Implementing Generative AI for the Enterprise

During the webinar, Generative AI for Enterprise: How to Tame a Stochastic Parrot, Squirro provided a solution to the limitations of Generative AI, such as ChatGPT, in the enterprise context by combining Large Language Models (LLMs) with Composite AI and Insight Engine technology.

Kick-Start the Generative AI Implementation at Your Company

Starting with a proof-of-concept (PoC) provides a fast and cost-effective way to test the technology based on a specific business use case and to pave the way to a successful pilot implementation and a roll-out.

Examples of potential PoCs:

  • Knowledge Management: Evidence-based enterprise search
  • Service Management: Generative AI application (as question answering or summarization) in a Service / Call Center, a customer self-service application, or a public website
  • Risk Compliance & Audit Management: summarization or Question Answering based on regulatory requirements

Get in touch with our experts to discuss the potential PoCs at your company and your specific functional domain.

Schedule a Call

What to Expect

How Squirro overcomes the limitations that restrict the application of Generative AI in the enterprise environment:


  • Hallucinations make it hard to trust the Generative AI output
  • Public data from the internet as the only data source
  • A disregard for company’s internal privacy and security restrictions and Access Control Lists (ACLs)

Squirro Solutions

  • Evidence-based: counter hallucinations with transparency and explainability in the form of the source of information
  • Ingest and locally up-train with private and premium data sources to ensure you get the correct information when you need it
  • Enterprise-ready architecture: robust, secure, and respecting ACLs

How to Implement Generative AI?

Over the last decade, Squirro supported a number of leading companies in implementing Enterprise Search and Insight Platform solutions in a broad range of functional domains:

From PoC to Rollout

Based on this experience, a three-step approach is proven as the most efficient and successful approach:

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