Product Design
- SaaS based
- User interaction through text & Region of Interest
- Agentic AI task ececution
Product Details
Service Offering
- Vehicle Counting
- Region Classification
- Area calculation
- Aggregation
- Vegetation Index
- GIS intelligence
Unique Features
- Get Answers, Not just data!
- Automate Complex Location Intelligence Tasks
- Predict Future Location-based outcomes
- Make Decisions with complete picture
- Trust insights with clear explanations
- Explore "What if" scenarios to discover
- Get advices tailored to local market & industry
What is Tmaps AI?
AI-powered Geospatial Platform
Tmaps AI empowers organizations to make faster, smarter, and spatially informed decisions. From land-use planning to logistics optimization, our platform brings advanced geospatial analytics and automation to your fingertips.
Unlocking Autonomous GIS
In a world where spatial decisions shape economies, cities, and ecosystems, traditional GIS tools are no longer enough. Tmaps AI is redefining how geospatial intelligence is accessed, interpreted, and acted upon. By combining large language models, agentic reasoning, and real-time data fusion, we enable organizations to move beyond static maps and into a future of interactive, AI-driven spatial decision-making. Whether it’s land-use assignment, infrastructure planning, or industrial site selection, our autonomous GIS engine transforms complexity into clarity.
At the core of autonomous GIS is the ability to automate reasoning over space—understanding regions, interpreting layers, running optimization models, and producing insights without human micromanagement. With Tmaps AI’s platform, users can ask questions in natural language, simulate multi-criteria decisions, and delegate spatial tasks to AI agents—all through an intuitive interface powered by Leaflet and PostGIS. It’s GIS reimagined—not just as a tool, but as an intelligent collaborator.
Core Features
Autonomous GIS Engine:Integrate satellite data, OSM, and enterprise layers to drive real-time spatial insights
Agentic AI Workflows:Let AI agents process AoIs, assign tasks, and deliver outputs autonomously.
Multi-Criteria Decision Analysis (MCDA):Optimize land, logistics, or investment decisions using advanced geospatial models.
Reinforcement Learning for Spatial Optimization:Simulate and learn best strategies for resource allocation, routing, and zoning.
LLM Integration:Ask natural language questions about land parcels, zoning rules, or urban dynamics—and get actionable answers.
Use Cases
