Enhance the value of your team and go beyond the basics with your in-house GenAI. Deliver an impactful user experience that will level up your employees' capabilities.
Are you unsure of what employee needs your GenAI tools should address?
Do you lack the internal knowledge to accomplish your GenAI goals?
Have you been challenged to get your GenAI project done in an aggressive timeline?
Do you have budget constraints that you think prevent you from delivering on your GenAI needs?
Go further on your Generative AI journey and partner with Stride to upgrade the user experience you deliver to your employees. According to MIT's Sloan School of Management, "Generative AI can improve a highly skilled worker’s performance by as much as 40% compared with workers who don’t use it."
In order to realize those benefits, employees need to use Generative AI tools. If you're struggling with internal adoption because employees don't know how to get started or are confused by the UX, we can help.
Together, we will explore your employees' problems and workflows that can be addressed by GenAI.
Together, we will build a full-stack end-to-end LLM product in as little as 6 weeks, using innovative UX to go beyond boilerplate chatbot interactions.
Together, we will provide your team with ongoing training and insights to scale and grow your LLM product.
For Nick Peddy, CLEAR's CTO, the focus was on the pivotal role of data security in LLM integration. Stride was instrumental in this process, with our team, particularly Rob and Dan, emphasizing the importance of aligning LLM capabilities with CLEAR's specific needs, rather than just implementing technology.
This approach led to the creation of Athena, CLEAR's tailor-made LLM, which has not only strengthened data security but also become a celebrated tool within the company, showcasing Stride's commitment to facilitating responsible and impactful technological innovation.
We can work with an existing LLM and extend it to meet your business needs, which could include data integrations, training, coaching, prompt engineering, UI/UX extensions, etc. You may also want a separate environment for certain sensitive use cases or with data which is not easy to integrate with a cloud LLM like OpenAI, and Stride can quickly and inexpensively build that kind of environment.
A custom secure Large Language Model (LLM) is tailored to a company's specific requirements, ensuring data privacy and security by training on sensitive information without it leaving the company's secure environment. It provides industry-specific knowledge, integrates seamlessly with internal systems, and complies with regulatory standards like GDPR or HIPAA. Such customization offers a competitive edge, allows for full control over the model, reduces bias in outputs, and protects intellectual property.
A: The LLM Jumpstart teams are composed of 4 Striders. Typically, these engagements consist of 2 software developers, 1 product manager and 1 designer.