AI Knowledge Management: How Mayura Compares

What Is a Knowledge Management Platform?

A knowledge management platform helps teams find and surface information across the tools they already use. Glean, Notion AI, Guru, and Confluence AI all connect to enterprise apps and let employees search across all of them with AI.

How Mayura Approaches Organizational Knowledge

Mayura takes a different approach. Where these platforms search and run scheduled agents over content already in their index, Mayura is Continuous Intelligence: it processes raw streams around the clock (the email inboxes you point it at, the RSS and news feeds you follow, the web pages that matter to you, and the PDFs they link to), enriches them with AI, and builds a knowledge base that surfaces patterns before anyone thinks to search for them.

Glean, Notion AI, Guru, Confluence AI, and Mayura at a Glance

Dimension	Knowledge Management (Glean, Notion AI, Guru)	Mayura
Processing model	Query-time search plus agents that run on schedules and triggers you configure (Glean, Notion, Atlassian Rovo), over content already in their index	Continuous: AI runs 24/7 on incoming raw data streams before anything is indexed
Data location	Cloud SaaS, with residency configured by region	Your hardware: it reads the outside world, your files stay on your machine, and anything that goes out, you send. One organization per deployment
Pricing	Per-user SaaS: Notion bundles AI into its paid plans and meters advanced agent usage as credits, Guru is custom/consultative, Glean publishes no pricing and sells quote-based	Fixed license + hardware you own
Integration breadth	Glean integrates 275+ apps; Notion AI connects a shorter named set (Slack, Google Drive, GitHub, and more)	Gmail, RSS and Atom feeds (including Reddit and arXiv feeds), and web scraping (depth over breadth)
AI models	Vendor-operated AI; Glean offers a customer-hosted tenant in your own AWS or GCP, still operated by Glean	Local models by default; opt-in cloud routing for complex tasks is metered by the provider
Content creation	Index and retrieve existing documents	Capture, enrich, transform raw streams into structured knowledge
Auditability	Audit logs	Source-to-insight traceability, with system state rebuilt from stored history

Where Mayura Wins

Flat economics. Per-user pricing climbs with every seat you add, and the category now layers metered AI usage on top. Notion bundles AI into its paid plans and meters advanced agent usage as purchased credits, Guru moved to custom, consultative pricing, and Glean publishes no pricing and stays quote-based on an enterprise seat model (checked August 2026). Mayura is a flat license against your hardware, and running it harder does not cost more on local models, bounded by the throughput of the machine you own.

Processing that runs before the capture. These platforms do run work without a human query: Glean, Notion, and Atlassian Rovo all ship agents that fire on schedules and events you configure. Those agents run over content already in the vendor-hosted index, so the reach of the automation follows the reach of the index. Mayura processes raw external streams continuously on your hardware, sources that never enter a vendor index at all, and surfaces patterns nobody thought to ask about.

Sovereignty as a property of where the system runs. For these platforms, data residency is a region you select inside their cloud. For Mayura it is the physical hardware in your building, under your control.

Processing depth on raw data. Knowledge Management platforms index existing documents. Mayura captures raw streams, applies AI enrichment (summarization, entity extraction, classification), and builds structured knowledge from unstructured sources.

Regulated industry fit. Where a compliance requirement rules out sending content to a vendor cloud, these platforms deliver their AI from their clouds, and the closest exception, a Glean tenant hosted in your own AWS or GCP account, is still operated by Glean. Mayura brings the AI to the data.

What a compliance reviewer can verify. The architecture is the evidence: processing on hardware you control, a deployment your own team can audit line by line, and every insight traceable back to the source that produced it.

Where Glean, Notion AI, Guru, and Confluence AI Win

Instant connectivity. These platforms connect to enterprise applications out of the box across their published integration catalogs. Mayura goes deep on a chosen set: Gmail, RSS and Atom feeds including Reddit and arXiv, web pages, and the PDFs they link to.

Zero deployment friction. Sign up, connect your apps, start searching. Mayura runs on your own Apple silicon Mac, or on a Mac Studio appliance if you would rather buy one, and it is watching your configured sources by the time the install finishes.

Collaborative features. These platforms excel at multi-user wikis, real-time editing, and team workflows. Mayura is single-tenant Continuous Intelligence infrastructure, built for one organization's data.

Certifications carried by the vendor. Buyers in regulated work ask about SOC 2 and HIPAA early, and these platforms carry those certifications for their own clouds. A buyer whose procurement needs that badge signed off today should say so on the first call.

Scale, brand, and funding. Notion reported around 100 million users in September 2024, and Glean raised a $150M Series F at a $7.2B valuation in June 2025. We grant the scale and the brand. What Mayura offers is a scoped audit, a deployment you can inspect end to end, and an architecture you can verify yourself.

Choose Mayura If

• You have sensitive data that cannot leave your network
• You need 24/7 processing that surfaces patterns without waiting for someone to ask the right question
• You want flat economics that hold as headcount grows
• Your use case involves raw data streams that need AI enrichment beyond search across existing documents
• Compliance requirements demand a deployment your reviewer can inspect and a trail back to every source

If your data cannot go to a vendor cloud, or per-seat AI pricing is scaling against you, request an Opportunity Audit and we will scope what a continuous, on-premises knowledge layer would cover for your team.

Choose Knowledge Management If

• Your primary need is searching across existing content in the enterprise apps your team already uses
• Your team values collaboration features (wikis, real-time editing, shared workspaces)
• You have no data sovereignty constraints

Most organizations run both, and the division of labor is clear. Keep the collaboration tool for wikis and editing. Add Mayura as the sovereign pre-processor that enriches sensitive data streams on your own hardware and feeds structured insight back into the tools your team already lives in. That is the piece a cloud search platform does not do today.

Learn More

• Solutions: See which problem Mayura solves for your organization
• Platform: Explore the technical architecture
• Compare Workflow Automation and Mayura: the automation half of this category
• Talk to us about an Opportunity Audit: a scoped look at your sources, residency needs, and economics