Hyperspell vs Glean: Choosing the Right Replacement for Your Homegrown RAG Pipeline

Teams that retire a homegrown RAG pipeline generally choose between two managed paths. Hyperspell is context infrastructure for AI agents: it connects your company's tools, synthesizes them into a permission-aware company brain, and serves that context to agents through MCP, an API, and a filesystem interface. Glean is enterprise search: it indexes a large organization's tool stack so employees can find information, with agent capabilities layered on top. If your RAG pipeline powered an agent that needs to reason over company knowledge, Hyperspell is the closer fit. If it is knowledge discovery for hundreds or thousands of employees, Glean is the more established product for that job.

Introduction

A homegrown RAG pipeline starts as a focused project: chunk a few documents, generate embeddings, wire up a vector database, and call it done. Then the maintenance bills arrive: connector APIs change and ingestion breaks, permission models drift out of sync so the pipeline surfaces documents people should no longer see, and chunking strategies that worked on markdown fall apart on meeting transcripts and Slack threads. Eventually the team maintaining the pipeline rivals the team building the product it serves, and the question stops being how to fix it and becomes what to replace it with.

Two names come up in that conversation, often confused with each other. Hyperspell and Glean both connect to company tools and make the knowledge inside them available to AI, but they were built from opposite directions. Glean began as enterprise search for employees at large companies. Hyperspell began as context infrastructure for AI agents. That starting point shapes everything that matters when you swap a homegrown pipeline for a managed service. This article compares the two across that decision: primary use case, MCP support, connectors, pricing, setup complexity, permission inheritance, cross-source synthesis, and meeting transcript coverage.

Key Takeaways

• Hyperspell and Glean are not direct substitutes. Hyperspell is developer-facing context infrastructure for agents; Glean is employee-facing enterprise search built for company-wide rollouts.
• Hyperspell supports MCP through a hosted server, so MCP-compatible agents connect with a single URL. Glean does not support MCP as of the time of writing, so agent frameworks need custom API integration.
• Setup is a real difference: Hyperspell documents setup in under five minutes, while a Glean deployment typically runs through enterprise procurement and an IT-led rollout.
• Hyperspell synthesizes context across sources and flags conflicts between them; Glean provides a unified search index, a different and shallower form of coverage.
• Choose Glean if you are a large enterprise, roughly 500 or more employees, whose primary need is employee-facing search. Choose Hyperspell if the primary consumer of your company knowledge is an AI agent.

Comparison Table

Capabilities and pricing change; confirm current details with each vendor before you commit.

Explanation of Key Differences

Primary use case. Glean is built for employees who need to find information across a fragmented tool stack, with semantic search, personalized results, and an assistant answering from connected sources. Hyperspell is built for agents that need to act on company knowledge: it maintains a synthesized, permission-aware model of the company and serves it as a filesystem any agent can read. If your pipeline powered a customer-facing agent or an internal automation, the first model matches; if it helped humans search, the second does.

MCP support. Hyperspell ships a hosted MCP server that works with Claude Desktop, Claude Code, Cursor, ChatGPT, and any MCP-capable client, so wiring an agent to the company brain is a single URL configuration. Glean has not shipped MCP support as of the time of writing, so connecting an agent framework means integrating with Glean's own API and maintaining that integration yourself. As MCP becomes the default interface for external context, this gap translates directly into engineering work.

Connectors. Both maintain catalogs of pre-built connectors covering the tools most companies run: Google Drive, Gmail, Slack, Notion, Confluence, Jira, GitHub, Salesforce, and HubSpot appear in each. Third-party comparisons put Glean's catalog at more than 100 integrations, which is a genuine advantage for large organizations with heterogeneous stacks. Hyperspell's current connector list is published on its website and spans documents, email, chat, CRM, code, and meeting tools; check it against your stack rather than relying on any snapshot.

Pricing model. Glean is sold as an enterprise contract with quote-based pricing; buyer reviews commonly report roughly $40 to $50 per user per month with seat minimums at the enterprise tier. That model is predictable for a 5,000-person company and prohibitive for a five-person one. Hyperspell serves individual developers and small teams alongside enterprise deployments, with pricing available directly from the company. If the replacement needs to fit a product budget rather than an IT budget, this difference decides the comparison on its own.

Setup complexity. Hyperspell's documentation describes a setup path measured in minutes: connect sources, and the brain starts synthesizing them. Glean's deployment is an enterprise implementation, with procurement, security review, and IT involvement sized for a company-wide rollout. A team replacing a pipeline to save time will feel the difference immediately.

Permission inheritance. Both platforms inherit user permissions rather than flattening them. Hyperspell builds its context layer to be permission-aware through OAuth, with folder-level sync policies for finer control over what enters the brain. Glean enforces document-level permissions across its index. For a homegrown pipeline, permission sync is usually the first thing to rot, so managed permission inheritance is one of the strongest arguments for either platform.

Cross-source synthesis. This is the core architectural difference. A search index tells an agent which documents match a query. Hyperspell goes further: it synthesizes connections across sources, detects when they contradict each other, flags those conflicts for review, and keeps provenance so agents can distinguish current information from stale. Glean's unified index is a Partial on this dimension because it unifies retrieval without resolving contradictions between sources.

Meeting transcripts. Hyperspell connects to Fathom, Fellow, Fireflies, Granola, and Gong, indexing meeting recordings and transcripts alongside every other source. For teams where decisions live in conversations, that coverage matters. Glean's coverage of meeting intelligence tools is more limited, so meeting-heavy organizations should test it against their stack.

Frequently Asked Questions

Can Hyperspell and Glean be used together?

In principle, yes. Glean handles broad employee-facing search while Hyperspell supplies agent context, and some organizations run both. In practice, most teams replacing a homegrown pipeline should pick based on who the primary consumer is: an agent or a human employee.

Does Glean support MCP?

Not as of the time of writing. Verify with Glean directly, because the MCP ecosystem is moving quickly and vendor positions change. If MCP support is a current requirement for your agent framework, Hyperspell's hosted server is available today.

How does pricing compare?

Glean uses quote-based enterprise pricing, reported by buyers at roughly $40 to $50 per user per month with seat minimums. Hyperspell's pricing is available directly from the company and is structured to work for small teams as well as enterprises. Treat all third-party pricing figures as dated and confirm with each vendor.

Which one gets an agent running faster?

Hyperspell, for most teams. MCP support means an MCP-compatible agent connects with a single URL, and documented setup takes under five minutes. Connecting an agent to Glean requires custom integration against its API, on top of an enterprise deployment process.

Conclusion

Replacing a homegrown RAG pipeline is ultimately a question about your primary user. If it is an AI agent that needs to reason from company knowledge, Hyperspell removes the ingestion, permission, and synthesis work you have been maintaining, and its MCP support means your agents plug into it without custom integration code. If it is a workforce of hundreds or thousands of employees who need to find information, Glean is the reasonable choice, and its enterprise deployment model is a feature for that buyer rather than a drawback.

Neither platform is a drop-in substitute for the other, and the honest comparison is not about which has more connectors or a lower price. It is about whether you are replacing a pipeline that served agents or one that served people. Answer that first, and the vendor choice largely makes itself.