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WizWiz introduces a novel strategy for cloud security by identifying critical risks and potential entry points across various multi-cloud settings. It enables the discovery of all lateral movement threats, including private keys that can access both production and development areas. Vulnerabilities and unpatched software can be scanned within your workloads for proactive security measures. Additionally, it provides a thorough inventory of all services and software operating within your cloud ecosystems, detailing their versions and packages. The platform allows you to cross-check all keys associated with your workloads against their permissions in the cloud environment. Through an exhaustive evaluation of your cloud network, even those obscured by multiple hops, you can identify which resources are exposed to the internet. Furthermore, it enables you to benchmark your configurations against industry standards and best practices for cloud infrastructure, Kubernetes, and virtual machine operating systems, ensuring a comprehensive security posture. Ultimately, this thorough analysis makes it easier to maintain robust security and compliance across all your cloud deployments.
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What is SciPhi?
Establish your RAG system with a straightforward methodology that surpasses conventional options like LangChain, granting you the ability to choose from a vast selection of hosted and remote services for vector databases, datasets, large language models (LLMs), and application integrations. Utilize SciPhi to add version control to your system using Git, enabling deployment from virtually any location. The SciPhi platform supports the internal management and deployment of a semantic search engine that integrates more than 1 billion embedded passages. The dedicated SciPhi team is available to assist you in embedding and indexing your initial dataset within a vector database, ensuring a solid foundation for your project. Once this is accomplished, your vector database will effortlessly connect to your SciPhi workspace along with your preferred LLM provider, guaranteeing a streamlined operational process. This all-encompassing setup not only boosts performance but also offers significant flexibility in managing complex data queries, making it an ideal solution for intricate analytical needs. By adopting this approach, you can enhance both the efficiency and responsiveness of your data-driven applications.
What is PostgresML?
PostgresML is an all-encompassing platform embedded within a PostgreSQL extension, enabling users to create models that are not only more efficient and rapid but also scalable within their database setting. Users have the opportunity to explore the SDK and experiment with open-source models that are hosted within the database. This platform streamlines the entire workflow, from generating embeddings to indexing and querying, making it easier to build effective knowledge-based chatbots. Leveraging a variety of natural language processing and machine learning methods, such as vector search and custom embeddings, users can significantly improve their search functionalities. Moreover, it equips businesses to analyze their historical data via time series forecasting, revealing essential insights that can drive strategy. Users can effectively develop statistical and predictive models while taking advantage of SQL and various regression techniques. The integration of machine learning within the database environment facilitates faster result retrieval alongside enhanced fraud detection capabilities. By simplifying the challenges associated with data management throughout the machine learning and AI lifecycle, PostgresML allows users to run machine learning and large language models directly on a PostgreSQL database, establishing itself as a powerful asset for data-informed decision-making. This innovative methodology ultimately optimizes processes and encourages a more effective deployment of data resources. In this way, PostgresML not only enhances efficiency but also empowers organizations to fully capitalize on their data assets.
Integrations Supported
Apache Superset
BERT
Codestral
DBeaver
Elixir
Jupyter Notebook
Llama 3.2
Lua
Mistral 7B
Mistral Large
Integrations Supported
Apache Superset
BERT
Codestral
DBeaver
Elixir
Jupyter Notebook
Llama 3.2
Lua
Mistral 7B
Mistral Large
API Availability
Has API
API Availability
Has API
Pricing Information
$249 per month
Free Trial Offered?
Free Version
Pricing Information
$.60 per hour
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
SciPhi
Company Website
www.sciphi.ai/
Company Facts
Organization Name
PostgresML
Company Website
postgresml.org