The knowledge problem nobody measures

Think about what happens when a new employee joins your organisation. They spend their first few weeks asking colleagues where things live, searching through SharePoint folders that haven't been organised since 2019, sifting through Slack threads that go nowhere, and sending emails to find out who owns what.

That onboarding frustration is just the visible version of a problem that affects every employee, every day, for the life of the business.

The average knowledge worker spends close to two hours every day searching for information. Across a team of 100 people, that's the equivalent of 25 full-time employees doing nothing but looking for things. Documents sit in Google Drive. Decisions live in email threads. Policies are buried in Confluence. Customer context is in the CRM. Expertise exists in people's heads and never gets written down. The institutional knowledge your organisation has built over years is everywhere — and practically inaccessible when someone actually needs it.

Traditional search doesn't solve this. Typing a keyword into SharePoint and getting a list of documents from 2017 isn't helpful when someone needs a direct answer. The tools organisations use to store knowledge are not the same as tools that help people use it.

That gap is where enterprise AI search comes in — and it's why some of the world's leading organisations are rethinking how their people access information at work.

What enterprise AI search actually means

It's worth being specific here, because "AI search" is one of those phrases that's starting to mean everything and nothing simultaneously.

Enterprise AI search isn't a better version of Ctrl+F. It's a fundamentally different approach to how organisational knowledge gets surfaced and used.

Rather than matching keywords against document titles, modern AI search understands the intent behind a question, the context of who's asking it, and the relationships between different pieces of information across your entire tech stack. It doesn't return a list of documents that might contain the answer — it gives you the answer, sourced from your own company's data, with references so you can verify it.

Ask it who handled the last renewal for a particular client and it knows. Ask it what the company's position is on a specific compliance question and it finds the policy, summarises it, and tells you where it lives. Ask it what your engineering team decided about a particular architecture question last quarter and it surfaces the relevant conversation, decision, and outcome. The information was always there. The difference is that it's now findable.

Why this is a bigger business problem than it looks

The knowledge access gap has a compounding effect on organisations that most leadership teams don't fully account for.

When information is hard to find, people make decisions with incomplete context. They duplicate work that's already been done because they can't locate it. They ask the same questions that have already been answered. Senior people become bottlenecks because junior team members can't self-serve the information they need. Onboarding takes longer than it should. Handovers lose context. Projects restart from scratch instead of building on what exists.

None of these inefficiencies appear as line items in a budget. They're invisible costs, spread across hundreds of small moments of friction every day. But at scale, the impact on productivity, decision quality, and organisational agility is significant. Forrester's analysis of enterprise AI search platforms found that the productivity gains from properly implemented solutions are measurable and consistent — not marginal improvements but hours recovered per employee per week.

For organisations competing in fast-moving markets, the ability to access institutional knowledge quickly isn't a nice-to-have. It's a competitive differentiator.

How leading organisations are using AI search today

The most sophisticated use cases go well beyond basic information retrieval. Organisations that have fully adopted enterprise AI search are using it in several ways that are worth understanding before evaluating platforms.

Sales teams are using it to pull full client context before calls — deal history, past communications, support tickets, renewal dates, and competitive intelligence — in seconds, without switching between five different systems. What used to take 20 minutes of preparation happens in under two.

HR and people teams are using it to give employees instant, accurate answers to policy questions — leave entitlements, benefits, processes, compliance requirements — without those questions landing in someone's inbox. The AI knows your employee handbook, your HR policies, and your intranet content, and answers naturally.

Engineering and product teams are using it to search across code repositories, technical documentation, past architecture decisions, and incident reports simultaneously. Finding out why a particular decision was made 18 months ago, or who has context on a specific system, takes seconds rather than a Slack broadcast hoping the right person sees it.

New starters are using it to onboard themselves. Rather than relying on a buddy or a structured onboarding programme to answer every question, they can ask the platform directly and get answers drawn from the organisation's actual knowledge base — policies, processes, people, history.

Leadership teams are using it to surface patterns and insights across customer conversations, support data, and internal documentation that would otherwise require a data analyst to compile. Business intelligence that used to take days to produce is increasingly available on demand.

Where Glean fits in

Glean is the platform that's emerged as the clear leader in this space, and the reason comes down to how it was built.

Founded by former Google search engineers, Glean was designed from day one to solve the enterprise knowledge problem properly — not as a feature added to an existing product, but as a purpose-built platform dedicated entirely to making organisational knowledge accessible.

At its core, Glean connects to over 100 enterprise applications — Google Workspace, Microsoft 365, Slack, Salesforce, ServiceNow, SharePoint, Confluence, GitHub, Jira, Workday, and more — and indexes everything across them into a single, unified, permissions-aware knowledge layer. When an employee searches, they see results from across every connected tool, in real time, filtered to show only what they have permission to access. No data bleeds between teams. No sensitive documents surface to people who shouldn't see them. The security model isn't bolted on — it's fundamental to how the platform works.

What makes Glean genuinely different from other solutions is what it builds on top of that connected data layer. The Enterprise Graph maps the relationships between people, content, and activity across your organisation — who works on what, who knows what, how information flows — so results aren't just relevant to the query, they're relevant to the person asking it. A search about a client returns different, more contextually appropriate results for the account manager than it does for someone in finance, because Glean understands how each person relates to that client.

The AI Assistant goes further still. Rather than searching and returning documents, it answers questions. It summarises complex content, drafts responses using your organisation's knowledge as context, and helps employees move from question to action without context switching. Glean describes it as giving every employee an expert who knows the entire business — and that's an accurate description of the experience at organisations that have fully deployed it.

In 2025, Glean expanded into AI Agents — automated workflows that can take action across connected systems, not just surface information. Agents can qualify incoming requests, update records, draft responses, route tasks, and complete multi-step processes using the same enterprise context that powers search. The platform now processes over 100 million agent actions per year, and the organisations using them are reclaiming significant operational capacity.

The growth trajectory reflects the demand. Glean crossed $200 million in annual recurring revenue in late 2025 — doubling from $100 million in under nine months — making it one of the fastest-growing pure-play enterprise software companies in recent memory. That growth isn't happening because of marketing. It's happening because organisations that deploy Glean see results they can measure.

What a Glean implementation actually involves

This is where most evaluation processes stall. Organisations can see the value of enterprise AI search clearly, but the question of what implementation looks like — how long it takes, what it requires, how it fits into existing systems — is often where the conversation slows down.

The good news is that Glean is designed for deployment velocity. Connecting your core applications, configuring the knowledge model, and getting the platform in front of users is not a six-month project. Organisations have reported going from contract to fully operational in under three weeks for standard configurations. That speed is possible because Glean's connector library handles the technical integration work, and the platform's permissions model mirrors whatever access controls you already have in place.

What actually determines implementation quality — and this is where experience matters — is the work that happens around the technical setup. Understanding which data sources matter most and in what order to connect them. Configuring the knowledge model to reflect how your organisation actually speaks and works. Defining the use cases that will drive adoption in the first 90 days. Training teams on how to get value from the assistant rather than treating it like a traditional search bar. Establishing governance frameworks so the platform scales cleanly as your team and your data grow.

These aren't technology problems. They're organisational and operational ones — and they're where an experienced implementation partner earns its place.

Glean's minimum deployment threshold is 70 licences, which means this is an investment designed for organisations that are serious about the problem. At that scale, the productivity and knowledge access gains are substantial — but so is the importance of getting the implementation right. A deployment that covers all the right applications, configured around your actual workflows, with clear adoption strategies for each team, delivers a fundamentally different outcome than one that's technically functional but operationally shallow.

How to know if your organisation is ready

The right organisations for Glean share a few common characteristics.

They're operating across multiple tools and data sources, and information silos are a felt pain — not a theoretical concern. They have teams where knowledge access directly affects decision quality, sales effectiveness, or customer experience. They're at a stage of growth where institutional knowledge is becoming harder to manage manually. And they have leadership that understands the difference between adding another tool to the stack and building proper knowledge infrastructure.

If your team regularly asks questions that should be answerable from internal data but aren't — if onboarding takes too long, if senior people are bottlenecks for information, if decisions get made with incomplete context — Glean addresses those problems at the root.

The organisations that get the most value aren't necessarily the largest ones. They're the ones where knowledge flows directly and visibly into business outcomes — where finding the right answer faster translates into a shorter sales cycle, a faster hire, a better client interaction, or a decision that would otherwise have taken a week.

Our role as a Glean implementation partner

MyScale Solutions is a Glean partner with experience deploying enterprise AI search for organisations across Australia and beyond. We handle the full implementation — connector configuration, knowledge model setup, permissions architecture, team training, and adoption strategy — so your organisation gets to value quickly and sustainably.

We're not a reseller who hands you a licence and points you at documentation. We work through what your organisation actually needs, configure Glean around your real workflows and data landscape, and stay involved through adoption to make sure the platform delivers what it's supposed to.

If you're evaluating enterprise AI search and want to understand what a Glean deployment would look like for your organisation specifically — timelines, costs, integration requirements, and what teams would see immediate benefit — we're happy to walk you through it with no obligation.

[Book a Glean Discovery Call] [Talk to Us About Enterprise AI Search]

MyScale Solutions is a Glean Partner and HubSpot Platinum Partner based in Sydney, Australia. We implement enterprise AI and CRM platforms for mid-market and enterprise organisations across Australia, New Zealand, and the US.

Frequently asked questions

What is Glean and what does it do? Glean is an enterprise AI platform that connects to over 100 workplace applications and makes all of your organisation's knowledge searchable and actionable from one place. It combines AI-powered search, a conversational assistant, and AI agents to help employees find information, answer questions, and automate work using your company's own data.

How is Glean different from a regular search tool? Traditional search tools match keywords against document titles and return a list of links. Glean understands the intent behind a question, the context of who's asking it, and the relationships between information across all your connected applications. It answers questions directly, summarises content, and surfaces the most relevant results to each individual based on their role, team, and history.

How long does a Glean implementation take? Standard implementations can be operational in as little as three weeks. The technical setup — connecting applications, configuring permissions — moves quickly because of Glean's connector library. A thorough implementation that includes knowledge model configuration, adoption strategy, and team training typically takes four to eight weeks for a complete deployment.

What is the minimum number of licences for Glean? Glean is designed for enterprise organisations and starts at a minimum of 70 licences. This reflects the platform's positioning as knowledge infrastructure for teams where the value of connected, searchable knowledge compounds with the number of people using it.

Is enterprise data secure inside Glean? Yes. Glean runs in a single-tenant cloud environment and enforces the same permissions that exist in your connected applications. Employees only see information they already have access to. The platform includes Glean Protect — an enterprise-grade security and governance layer — and is built to meet the requirements of regulated industries.

Do you need a technical team to deploy Glean? Not necessarily. Glean is designed for deployment without heavy engineering resources on the customer side. Working with an implementation partner handles the configuration, integration, and adoption work, meaning your internal IT team's involvement can be scoped appropriately rather than consuming significant bandwidth.