Dust accumulation accounts for 32% of energy loss. Thermal overheating adds 18%. Unplanned downtime takes another 5–8%.
For a single 300 MW solar farm in Saudi Arabia, that's an estimated $7.7M in lost generation revenue every year — not from a single catastrophic failure, but from conditions that build silently and go undetected.
The desert isn't the problem. Operating without prediction is.
Sunlight uses patented nanotechnology and AI-driven predictive intelligence to identify efficiency threats before they become losses — giving solar operators the power to intervene at exactly the right moment, not after the damage is done.
Our AI models analyze micro-climate data and panel-level telemetry to forecast accumulation rates, allowing for hyper-targeted cleaning schedules.
Stop managing problems after they appear. Sunlight tells you what's coming, so your team acts with precision and confidence.
By predicting exactly when and where intervention is needed, Sunlight reduces unnecessary water use and cuts carbon emissions across your entire operation.
Sunlight isn't just a concept — it's a technology with signed partnerships, institutional backing, and accelerator validation behind it.
Who Committed with us
A US-based AI infrastructure and power management company. Karios has formally committed to co-develop Sunlight's AI model frameworks for predictive maintenance, thermal management, and cleaning optimization — with full compliance to Saudi data sovereignty regulations (SDAIA, NDMO, PDPL).
A European advanced coatings company. SDC has signed an LOI to combine their 2D printing deposition technology with Sunlight's patented superhydrophobic coatings — co-developing a dust-reduction and anti-reflective solution for solar glass at scale.
A US-based data management and digital intelligence company. Signed an LOI to provide Sunlight with data infrastructure, AI optimization pipelines, and real-time analytics capabilities.
$100K seed fund recipient
Early-stage startup program
Deep technology validation program
Saudi Arabia's flagship startup accelerator
Saudi Arabia's solar potential is world-class. But the desert environment introduces a set of operating costs that most financial models underestimate — or ignore entirely. Here's what's really eating into your returns.
Saudi Arabia sits within one of the world's most active dust source regions. The Empty Quarter, Al-Dahna, and Al-Nofuth deserts blanket more than 30% of the country. Soiling accumulates daily, and sandstorms — which peak in spring and summer, precisely when production and demand are highest — can strip 20% of output in a single event. Left uncleaned for six months, KSA panels have recorded power drops exceeding 50%.
Stats:2–50% — Power loss range across KSA, 20% — Single sandstorm impact, 50% — 6-month unclean loss (Dhahran)
Cost Factor 01
Every silicon panel loses 0.3–0.5% of output for each degree above its 25°C test standard. When ambient temperatures exceed 50°C and panel surfaces go higher still, the efficiency gap between your P50 projection and real-world generation becomes a permanent revenue shortfall. Over 25 years, the compounding effect on IRR is significant — and it accelerates physical degradation of encapsulants, backsheets, and junction boxes, shortening effective asset life.
Stats:0.4%/°C — Typical silicon efficiency loss, 3–8% — Annual yield gap vs. P50, 50°C+ — KSA peak ambient temperature
Cost Factor 02
When failures are detected after they happen, the cost compounds quickly: emergency technician mobilization, expedited spare parts sourced from Europe or Asia, lost generation during repair windows, and potential contractual penalties on PPAs. In remote KSA desert sites, inverter or SCADA failures can mean days — not hours — of downtime while parts clear customs and crews travel to site.
Stats:3–5× — Cost premium: reactive vs. predictive, SAR 200K–1M+ — Per major unplanned failure event, 2–4 weeks — Typical parts lead time from overseas
Cost Factor 03
Monthly cleaning is the minimum recommended frequency for KSA sites — immediately after every sandstorm on top of that. Most utility-scale desert sites have no local water source. Water must be trucked in, stored in on-site tanks, and managed under strict national water regulations. Transportation costs alone can exceed the cost of the cleaning labor itself for remote sites in the Rub' Al Khali or northern regions.
Stats:SAR 15–40K — Water cost per MW per year, 12+ — Minimum cleaning cycles per year, High — Transport cost at remote sites
Cost Factor 04
Waterless robotic cleaning systems eliminate water trucking, reduce labor dependency, and can operate at night to avoid thermal shock on hot panels. But the upfront CapEx is substantial — typically SAR 150,000–400,000 per unit — and each unit covers a limited panel area. For a 50 MW farm, the full fleet investment can reach SAR 5–10M before operational savings materialize.
Stats:SAR 150–400K — Per robot unit (CapEx), SAR 5–10M — Fleet cost for 50 MW farm, 60–80% — Water reduction vs. manual, <2.5µm — Fine dust particle size robots miss, Invisible — Film undetectable by visual inspection, Ongoing — Accumulation continues post-cleaning
Cost Factor 05
From raw sensor data to optimized maintenance — fully automated, always on.
The platform connects directly with your solar farm's SCADA system, IoT sensors, and thermal monitoring devices — ingesting real-time operational and environmental data without disrupting existing infrastructure.
AI runs directly on-site — no cloud dependency, no delays. Machine learning models process panel temperature, weather conditions, dust levels, and performance trends in real time, identifying early signs of efficiency loss before they escalate into production failures.
The system flags overheating hotspots, abnormal panel behavior, and soiling accumulation — then automatically generates prioritized alerts and targeted maintenance recommendations in real time.
Operators act on precise, data-driven recommendations — cleaning and servicing panels before losses occur. The result: higher energy yield, less downtime, and significantly lower operational costs.
A Saudi materials engineer and nanotechnology specialist with an MSc from the Catholic University of America and a Women Innovators Fellowship at Georgetown McDonough School of Business. Rehab spent years researching the degradation patterns that desert climates inflict on solar infrastructure — and turned that research into a patented predictive solution. She founded Sunlight with one mission: bring that technology to scale across the region's most critical energy assets.
Jackie brings a rare combination of technical depth and operational discipline to Sunlight. With a background in software development at Lockheed Martin and leadership experience at JPMorgan Chase and Publix, he has built and scaled systems in some of the world's most demanding environments. At Sunlight, he leads team structure, internal operations, and the organizational infrastructure that turns a breakthrough predictive technology into a deployable product.
As Chief Technology Officer, Abdul Rehman spearheads the technology vision and architectural strategy for Sunlight CoSolar. Combining an MS in Computer Engineering with over five years of enterprise software engineering experience, he directs the integration of proprietary AIoT and predictive machine learning ecosystems. Abdul transforms real-time data into high-value operational intelligence, positioning Sunlight at the forefront of automated solar infrastructure.
