AI tool comparison
Glean Agentic Search vs Toki 2.0
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Productivity
Glean Agentic Search
Enterprise search that doesn't just find — it does
75%
Panel ship
—
Community
Paid
Entry
Glean Agentic Search extends enterprise knowledge retrieval into action execution, letting users issue natural language requests that trigger workflows across connected SaaS tools like Salesforce, Jira, and Notion. Rather than returning a list of documents, the agent interprets intent and performs tasks — updating records, creating tickets, summarizing threads — across the company's connected app graph. It builds on Glean's existing enterprise search index, meaning the agent has context about who you are, what you work on, and what permissions you hold before it acts.
Productivity
Toki 2.0
Turn vague goals into time-blocked calendar schedules automatically
75%
Panel ship
—
Community
Free
Entry
Toki 2.0 takes the gap between intention and execution seriously. You type a goal — 'learn piano', 'ship the MVP', 'train for a half marathon' — and Toki converts it into a structured, time-blocked schedule on your actual calendar. The 2.0 update focuses specifically on handling vague inputs: goals without deadlines, interests without clear milestones, and ambitions without a plan. The engine behind it does two things: it breaks goals into concrete sub-tasks with realistic time estimates, and it finds open slots in your existing calendar to place them. It accounts for your current commitments, working hours preferences, and energy patterns based on historical scheduling behavior. The output is a calendar, not a to-do list — each item has a start time and a duration. This is an indie launch from a small team shipping on Product Hunt today. The concept is deceptively simple but the execution gap — converting 'I want to do X' into an actual calendar event with a specific time — is where most people's goals go to die. Toki makes that conversion automatic.
Reviewer scorecard
“Glean is the rare enterprise AI product that has earned its agentic claims — they're not bolting 'agent' onto a search box, they already have the permission-aware, multi-app index that makes cross-app action actually coherent. The direct competitors here are Microsoft Copilot and Salesforce Einstein, and Glean genuinely beats them on breadth of integrations for non-Microsoft shops. What kills this in 12 months isn't a better competitor — it's that Microsoft 365 Copilot bundles this for free for the 80% of enterprises already on Office, and Glean's pricing cannot survive that math for most mid-market buyers. Ship it today if you're not a Microsoft shop; evaluate very carefully if you are.”
“Every AI scheduling tool faces the same cold-start problem: the AI doesn't know what your goals actually require, so it guesses. 'Learn piano' could be 15 minutes or 2 hours a day depending on your ambition level. Until AI scheduling has genuine context about your life and real feedback loops, these plans are mostly aspirational fiction dressed as a calendar.”
“The buyer here is the CIO or VP of IT at a 500-2000 person company that has already committed to a heterogeneous SaaS stack — Salesforce, Jira, Notion, Confluence, Slack — and is drowning in context-switching. That's a real budget line (digital workplace, employee productivity) and Glean has been extracting it for years. The moat is the permission-aware enterprise index they've spent years building: the agent only acts within what you're already allowed to see, which is the exact blocker that makes every homegrown agentic experiment fail in enterprise security reviews. The stress test is straightforward — if Microsoft bundles 80% of this into Copilot for M365 shops, Glean loses the volume market. But for Salesforce-centric or mixed-stack enterprises, the workflow lock-in compounds with every new integration connected, and that's a real retention flywheel.”
“The primitive here is a permission-scoped action router that sits on top of an enterprise search index and dispatches natural language intents to SaaS API connectors — which is actually a defensible and interesting thing. But Glean publishes no API documentation for the agentic layer, no connector SDK, and no developer-facing primitives I can find anywhere on their site. If you want to hook this into a custom internal tool or compose it with your own agents, the answer is 'talk to sales.' The DX bet is entirely 'we do everything inside our platform,' which means I'm not composing Glean primitives — I'm adopting a Glean workflow. For engineering teams that want to build on top of enterprise search-as-infrastructure, this is a locked box. Skip until they publish an API that lets me call the agent, not just use it.”
“The calendar integration is what separates this from every other goal-setting app. Putting it on the calendar is the commitment. If this handles Google Calendar and Outlook reliably, it solves a real friction point. The 2.0 focus on vague inputs is the right problem to solve — structured goal input was always fake precision.”
“Glean's thesis is specific and falsifiable: that enterprise SaaS fragmentation (average company uses 130+ apps) will not consolidate fast enough for any single platform to own the index, so a neutral cross-app agent with deep permission context becomes the operating system layer for knowledge work. That thesis holds as long as Microsoft doesn't fully vertically integrate its Copilot across non-Microsoft apps, and as long as enterprises keep diversifying their SaaS stacks — both of which have been true trends for a decade. The second-order effect that matters: if Glean wins, it becomes the entity that holds the most complete map of organizational knowledge and action history, which shifts power from individual SaaS vendors toward Glean as an enterprise dependency. The trend line is the shift from retrieval to execution in enterprise AI, and Glean is on-time, not early — they have the index, the integrations, and now the action layer, which is exactly the right sequence.”
“AI-mediated time allocation is underrated as a category. Most knowledge workers have no systematic way to translate priorities into time. Tools that automate the scheduling layer — freeing humans to focus on defining what matters — are going to become standard productivity infrastructure within three years.”
“As someone who juggles creative projects alongside client work, the idea-to-calendar conversion solves a real problem. The question is whether it handles irregular schedules and creative flow states intelligently. If it just force-fits rigid blocks, it'll feel clinical. But the impulse is exactly right — intentions without time don't become reality.”
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