Pioneering AI development tools and small language models built for financial services, compliance and other regulatory intensive industries in private cloud or local deployment. Innovative end to end solution for RAG and AI Agent Workflow automation framework
Hello Product Hunters! My name is Namee, co-founder of LLMWare.ai, and I would like to share my open-source repo that will help you build really useful AI apps for the enterprise.
I used to work as a Corporate Attorney at BigLaw working crazy hours doing very mundane and sometimes mind-numbingly repetitive tasks. I wanted to build AI that everyone can use to help solve the everyday soul-crushingly boring tasks like information retrieval, contract reviews, SQL queries, report generation and much more! (These are just few examples here and I am sure you can think of many others. 😅)
Enter Small Language Models🤖
To help people at their corporate jobs, however, I saw a big problem with using external models like ChatGPT to access sensitive data and information. Knowing the data privacy and security concerns of my enterprise clients from my legal days, I knew that they would have a big problem with sending out data this way. After all, enterprises live in fear of data breaches and data copies – this is one of the biggest security risks they have.
💡That realization led me to one simple conclusion. AI has to come directly and privately to laptops where most of us access our work.
‼️Of course the models had to be small enough to run locally. And we needed to provide easy access and easy deployment (either private cloud, on prem or on device) so that no data needs to leave the enterprise security zone. That was my A-ha moment that led me to focus on small language models about 18 months ago.
What is LLMWare?
From the beginning, LLMWare has been exclusively focused on using, fine-tuning, and deploying small language models (SLMs) to enable easy to use and easy to deploy AI for the enterprise. We are pioneers in this space and was selected by Github earlier this year as a leading AI project in open source. 🏆
Who is it Perfect for?
Enterprise developers looking to create lightweight apps for local deployment use cases to enhance productivity and to automate workflow.
How to Get Started
We have over 100+ examples in our open source repo that help you get started plus over 75+ models in Hugging Face. We have published Fast Start to RAG and Fast Start to Agents video series on YouTube along with many other videos that show you step-by-step how to get started with using SLMs. https://www.youtube.com/@llmware...
Sign Up for a Beta Test
In addition to LLMWare's open source library, we are developing our first commercial product that makes it easy to use and to deploy state of the art models directly on laptops, especially Intel-based hardware that powers most enterprise laptops (point and click deployment). If this sounds interesting to you, please contact me directly to sign up to be a beta tester!
A Big THANKS
Thank you Product Hunters for your support! And last but not least, a MASSIVE thanks to @chrismessina, our Hunter Extraordinaire, who believed in the mission behind LLMWare and helped us launch here. 🙏🌟
I really appreciate the easy integration with various vector databases and the industry specific models available. It’s so convenient!
This is exactly what us enterprises need to manage their AI models effectively in regulated environments!
This is a fantastic tool for developers in finance and compliance. Plus, being open source is a big plus!
Small Language Models are super compelling — both because they can run more easily behind the firewall but also because they can run locally on-device.
I'm glad @namee_oberst reached out to me to help her with this launch both because this approach to AI deserves more attention and because she's building a very compelling platform with LLMWare.
LLMWare is great we use their Slim extraction tool and it's been a game changer!!
What are the key features of LLMWare.ai that different it from other AI platforms on the market?
Love the focus on privacy and local deployment—perfect for today’s data-sensitive enterprises.
Much needed! compute is usually the major issue that restrict smaller enterprises for AI.
Congrats to the LLMWare team on the launch! A groundbreaking solution for AI development in highly regulated industries like finance and compliance. It's impressive how the platform enables private cloud or local deployment while automating workflows end-to-end!
The idea of using smaller models for industries like finance makes a lot of sense. It's compact, efficient, and doesn't compromise on privacy.
Hey Namee,
I'm curious about the performance trade-offs. How do these smaller models compare to larger ones in terms of accuracy and capability for specific enterprise tasks?
For companies concerned about data security, what kind of encryption or safeguards does LLMWare implement?
Congrats on the launch!
Wow, Congrats launch on the product Hunt. Do you have a guide for beginner developers?
That sounds like a fascinating product. Here are some questions I have to help me better understand:
What specific pain points in the financial services and regulatory industries do your AI development tools and language models aim to address? For example, are they related to compliance, risk management, or customer onboarding?
You mention a private cloud or local deployment. Can you elaborate on the benefits of this approach versus a public cloud or hybrid model, especially in terms of data security and sovereignty?
Thank you!
So do you want to position it as a model that can be deployed locally or a platform for quickly building AI applications? These are two different directions in themselves. Perhaps focusing more will make it easier for users to understand your positioning and help you do better.
