Problem

Opal addresses the costly gap between the volume and complexity of real-world data and the slow, manual workflows used to interpret it. Insurers spend hours documenting claims, cities rely on labor-intensive infrastructure inspections, and property and construction teams need expensive scanners or trained operators to create usable building models. In wildfire management, agencies, utilities, and communities must combine satellite imagery, weather, LiDAR, and other geospatial data quickly enough to make decisions before conditions change.

The clearest flagship use case is wildfire risk and disaster management in the wildland–urban interface, where homes, businesses, and critical infrastructure meet flammable vegetation. Opal’s goal is to shift customers from reactive response to proactive mitigation: FireVision provides property-level risk ratings updated hourly and forecasts up to 48 hours ahead, supporting evacuation planning, resource allocation, grid-hardening decisions, and community preparedness. The economic value is reduced manual analysis and faster decisions when delays can increase claims costs, emergency-response costs, infrastructure damage, and loss of life.

Product / Service

Opal is a spatial-intelligence and decision-support company whose AI converts video, satellite, LiDAR, 360-camera, sensor, and other multimodal data into operational outputs. Its product suite includes FireVision for wildfire intelligence, Astro Adjuster for automated property-claims documentation, Urbanomy for urban infrastructure assessment, and ScanToBIM/ScanTo3D for floor plans, CAD models, and building information models. The company combines vision-language models, physics-informed AI, remote sensing, weather modeling, and geospatial analytics, and sells a mix of enterprise and government solutions, professional scanning/model-generation services, and a mobile iOS application.

The workflow is designed to replace specialist-heavy analysis with automated processing and human-facing decision tools. Astro Adjuster analyzes audio and video, detects damage, transcribes conversations, and generates structured reports; FireVision integrates satellite-derived fuel and meteorological data with a conversational decision-support agent; Urbanomy maps and rates roads, sidewalks, and other assets; and ScanTo3D lets users capture spaces with an iPhone or iPad before Opal generates 2D or 3D deliverables. The claimed benefit is to compress work that normally takes hours, weeks, or a month into minutes or days while improving consistency and accessibility.

Market

Opal competes across overlapping spatial AI, geospatial intelligence, InsurTech, PropTech, GovTech, disaster-management, and infrastructure-analytics markets rather than in a single narrow software category. Its competitive set varies by product: for building capture, BIM, and 3D modeling, publicly identified alternatives include Autodesk, Cupix, and NavVis, while claims automation and wildfire-intelligence products place it alongside specialized insurance, remote-sensing, emergency-management, and climate-risk platforms. Opal differentiates around multimodal reasoning, real-world spatial data, and decision support for government agencies, utilities, insurers, cities, and other enterprise users.

The company has meaningful public validation but limited disclosed commercial metrics. NASA awarded Opal more than $1 million in Phase I and II SBIR funding for FireVision; the company says its technology has also been validated by the National Science Foundation and the U.S. Department of Transportation, and it was selected as a finalist for PG&E’s 2025 Pitch Fest. Opal says it is conducting FireVision pilots with fire departments, government agencies, and utilities, and cites a customer testimonial that reduced floor-plan turnaround from a month to two days. No public revenue figure was found in the reviewed materials, so Opal is best characterized as grant- and pilot-backed with early customer validation rather than definitively labeled pre-revenue.