Services
Combination of geographic information systems with machine learning to process planetary-scale satellite imagery, edge data, and spatial coordinates for national defense, climate monitoring, and smart city infrastructure planning. Sub-services include GeoAI for satellite imagery object detection, ArcGIS AI assistant integration, real-time geospatial intelligence analytics platforms, and climate risk spatial modeling.
Engineering of high-throughput AI pipelines for processing petabytes of satellite imagery from constellations like Sentinel and Landsat, enabling continent-scale object detection, land cover classification, and change detection for environmental monitoring and defense intelligence.
Development and deployment of specialized computer vision models (e.g., YOLO, Detectron2) trained on aerial and satellite imagery to identify and track objects like vehicles, ships, aircraft, and infrastructure with high precision for security and logistics applications.
Integration of foundational language models with spatial databases and GIS platforms to enable natural language querying of geospatial data, automated report generation from maps, and contextual analysis of location-based intelligence.
Architecture of retrieval-augmented generation systems specifically for geospatial knowledge bases, combining vector search across map tiles, satellite metadata, and spatial reports with LLMs to provide accurate, sourced intelligence summaries.
Deployment of lightweight AI models on drones, UAVs, and IoT devices at the edge to perform immediate geospatial analysis (e.g., damage assessment, object counting) without cloud latency, crucial for disaster response and field operations.
End-to-end service for curating domain-specific geospatial datasets, training custom models (e.g., using SAM 2 for segmentation), and fine-tuning foundation models for specific tasks like crop health analysis or urban sprawl detection.
Building of continuous training and deployment pipelines for geospatial AI, incorporating version control for models and training data, automated retraining on new imagery, and performance monitoring in production environments.
Development of predictive AI models that fuse climate data with geospatial layers to forecast and visualize risks like flood plains, wildfire susceptibility, and coastal erosion for insurance, government, and urban planning sectors.
Custom integration and extension of Esri's ArcGIS AI tools and assistants, automating complex spatial analysis workflows, connecting proprietary data sources, and building tailored dashboards for enterprise GIS users.
Engineering of multimodal AI systems that combine LiDAR point clouds, radar returns, and optical imagery to create detailed 3D terrain models, perform structural analysis, and enable navigation in low-visibility conditions for autonomous systems.
Development of real-time intelligence platforms that integrate satellite, drone, and social media data to map disaster impact, prioritize response areas, and model evacuation routes using AI-driven spatial analytics.
Implementation of AI models that analyze satellite and drone imagery over time to predict failures in critical infrastructure like pipelines, power lines, and railways, enabling proactive maintenance and reducing downtime.
Creation of high-fidelity synthetic geospatial datasets (imagery, point clouds) to overcome data scarcity for rare events, protect sensitive locations, and robustly train AI models without privacy or copyright concerns.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
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We understand the task, the users, and where AI can actually help.
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We define what needs search, automation, or product integration.
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We implement the part that proves the value first.
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We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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