The recently improved coherence, fluency, and capabilities of generative AI have made it the most transformative workplace tool in recent history. This is particularly true for knowledge workers in enterprise environments, where every department across the organization can utilize it for a variety of both technical and non-technical tasks. It’ll enable workers to accelerate and uplevel the work they deliver, focus on more meaningful application of their efforts, and cut costs and save time by eliminating repetitive, rote work.
However, it isn’t exactly smooth sailing yet – while generative AI and large language models are undoubtedly powerful force-multipliers for knowledge-based workforces, they require strong grounding in reliable and trustworthy knowledge in order to be dependable.
Why trusted knowledge is essential
Herein lies the keystone of making generative AI truly usable in enterprise environments. Without a stable foundation of enterprise knowledge to fuel it, generative AI tends to return confidently incorrect answers – which end up being extremely difficult to verify due to the coherency of the resulting text.
Think of a general-purpose generative AI model like a confident intern on their first day at a new company. They can give intelligent, well-spoken answers, but lack the company-specific knowledge to provide nuanced ones for unique circumstances. Knowledge workers who need the right answer the first time to move quickly and confidently can’t trust systems like that in complex enterprise environments.
To build trust, generative AI models need to provide answers that are rooted in trusted enterprise knowledge, allow users to understand where those answers come from, and adhere to data governance policies. This is why Glean is building generative AI features for our customers that are backed by their company-specific trusted knowledge models. By grounding generative AI in the right search foundation and your company's enterprise information, it becomes capable of delivering real answers you know are dependable.
To achieve that, Glean creates an enterprise knowledge graph for each of our customers that map data such as their:
- Content – Individual assets, documents, messages, tickets, entities, etc.
- People – Identities and roles, teams, departments, groups, etc.
- Activity – Content creation/creators, editing history, comments, searches, clicks, etc.
After mapping all of that information, Glean understands the intricate relationships between every element of these three pillars, enabling our search to provide results with exceptional relevance and reliability. It’s why we’re at the spearhead of fine-tuning and training models in-domain to power the progress of LLMs and AI in the enterprise through trusted knowledge models.
Driving generative AI forward with Google Cloud
We’re at the cusp of something exceptional, and that’s why we’re thrilled to announce a new stage of our partnership with Google Cloud. Their upcoming LLM and AI tools will help us deliver dependable generative experiences to ever more enterprise customers. Combined with the trusted knowledge model that our platform provides, this latest opportunity will help us deliver the definite generative AI solution capable of transforming the way knowledge workers around the world do their best work.
“Glean’s platform, running on Google Cloud, enables more helpful, trusted generative AI experiences for enterprises,” said Manvinder Singh, Managing Director, Partnerships at Google Cloud. “We’re delighted to support Glean with Google Cloud infrastructure, AI, and LLM services, and ultimately help businesses improve knowledge and understanding of their data through generative AI.”