FAQs

index is dedicated to transforming enterprise knowledge, enabling AI solutions to deliver accurate and auditable answers at scale. Our solutions clean, govern, and migrate knowledge, ensuring trustworthy AI by governing the knowledge it operates on and providing measurable ROI in weeks rather than years. We streamline the process of knowledge health check, issue remediation, and knowledge migration and orchestration, particularly for large customers with extensive knowledge bases.

Every day, people inside your organisation are trying to do the same simple thing: find the right answer quickly - during a client call, while resolving an incident, preparing a release, replying to a regulator, or writing a proposal.

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When that “hunt for knowledge” is short and lands on something correct and approved, work flows.

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When it isn’t, the cost doesn’t show up as “a knowledge problem.” It shows up as rework, delays, escalations, client frustration, and avoidable risk.

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Most companies try to solve this with better search or an AI assistant. That can improve retrieval speed, but it doesn’t fix the root cause: in many organisations the content itself is drifting - duplicates, contradictions, outdated guidance, missing owners, and review cycles that quietly break. So you can end up moving faster… toward the wrong thing.

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That’s why the damage often stays hidden until it suddenly isn’t:

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• A service desk agent under SLA pressure grabs the first plausible fix from past tickets. It looks right, but it’s the wrong variant or an outdated procedure, and the incident reopens or repeats.

• A critical query bounces between teams because the “owner” list hasn’t been maintained, so nobody can validate the answer quickly.

• A deployment slips because the “one document that matters” is buried, duplicated, or contradictory across repositories.

• A runbook is incomplete (or the critical step sits in a forgotten PDF), and a preventable client incident becomes a real one.

• And with AI in the mix, the stakes rise: AI can amplify whatever you give it. If internal knowledge is messy, AI can return confident answers that are incorrect, unapproved, or out of date - which is worse than “no answer,” because it looks authoritative.

index AI tackles this at the source.

We run a practical “knowledge health check” across your repositories to surface the failure patterns that drive these outcomes - duplicates, contradictions, ROT, broken links, missing ownership, and overdue reviews - then route remediation through governed workflows with human sign-off and evidence, and keep it healthy so it doesn’t drift back. The goal is straightforward: teams can trust what they find, and AI can be deployed more safely because it’s grounded in controlled, current content.

index helps organisations clean up, organise, and centralise their internal knowledge. We identify outdated files, broken links, duplicates, and content gaps, then work with your team to build a clear, searchable, and scalable knowledge system.

index differentiates itself through innovative AI solutions, market expertise, and unwavering dedication to quality. We transcend conventional approaches by understanding the unique needs of enterprises, ensuring a seamless transformation of messy content into machine-readable truth and fostering enduring partnerships that drive AI excellence.

No, not without your input and approval. We guide and support the cleanup process, but you stay in full control. We work collaboratively with your team to review, refine, and decide on any changes.

We’re a hybrid of both. Our platform provides powerful tools to scan and assess your content, and our specialists work with you directly to guide the cleanup, restructuring, and long-term knowledge management strategy.

Timelines vary based on content size and complexity, but most clients see tangible progress within a few weeks. We'll provide a clear roadmap after your index Scan.

We support organisations of all sizes, from growing startups with messy drives to large enterprises managing thousands of documents across multiple teams.

Full remediation of found issues is bound to take human involvement, but it is an effort that is well worth it. However, we know not every team has the time and resources for an in-depth remediation. That’s why we adapt to the clients’ needs and offer different levels of involvement required for different types of changes. Adjustments such as mapping broken links to their functioning new equivalents and then having these be automatically replaced only take brief alignments are a reliable automated change. Finding these changes that, in regards to effort, are low-hanging fruit, is part of our goal.

We have seen companies adapting AI without a good plan in place on how to make it reliable, trustworthy, and efficient to use, but simply due to a sense of time pressure to start using it. This leads to a drop in quality of output, frustration for users, and loss in faith in the deployed AI tools. We are here to help clients lay the groundwork for productive use of AI assistants, rather than using them as an inefficient toy.

In addition, our remediation approach improves company knowledge both for users that strive to use AI assistants and for those that prefer to use their company knowledge unassisted. Having a tidy knowledge base free of duplicates, contradictions, orphaned pages, and low-quality content benefits every user, no matter if they swear by AI-first or not.