Glean is the tool most enterprise teams benchmark against when they want AI-powered search across their company data. It earns that position: deep connectors, a knowledge graph that understands org structure, and solid permission inheritance. At $50+/user/month, it also earns a hard look at what else is out there.
But there is a second, more important question buried in most Glean evaluations: do you need better search, or do you need your AI agents to understand your business? Those are different problems, and the tools that solve them are increasingly different too. A Reddit thread on enterprise search futures put it plainly: "the search UI likely fades, but the context layer underneath becomes infrastructure for agents."
This post is honest about what Glean does well and routes you to the right alternative based on what you actually need.
Key takeaways
- Glean is strong at enterprise search: deep indexing, org-graph personalization, and permission-aware retrieval across 100+ connectors.
- Its pricing ($50+/user/month, cloud-only) and search-first architecture push many teams to look elsewhere.
- If you need a human-facing search interface, GoSearch, Guru, and Onyx are the strongest Glean-shaped alternatives.
- If you need your AI agents — Claude, ChatGPT, Cursor, Codex — to understand your business, you need a context layer that exposes company knowledge as MCP servers, not a search UI.
- Gyld is built specifically for the agent-context problem: it ingests your existing apps, permissions the knowledge, and serves it to agents through MCP — no fine-tuning, no hand-built RAG pipeline.
What Glean is good at — and who should stay on it
Glean is a horizontal enterprise search platform. It connects to 100+ SaaS tools, builds a knowledge graph that understands who you are and who you work with, and surfaces answers personalized to your role and relationships. Its own comparison page highlights that graph-based personalization and permission-aware context delivery as the core differentiators over simpler search tools.
That architecture genuinely wins for teams whose primary need is a single place where employees can ask questions and get sourced answers from across the company's SaaS estate. Large enterprises with complex org structures, compliance requirements, and thousands of users get real value from Glean's depth.
The reasons teams look for alternatives are consistent across forums and comparison sites:
- Cost. At $50+/user/month, a 200-person company pays $120,000/year before negotiation. That is a hard number to justify for search alone.
- Cloud-only deployment. Teams with data residency requirements or a preference for self-hosted infrastructure have no option with Glean.
- Search-first, not agent-first. Glean answers questions when employees ask them. It was not designed to feed context into Claude Code, ChatGPT, or Cursor as those agents run autonomously.
- Enterprise sales motion. No self-serve trial, mandatory demo, long procurement cycles — a poor fit for smaller teams or those wanting to move fast.
How to choose: route by what you actually need
Before the list, two questions that determine which category of tool you need:
1. Who is the consumer of the answer? If it is a human typing a question into a search box, you need an enterprise search tool. If it is an AI agent running a workflow, you need a context layer that the agent can query programmatically.
2. What is your cost ceiling? If per-seat pricing at $50+/month is viable and you have a large, complex org, Glean may be worth the price. If you have fewer than 200 seats or need self-hosting, the alternatives below are meaningfully cheaper.
The alternatives below are split into two groups: Glean-shaped search tools (same problem, different trade-offs) and agent-context tools (different problem, different architecture).
Selection criteria
Each entry was evaluated on: connector breadth and quality, permission handling, deployment flexibility (cloud vs. self-hosted), pricing transparency, and — for agent-context tools — how the knowledge is exposed to AI agents (API, MCP, RAG pipeline, or other).
Glean-shaped alternatives: better enterprise search
1. Onyx (open-source, self-hostable)
Best for: Teams that need Glean's core search capability but require self-hosting, data sovereignty, or cannot justify the cost.
What it is: Onyx (formerly Danswer) is an MIT-licensed enterprise search platform with 40+ connectors, AI chat, agents, and deep research. It can be self-hosted on your own infrastructure or used via Onyx Cloud.
Why it fits:
- Genuine open-source license — you can audit, modify, and self-host
- 40+ connectors covering Slack, Notion, Google Drive, Confluence, Salesforce, and more
- AI chat and agent capabilities built in
- Starts free (community edition) or $20/user/month on cloud (annual billing)
Trade-offs:
- Self-hosting requires engineering capacity to deploy and maintain
- The knowledge graph and org-personalization depth is less mature than Glean's
- Smaller enterprise support organization than Glean
Pricing: Free (community, self-hosted) or $20/user/month (cloud, annual billing), per Onyx's published pricing.
2. GoSearch
Best for: Mid-market teams wanting a Glean-like experience with faster deployment and lower cost.
What it is: GoSearch is an AI enterprise search platform that connects to 100+ apps and surfaces answers with source citations. It is part of the GoLinks product suite.
Why it fits:
- Broad connector library covering the standard SaaS stack
- AI-generated answers with source attribution
- Faster self-serve onboarding than Glean's enterprise sales motion
- People search and org-chart awareness
Trade-offs:
- Less depth in the knowledge graph and personalization compared to Glean
- Primarily cloud-hosted; self-hosting options are limited
- Better suited to mid-market than very large enterprise deployments
Pricing: Not publicly listed; requires a demo.
3. Guru
Best for: Teams that want search combined with a managed knowledge base — closer to a wiki with AI search on top.
What it is: Guru is a knowledge management platform with AI search across connected sources including Slack, Notion, Google Drive, and Salesforce. Reddit evaluators note it as "the closer Glean-shaped replacement" for teams that also want curated knowledge cards.
Why it fits:
- Combines search with editable knowledge cards teams can verify and maintain
- Integrates with Slack, Notion, Google Drive, Salesforce
- Good for customer-facing teams (support, sales) who need both search and curated answers
- More affordable than Glean for smaller teams
Trade-offs:
- Knowledge cards require ongoing curation — the quality of answers depends on how well the knowledge base is maintained (see why a wiki nobody updates isn't company context for AI)
- Less strong on the breadth of automatic indexing compared to Glean
- Not designed to feed AI agents
Pricing: Free tier available; paid plans from $10/user/month (published on Guru's site).
4. Microsoft Copilot (Microsoft 365)
Best for: Organizations already deep in the Microsoft 365 ecosystem (Teams, SharePoint, Outlook, OneDrive).
What it is: Microsoft Copilot is AI-powered search and assistance built into Microsoft 365. It indexes your Microsoft data estate and surfaces answers in Teams, Word, Excel, and Outlook.
Why it fits:
- Zero additional connector work if your company runs on Microsoft 365
- Permission inheritance from Active Directory and SharePoint
- Integrated into the tools employees already use daily
- Microsoft's enterprise compliance and data residency options
Trade-offs:
- Effectively limited to the Microsoft ecosystem — weak on Notion, Salesforce, HubSpot, and other non-Microsoft SaaS
- $30/user/month add-on on top of existing Microsoft 365 licensing
- The search quality outside the Microsoft graph is poor
- Not designed to expose context to external AI agents
Pricing: $30/user/month add-on to Microsoft 365 Business or Enterprise plans.
5. Coveo
Best for: Large enterprises with complex relevance-tuning requirements, particularly e-commerce or customer support at scale.
What it is: Coveo is an enterprise AI search platform with deep relevance engineering, behavioral analytics, and connectors for large content estates. It has been in the enterprise search market longer than most alternatives here.
Why it fits:
- Mature relevance tuning and behavioral signals
- Strong in customer-facing search (e-commerce, support portals) as well as internal search
- Robust analytics on search behavior
- Enterprise compliance and data residency options
Trade-offs:
- Complex implementation — typically requires a professional services engagement
- Pricing is enterprise-negotiated and opaque; comparable to or higher than Glean for large deployments
- The AI chat and generative layer is less mature than Glean's
- Not designed for agent-context use cases
Pricing: Not publicly listed; enterprise contracts.
Agent-context alternatives: feeding knowledge to AI agents
The tools above are Glean-shaped: they answer human questions through a search interface. The tools below solve a different problem — getting your company's knowledge into the AI agents your team already uses, so those agents can act on real business context rather than hallucinating.
This distinction matters more as teams move from "AI search" to "AI agents doing work." As one Reddit commenter put it in a thread on Glean's future: the context layer underneath search becomes infrastructure for agents. For a deeper look at why this distinction matters, see what a context layer gives AI agents that bigger models cannot.
6. Gyld — company brain as MCP servers
Best for: Teams who want the AI agents they already use — Claude, ChatGPT, Cursor, Codex — to understand their business without building a RAG pipeline or fine-tuning a model.
What it is: Gyld is a business context layer for AI. It ingests data from the apps a company already uses — Slack, Gmail, Outlook, Notion, Google Drive, HubSpot, Salesforce, QuickBooks, and more — into a per-company knowledge base, then exposes that knowledge as MCP servers (Model Context Protocol). Any AI agent that supports MCP can plug in and query real company context: decisions, commitments, project status, customer history, financial data.
The key difference from enterprise search tools: Gyld's output is not a search result page for a human. It is a structured context feed that an agent queries mid-task. Ask Claude "what did we promise Acme last quarter?" and it pulls the answer from your actual Slack threads and HubSpot notes, with the source attached.
Why it fits:
- No fine-tuning, no hand-built RAG pipeline — Gyld handles the ingestion and indexing
- You choose exactly what gets indexed; knowledge is permissioned (private, team, or company-wide)
- Every answer is source-cited — the agent tells you where it found the information
- Stays current as your apps update, without manual maintenance
- Works with agents you already use: Claude Code, ChatGPT, Codex, Cursor
- No new search UI to train employees on — the context goes into the tools they already have
Trade-offs:
- Gyld is an agent-context layer, not a human-facing search interface — if your primary need is employees typing questions into a search box, a Glean-shaped tool is a better fit
- MCP is a relatively new protocol; agent workflows need to be set up to use it
- The value scales with how much you use AI agents — teams not yet running agents get less from it
Pricing: Not published; see gyld.ai for current plans.
For a detailed look at how this compares to building your own RAG pipeline, see Gyld vs RAG.
7. Coworker.ai
Best for: Enterprise teams wanting agents that proactively act on company context — updating CRMs, flagging risks — rather than answering search queries.
What it is: Coworker.ai is an agent platform that pre-synthesizes org context in the background so agents can act proactively across 50+ tools. It positions itself explicitly as a Glean alternative on the agent-action dimension.
Why it fits:
- Agents act without being asked — proactive CRM updates, risk flags, follow-up drafts
- 50+ tool integrations
- Self-serve onboarding at $29.99/user/month (published pricing)
- Includes meeting transcript processing, Salesforce updates, and email drafting in its agent workflows
Trade-offs:
- Proactive agents require careful configuration to avoid acting on stale or incorrect context
- The platform is newer and less battle-tested at large enterprise scale than Glean
- Less control over exactly what context agents consume compared to Gyld's permissioned indexing model
- Vendor lock-in to Coworker's agent runtime — context is not exposed as MCP for use in Claude or Cursor
Pricing: $29.99/user/month, per published pricing.
8. PipesHub
Best for: Engineering teams that want an open-source, self-hostable context layer they can extend and audit.
What it is: PipesHub is an emerging open-source alternative in the enterprise search and context space. It is self-hostable and positioned for teams that need data sovereignty alongside AI-powered knowledge retrieval.
Why it fits:
- Open-source and self-hostable — full control over data and infrastructure
- Emerging connector ecosystem
- No per-seat licensing cost for self-hosted deployments
- Appeals to teams with strong engineering capacity who want to own the stack
Trade-offs:
- Significantly less mature than Glean or Onyx — fewer connectors, smaller community
- Requires substantial engineering effort to deploy, maintain, and extend
- No managed cloud option at the level of Glean or GoSearch
- Agent-context exposure (MCP or equivalent) is not yet a core feature
Pricing: Open-source; self-hosted deployment costs depend on your infrastructure.
How to choose: a routing guide
| Your situation | Best fit |
|---|---|
| Large enterprise, complex org, need personalized search for employees | Glean (stay) or GoSearch |
| Need Glean's core search but can't justify $50+/user/month | Onyx (self-hosted) |
| Deep in Microsoft 365, minimal non-Microsoft SaaS | Microsoft Copilot |
| Want search plus curated knowledge cards | Guru |
| Complex e-commerce or support search at scale | Coveo |
| Want AI agents (Claude, ChatGPT, Cursor) to understand your business | Gyld |
| Want proactive agents that act across tools without being asked | Coworker.ai |
| Engineering team, need open-source self-hosted context layer | PipesHub or Onyx |
The dividing line is whether you are solving for human search or agent context. Most enterprise search tools — including Glean — were designed before AI agents became the primary consumer of company knowledge. The architecture that works for a search UI (index, rank, return a result page) is not the same architecture that works for an agent that needs structured, permissioned, source-cited context mid-task.
If your team is already running AI agents and finding that they hallucinate or give confident wrong answers about your business, the problem is almost certainly missing context rather than a weak model. A company brain that feeds real context into those agents solves that problem at the source. See also why AI agents give wrong answers about your business for a detailed breakdown of the failure mode.
Frequently asked questions
What is the main difference between Glean and a company brain like Gyld?
Glean is a search interface: employees type questions and get answers. Gyld is a context layer for AI agents: it ingests your company's data and exposes it as MCP servers so agents like Claude or ChatGPT can query real business context mid-task, without a human in the loop. They solve adjacent but distinct problems.
Why is Glean so expensive?
Glean's published pricing starts at $50+/user/month for cloud-only deployment. The cost reflects its enterprise sales motion, deep connector development, and the knowledge graph infrastructure. Teams that need self-hosting or have fewer than a few hundred users typically find the cost hard to justify relative to alternatives like Onyx.
Can I replace Glean with an open-source tool?
Yes. Onyx is the most direct open-source replacement, with 40+ connectors, AI chat, and agent capabilities, MIT-licensed and genuinely self-hostable. PipesHub is an emerging option for teams with strong engineering capacity. Both require infrastructure to run, which adds operational cost that partially offsets the licensing savings.
What is an MCP server and why does it matter for enterprise AI?
MCP (Model Context Protocol) is a standard that lets AI agents query external data sources in a structured, permissioned way. Instead of an agent hallucinating from its training data, it can call an MCP server mid-task and get a real, source-cited answer from your company's actual data. Gyld exposes company knowledge as MCP servers so agents like Claude Code and Cursor can use it directly.
Do I need both an enterprise search tool and an agent context layer?
Possibly. Enterprise search solves the human-facing problem: employees finding information. An agent context layer solves the machine-facing problem: AI agents understanding your business. If your team uses both employee search and AI agents, you may need both — though the context layer often reduces the frequency with which employees need to search manually.
Is Glean good for small teams?
Glean's pricing and enterprise sales motion make it a poor fit for teams under 100-200 people. Guru and GoSearch are more accessible for smaller teams. For small teams running AI agents, Gyld's per-company model scales down more naturally than per-seat enterprise search pricing.
What apps does Gyld connect to?
Gyld connects to Slack, Gmail, Outlook, Notion, Google Drive, HubSpot, Salesforce, QuickBooks, and more. The customer chooses exactly what gets indexed, and knowledge is permissioned at private, team, or company-wide levels. Every answer the agent returns is source-cited back to the original document or message.
Related reading
- What a Context Layer Gives AI Agents That Bigger Models Cannot — why the agent-context problem is architecturally different from enterprise search
- Best Company Brain Software in 2026 — a broader look at tools that give AI real business context
- Company Brain vs Knowledge Base — why static wikis fail as AI context and what to do instead
- Why AI Agents Give Wrong Answers About Your Business — the root cause and the fix
If you have landed here because your AI agents keep hallucinating about your own business, the fix is giving them real company context — not a better search UI. Start building your company brain with Gyld and connect the apps your team already uses in a few minutes.