AI that understands your data.
Nomic operationalizes AI over complex files, documents and datasets.
Deploying modern AI systems requires unlocking your data: complex thousand page PDFs, deep file systems with millions of documents filled with domain knowledge.
At Nomic, we build a platform and models that help businesses and developers deploy AI across their most complex data sources.
At Nomic, we build a platform and models that help businesses and developers deploy AI across their most complex data sources.
Platform
Nomic Platform
Developer APIs for embeddings, document parsing, extraction and vector search
Production-ready APIs that power intelligent applications with advanced text processing and semantic search capabilities.
- Embedding APIs for text, images, and multimodal content
- Document parsing and extraction for complex PDFs and documents
- High-performance vector search and similarity matching with Datasets.
- Enterprise-grade infrastructure with 99.9% uptime SLA
Visualization & Analytics
Nomic Atlas
Analyze Massive Unstructured Datasets
The Nomic Atlas enables developers and domain experts to explore, analyze and understand large datasets of text, files and embeddings.
- Explore and search over 10M+ data points with rich, explainable visualization
- Interactive maps for understanding data relationships and patterns
- Unlock a new world of collaboration for technical and non-technical teams
- Seamless integration with your existing data pipelines
- Secure and ready-to-deploy
Open Source AI
Free & Open Source AI that Understands Your Complex Documents
Run AI models locally on any machine. No GPU required, no internet needed, completely free.
Why GPT4All?
- ✓Run Llama, Mistral, Nous-Hermes, and thousands more models
- ✓Works on any machine - no GPU or internet required
- ✓GPU acceleration for NVIDIA, AMD, Apple, and Intel
- ✓100% free and open source - no subscriptions or usage limits
- ✓Customize with retrieval augmented generation (RAG)
Trusted by
"The Nomic Platform empowers our 7,500 engineers to build custom AI solutions that understand our data."
customer story
Aurecon leverages the Nomic platform to build custom AI agents and solutions across our global engineering consultancy. The platform enables our teams to create specialized AI applications for data exploration, automated workflows, and intelligent decision-making systems that serve our diverse project needs.
Dave Mackenzie
Managing Principal Digital
Read Case StudyManaging Principal Digital
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"A new flow state of data development"
use case
At SmarterX we connect retailers, brands, and consumers to better product, chemical, and health data—empowering intelligent and sustainable decision making for everyone.
We use Atlas to visualize and map consumer chemical products. Based on what we see, we make tweaks to our classification methodology which improves the speed and decisiveness of our algorithms. Atlas also helps us communicate to customers what AI does for product classification. When they see THEIR products on the map they learn about their own catalog and gain confidence and excitement in our approach.
Atlas has enabled an entirely new flow state of data development and we were able to get started overnight! The best part of using Atlas is that we can find something new within 5 seconds of opening a map AND get lost exploring the data for hours.
We use Atlas to visualize and map consumer chemical products. Based on what we see, we make tweaks to our classification methodology which improves the speed and decisiveness of our algorithms. Atlas also helps us communicate to customers what AI does for product classification. When they see THEIR products on the map they learn about their own catalog and gain confidence and excitement in our approach.
Atlas has enabled an entirely new flow state of data development and we were able to get started overnight! The best part of using Atlas is that we can find something new within 5 seconds of opening a map AND get lost exploring the data for hours.
Charlie Vallely
Chief Executive Officer
Chief Executive Officer
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"Atlas is T-SNE on steroids"
Laurens van der Maaten
First Author of T-SNE
First Author of T-SNE
Enhancing model quality
use case
At Hugging Face, we want to bring as much transparency to our training data as possible. Exploring data at scale is a huge challenge and we spend a ton of time on data filtering and quality.
Using Atlas, we found several data and model errors that we didn't previously know about. The visualization made it easy to uncover where these errors existed. After addressing these errors we improved our performance metrics by a ton. We plan to use Atlas much earlier in the process during our next engineering cycle.
Learn MoreUsing Atlas, we found several data and model errors that we didn't previously know about. The visualization made it easy to uncover where these errors existed. After addressing these errors we improved our performance metrics by a ton. We plan to use Atlas much earlier in the process during our next engineering cycle.
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Victor Sanh Lead ML Scientist
Explore Nomic in the wild
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