Audience
Organizations looking for a solution to connect unstructured data to their GenAI applications
About Carbon
Instead of building expensive pipelines, automate with Carbon and only pay for monthly usage. Use less, spend less on our usage-based pricing model; use more, save more. Utilize our ready-made components directly for file upload, web scraping and 3rd party authentication. A rich library of smart APIs for AI-focused data import, built for developers. Create and retrieve chunks and embeddings from all data sources. Built-in enterprise-grade semantic and keyword search for your unstructured data. Carbon manages OAuth flows for 10+ sources, transforms source data into vector store-optimized documents, and handles data syncs automatically.
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Carbon
carbon.ai/
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Pinecone
Long-term memory for AI.
The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.
Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval.
Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results.
Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely.
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Context Data
Context Data is an enterprise data infrastructure built to accelerate the development of data pipelines for Generative AI applications. The platform automates the process of setting up internal data processing and transformation flows using an easy-to-use connectivity framework where developers and enterprises can quickly connect to all of their internal data sources, embedding models and vector database targets without having to set up expensive infrastructure or engineers. The platform also allows developers to schedule recurring data flows for refreshed and up-to-date data.
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Gantry
Get the full picture of your model's performance. Log inputs and outputs and seamlessly enrich them with metadata and user feedback.
Figure out how your model is really working, and where you can improve. Monitor for errors and discover underperforming cohorts and use cases.
The best models are built on user data. Programmatically gather unusual or underperforming examples to retrain your model.
Stop manually reviewing thousands of outputs when changing your prompt or model. Evaluate your LLM-powered apps programmatically.
Detect and fix degradations quickly. Monitor new deployments in real-time and seamlessly edit the version of your app your users interact with.
Connect your self-hosted or third-party model and your existing data sources.
Process enterprise-scale data with our serverless streaming dataflow engine.
Gantry is SOC-2 compliant and built with enterprise-grade authentication.
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Neum AI
No one wants their AI to respond with out-of-date information to a customer. Neum AI helps companies have accurate and up-to-date context in their AI applications. Use built-in connectors for data sources like Amazon S3 and Azure Blob Storage, vector stores like Pinecone and Weaviate to set up your data pipelines in minutes. Supercharge your data pipeline by transforming and embedding your data with built-in connectors for embedding models like OpenAI and Replicate, and serverless functions like Azure Functions and AWS Lambda. Leverage role-based access controls to make sure only the right people can access specific vectors. Bring your own embedding models, vector stores and sources. Ask us about how you can even run Neum AI in your own cloud.
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SaaS
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