Clearskies vs Glean

Enterprise search vs revenue context.

An honest read on how Clearskies and Glean differ — and how to pick based on where your revenue motion lives.

Where Glean is the right pick.

Cross-functional knowledge work

Glean indexes every doc, ticket, wiki, and message across your company. For finding ‘how do we handle X’ across engineering, support, HR, and product, Glean is the right shape.

Already deployed company-wide

If your company has Glean rolled out and your security team has approved it, leveraging the existing deployment is faster than introducing a new vendor.

Where the full customer context changes the answer.

Resolved customer context, not search results

Glean returns ranked documents. Clearskies returns a resolved customer story — identity-mapped, timeline-ordered, gap-detected — before your AI ever runs a query. Search-shape vs graph-shape.

Cross-system entity resolution

Clearskies knows that sarah.kim@acme.com in email, Sarah Kim in Gong, and @sarah.kim in Slack are the same person on the same deal. Glean’s search model doesn’t natively resolve identity across systems.

Gap detection

Clearskies surfaces what’s missing — a champion who went dark, a follow-up never sent. Search systems return what exists; they can’t tell you what isn’t there.

Your sales process is part of the context — and refines itself

Clearskies ingests your sales methodology, stages, exit criteria, and team structure as first-class context, then refines that model automatically as it observes calls, emails, CRM updates, and deal outcomes. Glean indexes a process doc if you’ve written one; it can’t reason about the process or improve it.

Write-back to CRM

Clearskies updates Salesforce and HubSpot fields from AI-prepared briefs. Glean is read-only enterprise search by design.

Revenue-shaped pricing

Glean is per-seat. Clearskies is a flat plan sized to your revenue team, with no per-user fees — so you can roll AI across the whole team without per-seat math.

Where they’re equivalent

Connects to your stack

Both connect to Salesforce, Gong, Slack, email. The shape of what they do with that data is different (see above) but coverage overlap is real.

Side by side.

x

Clearskies

Glean

Primary shape

Resolved customer context graph

Enterprise search index

Identity resolution across systems

First-class — sarah.kim@acme.com / Sarah Kim / @sarah.kim resolved automatically

Approximate / search-based

Timeline construction

Every interaction ordered chronologically per account, deal, and person

Per-doc; cross-source timelines not native

Gap detection

First-class — surfaces what’s missing across systems

Not supported (search returns what exists)

Sales process modeling

Ingests methodology, stages, exit criteria, and team structure — and refines the model automatically from observed activity

Indexes process docs if you’ve written them down; no reasoning or refinement

Cross-system queries

One resolved answer pulling from CRM, calls, email, and Slack

Returns ranked results across sources; user synthesizes

Write-back to CRM

Yes — Salesforce, HubSpot custom fields

Read-only

Model-agnostic

Claude, ChatGPT, Gemini, any AI via MCP or API

Glean Chat primary; some API access

Coverage outside revenue ops

Optional — focused on revenue

Strong — engineering, support, HR, product, all of it

Already in your stack

New connection

If already deployed, no new procurement

Pricing model

Flat, team-sized, no per-user fees

Per-seat

Time to value

Minutes for connection; days for first workflow

Weeks (enterprise rollout typical)

“I have Clearskies MCP connected to Claude which also connects into Amplitude, M365, and Atlassian. I’m running daily and weekly CEO Briefs on sales, competition, product sentiment, customer success, and customer health. I’m getting a level of insight that would have been impossible or massively labor intensive before.”

— Jake Olsen, CEO at Stratus

The honest call.

Pick Clearskies if

  • Your AI use cases are revenue-shaped — pipeline, deals, accounts, reps, customer success.
  • You want cross-system identity resolution and gap detection, not document search.
  • You want your sales process to live in the AI context layer, and improve itself as your team uses it.
  • You want to roll AI across the revenue team without per-seat cost math.
  • You want any AI tool (Claude, ChatGPT, etc.) to work from the same context — not be locked into one vendor’s assistant.

Pick Glean if

  • Your need is broader than revenue — engineering wikis, support tickets, HR docs, all unified.
  • Glean is already deployed and approved company-wide; leveraging existing rollout is faster.
  • Search-shape (ranked relevant docs) fits your use case better than graph-shape (resolved entities and timelines).

Comparing other AI tools too? See every comparison. Or visit Glean.

Run a side-by-side.

Same data, both tools, one workflow you don’t fully trust today. See the difference on something real.