AI
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Introducing the new Agentic Queryable Earth: Conversational, Composable, and Traceable
We discuss the evolution of Queryable Earth into Agentic Queryable Earth, including a more conversational experience.
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Introducing the new Agentic Queryable Earth: Conversational, Composable, and Traceable
We discuss the evolution of Queryable Earth into Agentic Queryable Earth, including a more conversational experience.
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Getting Acquainted with Element 84: A Guide to our Intro Client Calls
In this blog we give a sneak preview into the typical conversation structure we have with new-to-us organizations through frequently asked questions that we regularly answer during introductory calls.
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De-Risking AI: A Roadmap for AI Integration in Finance and Other Highly Regulated Industries
For businesses operating in highly regulated industries, zero risk tolerance policies often lead to delays in AI adoption. Although there are certainly risks that accompany irresponsible AI use, with intentional implementation AI has the potential to boost productivity, reduce risk, and increase profits. Furthermore, failing to implement AI is a risk of its own in…
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ChatGSFC: Building Composable AI Tools for NASA on Open Source Tooling
Sharing our findings from the past year helping NASA build and scale a chat-based AI tool called ChatGSFC.
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Building Conversational Interfaces for Querying and Analyzing Geospatial Data
NOAA maintains thousands of datasets of various kinds (remote sensing, in-situ, derived etc.) across multiple domains (climate, weather, ecology, etc.) consumed by a wide variety of users (scientists, engineers, urban planners, etc.), but discovering, accessing, and using these datasets remains a significant challenge. Recent developments in cloud-native geospatial technologies and standards have made geospatial data…
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Building and Validating LLM-Generated Captions and Embeddings for Geospatial Imagery in Queryable Earth
At Element 84, we’ve been exploring how LLMs can improve geospatial imagery search. We recently published a blog post detailing our latest updates to our Queryable Earth demo which lets users search for visible features on the Earth using natural language. Until recently, it relied entirely on SkyCLIP, an open-source vision-language model, to generate the…
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AI Coding and the Future of Open-Source Geospatial Software
In an episode of Star Trek: The Next Generation, Commander Data (an android), creates a new android, Lal. His creation, paralleling the new generation of AI-assisted tools, extends her creator’s capabilities but also begins to operate autonomously. Lal begins to learn, evolve, and act independently, faster than Data can fully guide her. Eventually, she is…
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Beyond the Hype: Element 84’s Pragmatic Vision for AI in Engineering
At Element 84, we’ve always been focused on solving our clients’ most complex geospatial problems with high-quality, reliable, and scalable software. We’re excited about AI’s potential to accelerate development and allow our engineers to focus their creative energy on core problem-solving. To achieve that without sacrificing our quality and reliability, our approach is centered around…
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Mobilizing Metadata; using STAC to Manage Risk in the Reinsurance Industry
Data doesn’t have any value unless you can use it… and trust it. Users need to quickly access data and know where it came from. This is especially true with the integration of AI, making quick access more achievable but data provenance more opaque. This is where STAC comes in. The reinsurance industry uses climate…
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Introducing Natural Language Geocoding v0.1.0: An LLM-Enabled Geocoding Database
The landscape of geospatial AI is rapidly evolving. Many organizations are building LLM-powered solutions that tackle complex geospatial problems and answer sophisticated questions about our planet. These agentic approaches allow LLMs to autonomously select from toolsets that include geospatial tools, Earth Observation (EO) catalogs, and EO data processing capabilities. The result? Systems that can process…
