TL;DR
Why now
- WA/ANZ boards carry a positive duty on psychosocial hazards
- Claims and premiums are rising on a compulsory spend line
- Frontline contexts are under-served by existing tools
First lane
- ISO 45003 Board‑Readiness Pack
- Deploy in 14 days, board-ready inside 90
- Live control coverage, intervention log, audit trail
Compounding upside
- Data flywheel from capture → interventions → outcomes
- Attrition, fatigue, interpersonal dynamics modules post-readiness
- Simple per-seat pilot pricing; outcome fees later once validated
Why now (WA → Worldwide)
- Legal shove: psychosocial hazards on same footing as other WHS risks; boards must show live, effective controls
- Economic pull: rising claim costs and premiums against payroll
- Tooling gap: Echo meets FIFO and shift workers in their vernacular, on devices they already use
First 90 days: ISO 45003 Board-Readiness Pack
Inputs
- Weekly 90-second check-ins (voice/WhatsApp)
- Roster and incident feeds
- Site context and policy map
Outputs
- Live Control Coverage and Hazard Heatmap
- Intervention Log with time-to-action
- Quarterly Board Pack and audit trail
Operating promise
- Deploy in 14 days on pilot sites
- Board-ready inside 90 days
- Privacy dials aligned to worker-council expectations
Proves now, unlocks next
- Proves: participation, privacy/governance, operational discipline
- Unlocks: attrition risk, fatigue index, interpersonal conflict, later jurisdiction-specific financial mapping
Business model (year one)
- Per-seat subscription comparable to leading EHS suites
- Fixed-scope pilot, 90-day exit
- Modules layered post-pilot (attrition, fatigue, scheduling)
- Outcome-based components only after independent validation
Go-to-market
- WA heavy-industry beachhead (mining, energy, healthcare, logistics)
- Time-boxed design-partner cohort with co-authored governance
- Broker-supported introductions and safety leadership forums
- Global expansion via copy-paste playbooks from WA
Pre-pilot diligence materials
Privacy & governance
- PIA summary by a recognised firm
- Privacy console screenshots and policy dials
- ISO 27001 gap analysis and audit logging
Pilot protocol
- Population, inclusion criteria and success metrics
- Decision gate and deployment plan
- Worker-council comms templates
Product artefacts
- Demo conversations with paralinguistic telemetry
- Method playbook and facilitation guides
- Metrics dashboards and KPI definitions
- Sample board pack
Roadmap after board-readiness
Attrition
Risk flags, supervisor prompts, and replacement forecasting to stabilise teams.
Fatigue
Roster risk index, alerting and mitigations tuned to shift patterns and site context.
Scheduling
Team design and shift optimisation using human-factor signals and constraints.
Then: translate improvements into jurisdiction‑specific frequency/severity trends and premium trajectories as data matures.
Why this compounds
Data flywheel
Every check-in, intervention and outcome labels the model. Early sites seed benchmarks that later sites rely on.
Frontline engagement edge
Timing, tone and turn-taking tuned for FIFO and shifts; hard to fake without the data and scripts.
Speed + trust
Shipping cadence across privacy-sensitive deployments builds political capital and raises switching costs.
Under the hood: defensible feature engineering around voice-derived fatigue/stress signals and standardised board outputs used in WHS ops.
Milestones (18–24 months)
-
Q1–Q2
- 3–5 WA design-partner deployments
- ≥ 60% monthly participation
- Privacy and governance verified
-
Q3
- Global expansion playbooks live
- Attrition & fatigue modules in production
-
Q4
- Independent analysis links controls to reduced claim frequency/severity
-
Following Q1
- Scale to ~100k covered lives across priority global beachheads
Team
Fletch Young · Founder/CPO
Ex-UBER. WA launch to nine-figure GTV; BHP Mining & Met ops → Strategy & BD; enterprise healthcare AI strategy. Eng/Sci; LBS MBA.
Leonardo Fernandez Sanchez · Founding CTO
Ex-Unilever Digital Ventures CTO; ex-McKinsey tech lead. Real-time data platforms, SRE discipline, secure cloud.
Mark Heath · Commercial Advisor
Ex-Goldman IBD → Uber ANZ leadership → Sequoia-backed founder; now COO at an ag-tech scaleup. Fundraising and enterprise BD.
Tom White · Exec Sponsor & AI Ethics Chair
Ex-UBER. Scaled regulated tech across APAC; deep WA resources network and policy interface. MA AI Ethics Cambridge.
Prof. Warren Mansell · Psychology Advisor
Global authority on Perceptual Control Theory; BA Cambridge, DClinPsy KCL, DPhil Oxford. Guides psych modelling and intervention logic.
Risks & mitigations
“Surveillance” push-back
Radical transparency, opt-ins, anonymised cohorts; narrow, auditable safety exceptions; worker-benefit first.
Cold start without claims
Start with compliance outcomes and early proxies, then connect to frequency/severity as data matures.
Feature replication
Lean on frontline engagement, privacy reputation and accepted board benchmarks; partner defensibly in WA/ANZ.
The frontline economy: massive, regulated, hiding in plain sight
Developed markets at a glance
- Frontline & high-risk workers: ~140–180 million
- Annual payroll tied to these roles: ~US$5–6 trillion
- Employers with ≥500 frontline staff: ~40–60k
Scope: US, UK, EU, CA, AU, NZ, JP, KR. Roles include mining, energy, logistics, manufacturing, construction, healthcare, aged care, utilities, aviation/rail, and retail ops with safety exposure.
Why this spend is durable
- Legal duty of care: psychosocial and safety obligations are explicit and rising.
- Consumer safety risk: fatigue/distraction translate directly into incidents and brand exposure.
- Insurance & audit pressure: boards must evidence live controls, not intent.
This converts wellbeing from “nice to have” into a compulsory operating control with budget.
Simple, conservative TAM math
- Targetable seats near-term: **100–150 million** (safety-critical frontline in developed markets)
- Echo pilot pricing (per-seat): US$10–15 pmpm (US$120–180 per year)
- 1% penetration of 150m seats → ~US$180–270m ARR
- 5% penetration → ~US$0.9–1.35bn ARR
Illustrative scenarios only. Final pricing and mix vary by sector and jurisdiction.
Where the workers are (illustrative ranges)
Healthcare & Aged Care
- ~20–35m clinicians, nurses, carers
- High consumer-safety sensitivity; shift fatigue
- Typical loaded pay band: US$40–80k
Logistics, Transport & Distribution
- ~15–25m drivers, warehouse, last-mile
- Fatigue, distraction, linehaul isolation
- Loaded pay band: US$40–65k
Manufacturing & Fabrication
- ~30–50m operators, technicians
- High-tempo floors; error costs compound
- Loaded pay band: US$50–70k
Construction
- ~12–20m trades, site crews
- Permit pressure; subcontractor complexity
- Loaded pay band: US$55–80k
Energy, Utilities, Oil & Gas
- ~3–6m field crews, plant ops
- Critical lifts/permits; remote work
- Loaded pay band: US$80–110k
Mining
- ~1–3m pit & processing roles
- Rostered isolation; heavy mobile equipment
- Loaded pay band: US$90–130k
Why this matters for Echo
- Same problem, many jurisdictions: shift-work fatigue and psychosocial risk present the same failure modes from Perth to Pittsburgh.
- Copy-paste playbooks: WA pilots establish evidence and privacy governance that travel globally with minor localisation.
- Data flywheel: more sites → richer labels → better interventions → measurable outcomes → higher value per seat.
- WA wedge
- Global scale
- Board-grade controls
Notes: figures are rounded ranges compiled from national labour statistics and industry reports; they serve to show order-of-magnitude only. Detailed, sourced breakouts appear in the data room.
Investor FAQ
Are you doing gain-share or outcome pricing?
Pilots are per-seat only to keep procurement simple. Outcome-based components are considered after independent validation; not required to start.
Where does Echo start and expand?
Western Australia first, then global heavy-industry and healthcare beachheads with similar workforce profiles. Financial impact is tailored by jurisdiction after board-readiness is established.
How do you protect worker privacy?
Two-stream architecture: private coaching to workers; anonymised cohort analytics to management. Tunable dials for retention, anonymity thresholds and safety exceptions.