Partnership Proposal
Scaling Ocean Economy AI Lab's AI Capability
Prepared for [CEO Name] · [Date]
MELLONE
Context
Where Ocean Economy AI Lab stands today
EEZ coverage
2M km²
Mauritius's Exclusive Economic Zone
Target species
Yellowfin & bigeye
Tuna — 1M+ tonnes/yr, Indian Ocean
Scientific partner
OceanEyes (Japan)
Projected 30–40% productivity gains
Status
Launched, May 2026
PFG tool demoed; live fisherman trials
Georges Chung Tick Kan
Founder & President
Vishal Seeboruth
Chief Executive Officer
Vanessa Chellen
Chief Technology Officer
Dr. Hidekazu Kasahara
Scientific Partner, OceanEyes
The ambition: position Mauritius as the Indian Ocean's reference point for ocean-data intelligence. Turning that ambition into reality starts with the AI and data engineering capability behind it.
The challenge
A capability gap the local market can't supply
These are live, immediate requirements — not a future plan. And Mauritius's AI and data engineering talent pool is genuinely thin: a known structural reality, not a reflection of anyone's hiring effort.
Mauritius's own national AI strategy names limited AI expertise among the country's structural challenges.
AI Engineer
Data Engineer
Recruiting, vetting, and retaining this kind of specialised talent starts from zero in this market — and that's before the operational weight of doing it alone.
The real cost
Going it alone costs more than salary
| United States | Europe | Asia | |
| AI/ML Engineer | $120K–$190K | $70K–$110K | $90K–$125K |
| Data Engineer | $115K–$155K | $65K–$105K | $90K–$125K |
Sources: Indeed, Glassdoor, ZipRecruiter, KORE1 (US) · Glassdoor, DigitalDefynd, TechStaq (Europe) · Morgan McKinley Asia-Pacific salary guide (Asia)
And in India specifically, going it alone means
Misclassification & PE tax risk
FEMA, GST & TDS paperwork
IT & security infra
High churn in niche AI/data roles
Sources: RBI/FEMA inward remittance guidelines · India Income Tax Act business-connection provisions · Aon India 2026 attrition data
There's a way to get this capability in India — without the misclassification risk, the paperwork, or the replacement cycles.
The model
A dedicated team, without the operational weight
Ocean Economy AI Lab
Directs the work
Mellone
Sources · employs · manages · absorbs compliance, infrastructure & continuity
AI Engineer + Data Engineer
Based in India
What this resolves
Misclassification & PE tax risk
FEMA, GST & TDS paperwork
IT & security infra
High churn in niche roles
Here's exactly how that works, step by step.
How it works
A defined process, start to finish
Sourcing & vetting
First-level technical screening by Mellone
Candidate review
Joint review & interviews with OEL
Onboarding
Infrastructure & access setup
Ongoing management
Reporting cadence + continuity coverage
Every step protects the same thing: trust in how your data is handled.
Data trust & governance
The same principles you've already committed to
Ocean Economy AI Lab has been public about leading with trust and transparency — respecting data ownership, ensuring ethical use, and operating under clear contractual frameworks with every stakeholder. The same principles govern how this engagement handles your satellite, oceanographic, and fisheries data.
IP & data ownership
All satellite, oceanographic & fisheries data stays fully OEL's
Controlled access
Engineers access only what's needed for assigned work
Contractual confidentiality
NDAs & data-handling terms in place from day one
Trust isn't a feature here — it's the foundation everything else is built on.
Why Mellone
Practitioner-led, not a staffing vendor
Mellone trains and works alongside AI practitioners directly — vetting rigor and capability development aren't outsourced, they're how we operate.
Practitioner-led
Vetting rigor & capability development built in, not bolted on
Already active in Mauritius
Direct corporate training, plus in-market delivery through Spectrum AI
Continuous upskilling
Directly addresses the attrition risk flagged earlier
And it's not an anonymous bench — here's who's behind it.
The team behind Mellone
Networks that make sourcing — and retention — easier
Rakesh Venugopal
Co-Founder, Product & Strategy
Indian School of Business"Seed to Series F — strategy, growth & org transformation"
Swadhin Sahu
Co-Founder, Operations & Revenue
"Ed-tech to AI products & services — revenue, growth, analytics & operations"
Balwinder Singh
Tech Advisor
NIT Allahabad"Enterprise data & AI engineering leadership — Nike, Amadeus, Lowe's"
Between them, networks built across India's top engineering and business institutions — the same networks this engagement draws on for sourcing, vetting, and retention.
That's the team and the model. Here's the investment.
The investment
A fraction of the global benchmark, fully managed
Global market equivalent
$100K – $190K
Per role, per year
Through Mellone
$65K
Per role, per year · incl. quarterly visits to Mauritius
Negotiable — we're focused on making this work, not maximizing margin.
Convenience
Cost savings
Other benefits
Ready to move fast — here's the rollout timeline.
Timeline
Fast mobilization, start to impact
Weeks 1–2
Parallel sourcing & shortlisting, both roles
Week 3
Technical interviews with OEL
Week 4
Offers & onboarding
Weeks 5–6
Ramp-up into active PFG & data workflows
Actual joining dates depend on each candidate's current notice period — commonly 30–90 days in India. Sourcing and interviews should begin immediately to protect this timeline.
Six weeks from kickoff to contributing work — let's set the date.
Next steps
Three steps to kickoff
Align on final terms
Sign the services agreement
Kick off sourcing immediately, to protect the six-week window
Let's build the capability behind Mauritius's next phase of ocean-data leadership.
Thank you.
We'd be glad to answer questions, walk through the process in detail, or schedule a call to discuss next steps directly.
Rakesh Venugopal, Co-Founder, CEO
rakesh@mellone.ai · +91 8129428742
