Best Data Management Software for Llama 3
View:
Compare the Top Data Management Software that integrates with Llama 3 as of November 2025
Sort By:
This a list of Data Management software that integrates with Llama 3. Use the filters on the left to add additional filters for products that have integrations with Llama 3. View the products that work with Llama 3 in the table below.
What is Data Management Software for Llama 3?
Data management software systems are software platforms that help organize, store and analyze information. They provide a secure platform for data sharing and analysis with features such as reporting, automation, visualizations, and collaboration. Data management software can be customized to fit the needs of any organization by providing numerous user options to easily access or modify data. These systems enable organizations to keep track of their data more efficiently while reducing the risk of data loss or breaches for improved business security. Compare and read user reviews of the best Data Management software for Llama 3 currently available using the table below. This list is updated regularly.
-
1
LM-Kit.NET
LM-Kit
LM-Kit.NET is a cutting-edge, high-level inference SDK designed specifically to bring the advanced capabilities of Large Language Models (LLM) into the C# ecosystem. Tailored for developers working within .NET, LM-Kit.NET provides a comprehensive suite of powerful Generative AI tools, making it easier than ever to integrate AI-driven functionality into your applications. The SDK is versatile, offering specialized AI features that cater to a variety of industries. These include text completion, Natural Language Processing (NLP), content retrieval, text summarization, text enhancement, language translation, and much more. Whether you are looking to enhance user interaction, automate content creation, or build intelligent data retrieval systems, LM-Kit.NET offers the flexibility and performance needed to accelerate your project.Starting Price: Free (Community) or $1000/year -
2
Firecrawl
Firecrawl
Crawl and convert any website into clean markdown or structured data, it's also open source. We crawl all accessible subpages and give you a clean markdown for each, no sitemap is required. Enhance your applications with top-tier web scraping and crawling capabilities. Extract markdown or structured data from websites quickly and efficiently. Navigate and retrieve data from all accessible subpages, even without a sitemap. Already fully integrated with the greatest existing tools and workflows. Kick off your journey for free and scale seamlessly as your project expands. Developed transparently and collaboratively. Join our community of contributors. Firecrawl crawls all accessible subpages, even without a sitemap. Firecrawl gathers data even if a website uses JavaScript to render content. Firecrawl returns clean, well-formatted markdown, ready for use in LLM applications. Firecrawl orchestrates the crawling process in parallel for the fastest results.Starting Price: $16 per month -
3
Coginiti
Coginiti
Coginiti, the AI-enabled enterprise data workspace, empowers everyone to get consistent answers fast to any business question. Accelerating the analytic development lifecycle from development to certification, Coginiti makes it easy for you to search and find approved metrics for your use case. Coginiti integrates all the functionality you need to build, approve, version, and curate analytics across all business domains for reuse, all while adhering to your data governance policy and standards. Data and analytic teams in the insurance, financial services, healthcare, and retail/consumer package goods industries trust Coginiti’s collaborative data workspace to deliver value to their customers.Starting Price: $189/user/year -
4
Bakery
Bakery
Easily fine-tune & monetize your AI models with one click. For AI startups, ML engineers, and researchers. Bakery is a platform that enables AI startups, machine learning engineers, and researchers to fine-tune and monetize AI models with ease. Users can create or upload datasets, adjust model settings, and publish their models on the marketplace. The platform supports various model types and provides access to community-driven datasets for project development. Bakery's fine-tuning process is streamlined, allowing users to build, test, and deploy models efficiently. The platform integrates with tools like Hugging Face and supports decentralized storage solutions, ensuring flexibility and scalability for diverse AI projects. The bakery empowers contributors to collaboratively build AI models without exposing model parameters or data to one another. It ensures proper attribution and fair revenue distribution to all contributors.Starting Price: Free -
5
SQL
SQL
SQL is a domain-specific programming language used for accessing, managing, and manipulating relational databases and relational database management systems.Starting Price: Free -
6
DataChain
iterative.ai
DataChain connects unstructured data in cloud storage with AI models and APIs, enabling instant data insights by leveraging foundational models and API calls to quickly understand your unstructured files in storage. Its Pythonic stack accelerates development tenfold by switching to Python-based data wrangling without SQL data islands. DataChain ensures dataset versioning, guaranteeing traceability and full reproducibility for every dataset to streamline team collaboration and ensure data integrity. It allows you to analyze your data where it lives, keeping raw data in storage (S3, GCP, Azure, or local) while storing metadata in inefficient data warehouses. DataChain offers tools and integrations that are cloud-agnostic for both storage and computing. With DataChain, you can query your unstructured multi-modal data, apply intelligent AI filters to curate data for training and snapshot your unstructured data, the code for data selection, and any stored or computed metadata.Starting Price: Free -
7
Deasie
Deasie
You can't build good models with bad data. More than 80% of today’s data is unstructured (e.g., documents, reports, text, images). For language models, it is critical to understand what parts of this data are relevant, outdated, inconsistent, and safe to use. Failure to do so leads to unsafe and unreliable adoption of AI.
- Previous
- You're on page 1
- Next
