Turning Earth observation into risk decisions.
EO2DM fuses satellite optical, radar and hyperspectral data with AI anomaly detection to help India's mining operators, regulators and insurers see risk before it becomes loss — illegal extraction, ground instability, tailings-dam failure, and mispriced exposure.
Ground truth arrives too late, too partial, and too expensive.
India's minerals economy is scaling fast, but the risk infrastructure hasn't kept up. Enforcement, safety and underwriting still rely on sporadic field inspections that cover a fraction of sites — leaving revenue, lives and capital exposed.
Illegal & unpermitted mining
National satellite surveillance exists, but reporting shows nearly half of illegal-mining triggers go un-actioned for years. Extraction without paid royalties has cost the exchequer thousands of crores.
Catastrophic ground failure
Tailings failures keep coming — Brumadinho (2019), Jagersfontein (2022), Zambia’s 2025 Kafue River spill that hit water for ~60% of the country. Movement is often measurable months in advance — but no one is watching continuously.
Blind, mispriced risk
Insurers underwrite mines, infrastructure and land with stale or self-reported data. Claims are slow to validate and fraud is hard to catch without an independent, time-stamped record.
An anomaly-detection engine for the built and mined environment.
EO2DM continuously ingests multi-sensor Earth observation over client-defined Areas of Interest, learns each site's normal behaviour, and flags statistically significant deviations with quantified confidence — delivered as alerts, reports, or an API into existing workflows.
Multi-sensor fusion
Optical (Sentinel-2, Landsat, high-res tasking), SAR/InSAR (Sentinel-1) and hyperspectral, fused across space, spectrum and time.
Learn the baseline
Generative & transformer models build a per-AOI expectation of vegetation, water, surface and deformation behaviour.
Flag anomalies
Probabilistic deviation scoring separates real change from noise — new pits, encroachment, movement, contamination.
Deliver decisions
Prioritised alerts, audit-ready reports and API feeds into enforcement, HSE and underwriting systems.
Radar that sees through monsoon
SAR/InSAR penetrates cloud, rain and smoke — reliable monitoring in exactly the conditions when optical fails and risk peaks.
Millimetre early warning
InSAR detects 1–2 mm of surface displacement, revealing slope and embankment instability long before visible failure.
Explainable AI, quantified uncertainty
Every flag carries a confidence score and evidence imagery — defensible for regulators, auditors and reinsurers.
The same anomaly signal is worth money to two buyers.
MINING & REGULATORS
- Illegal / boundary-breach detection — new excavation, over-lease extraction and encroachment flagged automatically across a state.
- Tailings-dam & slope stability — continuous InSAR deformation monitoring with early-warning thresholds.
- Subsidence over underground workings — track sinking above old and active mines that threatens villages and rail.
- Environmental & rehabilitation compliance — water contamination, dust, vegetation loss and mine-closure verification.
- Production & volume estimation — stockpile and pit-progression analytics for royalty reconciliation.
INSURANCE & REINSURANCE
- Underwriting risk scoring — independent, site-level hazard grades for mines, plants, solar farms and infrastructure.
- Exposure verification — confirm what is actually on the ground vs. what was declared at bind.
- Parametric triggers — objective EO indices that auto-settle flood, drought and land-movement covers.
- Claims validation & fraud — time-stamped before/after imagery to confirm loss and dates.
- Portfolio accumulation — geospatial view of correlated risk across an entire book.
“Progressive Snapshot” for mines — the monitor that sets the rate.
Usage-based insurance already prices auto premiums off real driving behaviour — a ~$62B market with ~20M usage-based motor policies worldwide. EO2DM is the telematics box for a mine: satellite-observed deformation, freeboard and housekeeping become an independent MRV record and a live risk score insurers price against.
Condition of cover
Insurers require EO2DM monitoring to bind and keep coverage.
Every mine a subscriber
The insurer becomes EO2DM’s low-CAC distribution channel.
Behaviour-based premiums
Continuous MRV drives dynamic pricing and loss-control alerts.
Widening moat
Lower loss ratios lead to more insured mines, more data, and sharper pricing.
Why now: failures keep coming (Brumadinho 2019; Zambia’s Kafue River spill, 2025) — insurers have cut tailings limits by ~a third, doubled premiums, some refuse cover, and now demand independent third-party monitoring. EO2DM is that layer.
A large, structurally growing, under-served market.
The global Earth-observation market (~$4–9B depending on scope) is growing, with value-added analytics — exactly EO2DM's layer — the fastest-growing segment (~10% CAGR). India is one of the highest-leverage geographies: enormous mineral and agricultural exposure, a national push on mining, and newly opened satellite-data access.
EO analytics for mining, insurance & infrastructure risk across South & Southeast Asia and comparable emerging markets.
India mining-risk & insurance-analytics spend addressable via EO — regulators, PSUs, private miners, insurers & reinsurers.
Beachhead: a handful of state mining departments, PSU miners and 2–3 insurers on recurring monitoring contracts.
The policy and data tailwinds just turned on.
Indian Space Policy 2023 & IN-SPACe opened the sector to private players with a single-window regulator and dedicated funds, including a ₹500 cr technology-adoption fund and a ~$120M space VC fund.
Free & open ISRO data to 5 m resolution plus a private-led 12-satellite EO constellation (Pixxel, SatSure et al.) collapse the cost of high-frequency coverage.
Government mandate to double mining's GDP share to 5% by 2030 — with intense scrutiny on illegal mining and mine safety.
Insurance going digital & parametric — schemes like PMFBY cover 30M+ farmers and are moving to remote-sensing yield estimation (YES-TECH), normalising EO in underwriting.
Earth-observation science meets industrial go-to-market.
A rare pairing for this market: two decades of front-line industrial asset-monitoring sales in India, alongside deep remote-sensing and AI science. That combination is our edge — we know both the technology and the buyer.
Sachin Chadha
~20 years leading industrial predictive-analytics and asset-performance sales at Baker Hughes, GE Oil & Gas and Rockwell Automation. Deep relationships across energy, industrial and EPC buyers in India. Leads commercial strategy and go-to-market.
Saurav Kumar, PhD
Remote sensing, hyperspectral imaging and AI for Earth systems. Leads the scientific vision, detection algorithms and validation methodology.
Team — building
Recruiting India-based geospatial engineering and domain advisors across mining regulation and insurance underwriting.
Let's put eyes on the ground — from orbit.
We're raising a pre-seed round to build the India pilot, land our first regulator and insurer contracts, and productise the platform. Request the full investor deck and technical brief.
Contact ussaurav.kumar@eo2dm.com · sachin.chadha@eo2dm.com