Silurian
Custom AI foundation models for weather & infrastructure impact simulation
Silurian is a strong fit for utilities and agencies with proprietary data who need hyper-local, AI-driven weather intelligence. Its GFT models beat generic forecasts for grid resilience and rime-ice detection, but the lack of self-service and public pricing limits it to enterprises with dedicated budgets and data pipelines. If you're a large utility like Hydro-Québec, the 0.72 average precision on rime-ice alerts justifies the investment. For smaller teams or those needing instant API access, consider alternatives like Tomorrow.io or Climacell.
Verified 2d ago · liveness 58/100 · cite: rightaichoice.com/tools/silurian
- Energy utilities needing grid resilience against extreme weather
- Government agencies requiring localized weather intelligence
- Infrastructure operators with asset-level weather risk
- Enterprises with proprietary data feeds to train custom models
- Users needing free or low-cost public weather data
- Small businesses without dedicated data pipelines
- Hobbyist weather enthusiasts seeking consumer apps
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Skip Silurian if you need instant self-serve weather data, a public API, or a low-cost off-the-shelf solution—this is a bespoke enterprise service requiring proprietary data pipelines, a dedicated budget, and a sales engagement.
You'll need to invest in data infrastructure and proprietary data pipelines before Silurian can even start training your model, which can be a significant upfront cost.
Silurian's pricing is custom and likely premium, fitting large utilities and government agencies with dedicated budgets for critical infrastructure protection. Compared to off-the-shelf weather APIs like Tomorrow.io (which offer self-serve tiers starting around $50/mo), Silurian's bespoke modeling is a far larger investment, but it delivers asset-specific accuracy that APIs can't.
In short
Silurian — Custom AI foundation models for weather & infrastructure impact simulation. Best for Energy utilities needing grid resilience against extreme weather, Government agencies requiring localized weather intelligence, Infrastructure operators with asset-level weather risk. Contact Sales pricing.
What's new in Silurian
Checked 2 days agoAcross the latest 2 updates: 1 feature update and 1 launch.
Day-Ahead Rime-Ice: From Reactive to Preventive
Silurian's GFT model delivers day-ahead rime-ice alerts for Hydro-Québec with 0.72 average precision, reducing dispatch costs.
GFT for the Power Grid: Silurian and Hydro-Québec Partnership
Silurian partners with Hydro-Québec to train GFT on utility-grade grid data for early icing warnings; results presented at CIGRE 2025.
What people actually say about Silurian — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
28 mentions across 2 sources (Hacker News, Lemmy) · researched Jul 3, 2026.
- +Specialized in high-resolution regional weather forecasting for infrastructure assets.
- +Built on Generative Forecasting Transformer (GFT) foundation model technology.
- +Offers fine-tuning on proprietary client data for specific use cases like rime-ice.
- +Provides rapidly refreshing forecasts, unlike slow traditional numerical weather prediction.
- +Team includes co-creators of ClimaX and lead authors of Aurora model.
- −Zero community feedback available to validate claimed capabilities.
- −No independent benchmarks or third-party reviews published.
- −Pricing opaque — requires contacting sales with no public tiers.
- −Unknown integration support; no documented APIs or plugins.
- −Only covers weather — not broader Earth simulation as tagline suggests.
- • No public pricing — potential setup fees or minimum commitments unknown
- • Custom model fine-tuning may require significant data engineering investment
Viability Score
How well maintained and how widely used is Silurian? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: August 2026
How we score →Key Features
- Custom foundation model training on client data
- High-resolution regional weather forecasts
- Rapidly refreshing AI-powered forecasts
- 72-hour severe weather early warnings
- Day-ahead rime-ice detection for power grids
- GFT-C for tropical cyclone intensification/prediction
- Grid observation data integration for rime-ice warnings
- Early warnings for power grid operators (Hydro-Québec case)
- Asset-level forecasting for utilities
- Weather impact simulation on infrastructure
- Generative Forecasting Transformer (GFT) models
- AI-based weather model fine-tuning
- Proprietary data feed integration
- Aurora foundation model lineage
About Silurian
Silurian AI builds tailored foundation models that simulate Earth's weather and its impact on physical assets, helping energy utilities and government agencies move from reaction to prevention. Instead of a one-size-fits-all weather API, Silurian trains its Generative Forecasting Transformer (GFT) on your proprietary data feeds—grid observations, asset telemetry, and more—to deliver high-resolution regional forecasts and asset-level intelligence that general-purpose models can't match. The company is founded by the team behind the Aurora foundation model, the first foundation model for the Earth system, giving it deep research pedigree. GFT models are deployed in partnership with enterprises, not as a self-service tool. In collaboration with Hydro-Québec, Silurian's GFT delivers day-ahead rime-ice alerts with 0.72 average precision, helping grid operators cut dispatch costs and prevent catastrophic icing events. The GFT-C variant adds early predictions for tropical cyclone intensification and dissipation, demonstrated with Pacific storm Henriette and Atlantic hurricane Erin. Silurian also provides 72-hour severe weather early warnings and rapidly refreshing AI-powered forecasts, replacing slower numerical weather prediction for asset-heavy operators. CEO Jayesh K. Gupta testified before the House Environment Subcommittee in July 2025, underscoring its role in public-sector weather intelligence. For organizations with dedicated data pipelines and budgets, Silurian is a specialized enterprise alternative to off-the-shelf weather services—not a fit for individuals or teams needing instant API access.
Behind the Verdict
Silurian AI occupies a unique niche: it doesn't sell a weather API you can plug into on day one; it builds custom foundation models trained on your own data. This is a fundamental difference from most weather services, which offer standardized forecasts. The strength here is precision: by fine-tuning on your grid's specific observations, Silurian's GFT can detect rime-ice events with 0.72 average precision—a level of accuracy that generic models can't match, as demonstrated in the Hydro-Québec case. This can translate directly into cost savings by preventing catastrophic icing events and reducing dispatch costs. The team's pedigree—the creators of the Aurora foundation model—lends credibility to their research claims. However, this bespoke approach has drawbacks. You need proprietary data feeds and dedicated pipelines, which means significant upfront investment in data infrastructure. Pricing is not public, so budgeting is uncertain until you engage in a sales conversation. There's no self-serve API, no public documentation of the sort you'd find with Developer-friendly platforms. The website is minimal, with no changelog or integration pages, making it hard to evaluate the product without a demo. In short, Silurian is a high-stakes, high-reward enterprise play for organizations with serious weather-related risks and the resources to build custom AI models. It's not for anyone who needs a quick, off-the-shelf weather solution.
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Real-world workflow fit
Concrete scenarios for the personas Silurian actually fits — and what changes day-one when you adopt it.
You want to prevent rime-ice damage on power lines.
Outcome: Within weeks, Silurian trains a GFT model on your grid observation data, delivering day-ahead rime-ice alerts with 0.72 average precision, letting you pre-position crews and avoid catastrophic outages.
You need early warnings for tropical cyclones to plan evacuations.
Outcome: Silurian deploys a GFT-C model that predicts intensification and dissipation patterns, giving you extra days of lead time for Pacific and Atlantic storms compared to traditional forecasts.
You want to simulate how a specific facility will fare under future weather extremes.
Outcome: Silurian builds a custom model that integrates your asset telemetry to simulate weather impacts at the asset level, helping you prioritize retrofits and improve long-term resilience planning.
Use Cases
- Deploy custom foundation models to forecast high-resolution regional weather for energy grid operators.
- Train AI models on utility-grade grid observation data to detect rime-ice risks 72 hours in advance.
- Simulate asset-level weather impacts for infrastructure resilience planning.
- Predict tropical cyclone intensification and dissipation paths using GFT-C models.
- Integrate proprietary data feeds into tailored earth intelligence models for government agencies.
- Reduce dispatch costs and operational risks with actionable day-ahead weather alerts.
Models Under the Hood
as of 2026-08-19
Limitations
- Limited public information; pricing is not listed on the website.
- The models are tailored to client data, requiring proprietary data feeds and dedicated pipelines for deployment.
- Public documentation, changelog, and detailed integration pages are empty, suggesting limited self-serve access.
- No explicit API documentation is available on the site, though the header links to an API page.
as of 2026-08-21
Verification history
We have re-verified Silurian 5 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Silurian's pricing actually pencils out — and where peers do it cheaper.
Silurian's pricing is custom and likely premium, fitting large utilities and government agencies with dedicated budgets for critical infrastructure protection. Compared to off-the-shelf weather APIs like Tomorrow.io (which offer self-serve tiers starting around $50/mo), Silurian's bespoke modeling is a far larger investment, but it delivers asset-specific accuracy that APIs can't.
Setup time & first value
How long it actually takes to get something useful out of Silurian — broken out by persona, not the marketing-page minute.
Setup takes several weeks to months, depending on data readiness and partnership process. After initial data integration and model training, your team gets tailored forecasts during a pilot phase before full deployment.
Switching to or from Silurian
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From legacy numerical weather prediction (NWP) systems: Transition from slower generic models by providing your historical grid data to Silurian for custom model training, replacing NWP with rapidly refreshing AI
- ↗To off-the-shelf weather APIs (e.g., Tomorrow.io, OpenWeather): Export any derived forecasts or alerts from Silurian via their deployment team, then switch to a self-serve API if your needs standardize.
Resources & Guides
Tutorials & Learning
Official links
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Featured Head-to-Head Comparisons
Silurian vs Spider Cloud
If your business needs custom, high-resolution weather forecasting for infrastructure resilience, Silurian is your specialized enterprise partner. For AI agents and RAG pipelines requiring fast, cost-effective web data extraction, Spider Cloud is the clear choice with its freemium model, Rust engine, and expanding feature set. Choose based on your data domain: weather vs. web.
Silurian vs Temporal Ai
Temporal AI and Silurian serve completely different needs. Choose Temporal if you need a battle-tested durable execution platform to build reliable AI agents or orchestrate microservices with automatic retries and state recovery—especially with its recent usage-based billing and Serverless Workers. Choose Silurian only if you are a utility or government agency requiring custom AI-based weather forecasting models trained on your own data; it is a specialized enterprise tool with no self-service pricing.
Silurian vs Screenplayiq
ScreenplayIQ and Silurian serve entirely different domains: screenplay analytics for entertainment vs. weather simulation for infrastructure resilience. Your choice depends purely on your industry: if you write feature films, ScreenplayIQ offers affordable tiers with box office prediction; if you manage weather-exposed infrastructure, Silurian’s custom models provide enterprise-grade forecasts. There is no overlap.
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