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Fast-Track AI Innovation with deepset

Discover why deepset's AI platform is a scalable, accessible, and simple option for implementing applications with LLMs-and how it can benefit your product development lifecycle

By
The deepset Team
,
Published on
February 5, 2024
12
min read

TLDR

Key Metrics:

The range of options for building Generative AI-enabled applications is rapidly growing. It’s not just hard to know where to start, it’s positively overwhelming – for even the most seasoned AI teams.

The deepset AI Platform (formerly known as deepset Cloud) is designed for teams at organizations that have started to integrate LLMs into their products. With the right balance between a one-size-fits-all black box solution and an infinitely customizable toolchain, deepset fits seamlessly into any existing or new API-driven application architecture. It offers a clear path toward building an LLM-driven solution from pre-built components and best-in-class pipeline templates.

Here’s how deepset makes it easy for AI teams to integrate, deploy, manage and scale LLMs in their applications:

  1. Flexible, unified environment: deepset provides a cohesive development platform, integrating various LLM components into a single, streamlined environment, encouraging efficient and effective experimentation.
  2. Rapid prototyping: The platform enables swift experimentation and prototyping, allowing AI engineers to explore different LLM configurations and applications without the overhead of building individual components.
  3. Visibility and transparency: With built-in monitoring and analytics tools, managers and team leads can easily track development progress, aligning technical exploration with business objectives and building a trustworthy AI.
  4. Standardized yet customizable components: Mix and match standardized, expert-built components, while supporting the creation of custom elements to cater to the engineers’ desire to delve into the technology.
  5. Learning fast: deepset helps mitigate the steep learning curve of Gen AI, allowing AI engineers to understand the intricacies of LLMs while starting to implement practical applications in no time.

Fast-forward to a quick-win solution

One of the biggest barriers to LLM implementation for AI teams is the cost in time and engineering resources associated with leveraging LLMs in a full do-it-yourself (DIY) manner. Thanks to our years of experience and expertise in helping companies build products with LLMs, deepset can help you overcome these major obstacles. With our flexible pricing model and a professional AI services team, organizations can optimize the cost of starting and launching production-focused pilot applications.

Here are five key benefits of working with us and adding deepset to your Gen AI toolkit.

An infographic comparing two implementation strategies for Gen AI: full DIY (Do It Yourself) versus using build with 'deepset Cloud.' There are five columns titled PEOPLE, COMPLETE PILOT, PRODUCTION, INFRASTRUCTURE, and EFFICIENCY, each with two rows comparing the two approaches. For PEOPLE, DIY requires a 'Homegrown tech stack + components' and 8 FTEs (Full-Time Employees), while with deepset Cloud 2 FTEs are required. For COMPLETE PILOT, DIY takes '6 months to implement', whereas using deepset Cloud it takes '1 month to implement'. Under 'PRODUCTION', DIY lists '12+ months' for implementation time, whereas with deepset Cloud it usually takes 'weeks'. For INFRASTRUCTURE, DIY states 'Has to be built and orchestrated', while deepset Cloud offers 'Scalable & Reliable Infrastructure'. For EFFICIENCY, DIY states 'Diverse teams must self-organize and tackle steep learning curve', in contrast to deepset's 'End to End Lifecycle Support' with 'expert guidance from the deepset team'. The deepset Cloud benefits are highlighted in a blue background.

Helping AI teams succeed

deepset is streamlining the way AI teams build real-world applications with LLMs. It's 'compressing time' by offering an indispensable toolkit and infrastructure that mitigate the risks associated with designing and implementing an LLM-based application architecture. Aside from augmenting internal platforms and toolchains, it also brings useful templates and trusted reference implementations – all based on deepset's years of experience in implementing scalable solutions for enterprise customers.

Don't miss out on the opportunity to see deepset in action. Schedule a demo today to experience firsthand how it can accelerate your AI journey and drive your organization toward successful innovation.

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