LLMWare

Deploy AI privately and securely with small language models

5.0•3 reviews•

617 followers

Deploy AI privately and securely with small language models

5.0•3 reviews•

617 followers

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LLMs

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AI Infrastructure Tools

Building pioneering AI tools for financial, legal, compliance and regulatory intensive industries in private cloud or on prem with Small Language Models

Free

Launch tags:Open Source•Artificial Intelligence•GitHub

Launch Team / Built With

Viktor.comAn AI coworker that actually does the work

Promoted

Started using it and already loving how easy it made deployment easy.

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2yr ago

APIPark

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.

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2yr ago

LLMWare

Maker

@an_zuo Hi Thank you for your question - I understand that I need to better clarify. It is a platform for quickly building AI applications but we also have models in Hugging Face that can be used to build such applications...

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2yr ago

Telebugs

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!

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2yr ago

LLMWare

Maker

@kyrylosilin Thank you so much for the excellent questions! Small Language Models are truly getting better and better and I believe that they may be better or at par accuracy and capability for specific tasks (exception being multi-modal tasks). Enterprises have a lot of smaller workflows and repetitive tasks they would like to have automated, but they are very specific to them (or their department). Smaller models allow for much more focused and targeted approach to automate workflows because: 1) they can be specifically fine-tuned for an extremely low cost (GPU cost of training can be as low as $10 for a small model) for that particular function or domain, and 2) the small models can be stacked (one function after another) so that they can be used with great specificity. We have many examples in our YT channel where we show stacking these small models together as well as over 100+ examples in our repo. These models and workflow can be deployed on prem or on device so there is much less exposure during data transfer. In addition, our library exposes a confidence score that maps responses to the actual source document so that users can check for hallucination. Our commercial product has many additional security and safety features as well. Here is an article in Venture Beat, FYI, about SLMs in case you're interested: https://venturebeat.com/ai/why-s... I hope you give our repo a try - thank you!

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2yr ago

Autonomous

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!

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2yr ago

LLMWare

Maker

@nancy_autonomous The pain point of financial services or highly regulated industries to begin is around data privacy and security. These types of industries are subject to more scrutiny and stricter privacy and compliance regulations. We designed a solution that for complete and secure end-to-end control by the enterprise for local or private deployment. For example, we have our own proprietary parsers (for enterprise grade document ingestion) all the way to our own fine-tuned specialized small language models (as well as specialized models for contract review, insurance industry, loan documents and SEC documents) so that enterprises can have complete control and visibility into every step of user AI inferencing and for tracking data lineage with models that can all run locally or with low resources. This is important for compliance & audit requirements as well as AI explainability for regulated industries. I hope this helps!

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2yr ago

@namee_oberst Congratulations on your launch! Just intrigued, how simple can teams adjust AI technologies to meet varied regulatory requirements? I'm excited to see what effect this will have on the industry!

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2yr ago

Diaflow

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!

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2yr ago

LLMWare

Maker

@vietpham Thank you so much for your kind feedback!

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2yr ago

Elisi : AI-powered Goal Management App

LLMWare.ai is a timely solution for enterprises prioritizing data security without sacrificing the benefits of AI. The emphasis on small language models that run locally really addresses the common concerns around data privacy and breaches. I love the comprehensive open-source repository and the abundance of examples—it makes integrating AI into existing workflows much more accessible. Getting recognized by GitHub is a fantastic achievement and speaks to the project’s quality. Excited to see how the commercial product simplifies deployment on standard enterprise hardware. Kudos to Namee and the team for tackling such a crucial aspect of AI in the workplace!

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2yr ago

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5.0

Based on 3 reviews

Review LLMWare?

LLMWare is praised for its ease of setup and use, particularly for industries like finance and legal that require secure and private AI deployment. Users appreciate its open-source nature and the ability to deploy AI apps without overwhelming resources. The small language model approach is highlighted as effective for companies handling sensitive data. The option for private cloud and on-prem deployment is seen as a significant advantage. Overall, LLMWare is recognized for addressing unique industry needs efficiently.

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