | ~$1.3M ARR |
Bear case: profitable at $1.3M ARR but Series A timing → Q1 2027.
| Period | ARR | Growth | Round |
|---|---|---|---|
| Mar 2026 | $170K | — | Angel SAFE |
| Dec 2026 | $2M | 12× | Series A open |
| Dec 2027 | $8M | 4× | → Series B |
| Dec 2028 | $32M | 4× | → Growth |
| Dec 2029 | $96M | 3× | — |
| Dec 2031 | $300M+ | 3× | → Exit / IPO $5B+ |
| ① Revenue multiple | Dec 2026 $2M ARR × 40× forward = $80M |
| ② Mercor comp (adjusted) | Mercor Series A: $250M on $35M ARR (7×). Blucor: earlier stage + infrastructure premium (Phase 2/3) = net 40× forward justified. |
| ③ Capital efficiency | $1.2M → $2M ARR + profitability. Equivalent cap efficiency = 35–50× forward ARR. |
| Keita (Common) | 1,000,000 shares | 70% |
| Option pool (unissued) | 428,571 shares | 30% |
| Angel + Bridge (SAFE) | $1.2M outstanding | Converts at cap |
40× justified by Phase 2 infrastructure premium. Phase 1 alone = $2M × 15× = $30M valuation.