Enterprise Knowledge Search
IBM’s CIO organization needed a digital assistant that could help employees complete routine work faster and search across enterprise knowledge without exposing confidential or sensitive information.
Reported impact
AskIBM put a governed internal assistant in front of IBM employees worldwide, reducing friction in everyday knowledge work and accelerating the company’s own AI adoption journey.
IBM’s CIO organization built AskIBM in 60 days using IBM watsonx.ai and IBM Granite foundation models as a retrieval-augmented employee assistant. The platform was designed to automate everyday knowledge-work tasks such as drafting email, translating documents, summarizing long files and searching for information. Strategic internal IBM content—while excluding confidential, sensitive personal and customer information—was ingested into the system so the assistant could ground responses in approved enterprise knowledge. The initial alpha release started with about 5,000 multilingual documents and expanded to more than 30,000 by July 2024. AskIBM applies RAG to retrieve relevant content and generate tailored answers, while IBM’s legal, privacy, cybersecurity and AI-ethics reviews served as production guardrails. The result is a global internal assistant that puts enterprise knowledge and generative AI directly into employee workflows.
Approved internal IBM documents are ingested into AskIBM’s RAG pipeline, retrieved based on employee prompts and used by watsonx.ai and Granite models to generate task-focused responses for knowledge workers around the company.
The AskIBM foundation was built in 60 days with watsonx.ai.
The AskIBM foundation was built with watsonx.ai™ and IBM Granite™-class large language models (LLMs).
The Retrieval-Augmented Generation (RAG) technique enables AskIBM to use the ingested contents to deliver tailored and appropriate responses to IBM employees.
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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