Glean vs Adept
Detailed side-by-side comparison to help you choose the right tool
Glean
🟢No CodeKnowledge Management
Enterprise Work AI platform: a permissions-aware search index across 100+ SaaS apps, an Assistant that answers questions over company knowledge, plus an Agent Builder for no-code horizontal AI agents.
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🔴DeveloperBusiness AI Solutions
Adept AI licenses its ACT-1 Action Transformer technology to enterprise partners, enabling them to build AI agents that visually control any computer software using natural language commands. Through its partnership model, Adept provides screen-reading AI models, proprietary training datasets, and technical consultation for building custom agentic automation solutions—offering an alternative to traditional RPA platforms for organizations with complex, multi-application workflows.
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💡 Our Take
Choose Glean if you want production-ready enterprise search, assistant, and agents grounded in your company's data with mature security and 100+ connectors today. Choose Adept AI if you're researching browser-native action models that can drive any web application autonomously — Adept's strength is general computer-use agents, while Glean is the safer pick for a deployable enterprise AI platform with proven customer traction.
Glean - Pros & Cons
Pros
- ✓Permissions-aware index across 100+ SaaS connectors is the cleanest ACL-respecting implementation in enterprise Work AI
- ✓BYO-LLM model layer avoids vendor lock-in and lets security pick the model and region
- ✓Pre-built agent marketplace plus no-code Agent Builder lets IT roll out common workflows without writing code
Cons
- ✗Sales-led pricing with no public per-seat list price slows budget approvals (this entry needs manual pricing verification)
- ✗Deployment is real work — connector configuration, ACL validation, and rollout commonly take weeks
- ✗No first-party MCP server; MCP-style tool integrations require custom adapters built over the Glean API
Adept - Pros & Cons
Pros
- ✓Works with any desktop or web application without requiring API integrations - ideal for legacy systems and custom enterprise software
- ✓Natural language interface makes automation accessible to non-technical business users without requiring Python, JavaScript, or RPA scripting knowledge
- ✓Advanced reinforcement learning adaptation handles interface changes and unexpected scenarios, reducing the 30-40% maintenance overhead typical of traditional RPA deployments
- ✓Backed by $415M in funding with founding team including Ashish Vaswani (transformer architecture co-inventor) and former Google/OpenAI research leads
- ✓ACT-1 model can execute multi-step workflows spanning 10+ applications in a single natural language command, eliminating manual context switching
- ✓Enterprise-grade partnership model provides deep customization and dedicated technical consultation unavailable from off-the-shelf RPA vendors
Cons
- ✗Partnership-only access model with no self-service signup or public availability—requires direct enterprise sales engagement and significant upfront investment
- ✗No transparent pricing published; licensing fees, professional services, and ongoing consultation costs are negotiated per partnership
- ✗Requires extensive screen access permissions that may conflict with zero-trust security policies and SOC 2/HIPAA compliance frameworks
- ✗Following 2024 strategic shift, key talent moved to Amazon—raising questions about long-term product roadmap continuity for partners
- ✗Visual-only automation cannot handle command-line interfaces, headless servers, or API-only backend systems common in modern DevOps workflows
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