Help ensure agent decisions are grounded in reality and explainable, enabling systems to choose the best possible outcome.
Enable cost-effective, accurate location reasoning in your agentic solution, even with complex constraints.
Co-create tailored agentic systems aligned to your specific industry needs, business logic and IT landscape.
Layer location intelligence on top of your agentic AI systems to make precise, real-time decisions with the industry’s most comprehensive, up-to-date and high-quality map data. Enhanced with critical domain intelligence, we deliver the accuracy your system needs to take autonomous action and thoroughly explain its rationale.
Process complex, constraint-rich queries with location reasoning that effectively extracts location intelligence so agents and LLMs can interpret and act on it. From rerouting fleets to avoiding restrictions or balancing anticipated risk against user goals, the engine allows agents to process and deliver operationally sound outcomes.
Drive intuitive human-to-agent and agent-to-agent interactions through natural language. Enable agents to read text, comprehend intent and negotiate, explain and coordinate effectively through natural language processing (NLP) across operational networks, from individual fleets to complete cities.
Harness enterprise-scale feedback loops to drive measurable improvements in data quality and operational efficiency. These systems allow agents to learn from new data, real-world behaviors and prior agent results.
Convert raw spatial data into rich real-world context that AI agents can understand and act on. By combining road structure, rules, patterns of movement and domain knowledge, HERE turns coordinates into a living, semantic map that helps agents navigate and reason about complex environments.
Find out how Sensos merges real time data from HERE with agentic AI to deliver intelligent logistics solutions.
Learn how agentic AI will deliver more intuitive data interfaces, optimize operations and create automated workflows.
Discover why Radio Free Mobile thinks AI’s superpowers lie in using natural language to communicate with technology
LLMs are fluent with words, but weak at spatial reasoning. This article explains why geography breaks next-token prediction, and why agentic AI needs structured location intelligence to act in the real world.
AI systems need more than language to plan, move and make decisions safely. Learn how location context, workflow design and real-world constraints can make LLM-powered agents more reliable.
Agentic AI doesn’t just respond to prompts but sets plans, makes decisions, carries out tasks on its own to achieve a goal.
With demand rising for tools that simplify operations instead of complicating them, automotive and logistics companies are turning to agentic AI that can plan, adapt and act in the real world, not just answer questions.
