How to Build, Deploy and Govern AI Agents with Glean: The Enterprise Solution
Most enterprises struggle with AI agents that lack context about their business - leading to generic responses and security risks. Glean's platform combines enterprise search with AI workflows to create agents that understand your data relationships, permissions and processes. See how companies like Canva achieved 70% ticket deflection and Uber saved $200M annually through contextual AI automation.
The Enterprise AI Challenge
Enterprise teams face a fundamental disconnect when implementing AI agents. While consumer AI tools provide generic capabilities, business processes require deep understanding of organizational context - who has access to what data, how departments interact, and where sensitive information resides.
Ryan Der from Glean explains: "If you don't have this contextual engine, you're really not going to have great agents because they're not pulling on great information in the first place." This context gap leads to three major problems:
- Agents make recommendations based on incomplete data
- Security risks from over-permissioned access
- Manual workarounds that negate automation benefits
70% of enterprise AI projects fail due to lack of contextual understanding according to Gartner. Glean solves this by building agents on top of an enterprise knowledge graph that maps relationships between people, data and processes.
Glean's Unique Approach
Glean's platform combines three innovative layers to enable contextual AI agents:
- Enterprise Graph: Connects to 100+ SaaS tools to build a map of your organization's data relationships and activity signals
- Hybrid Search: Combines vector search with traditional keyword search enhanced by self-learning language models
- Protect Layer: Adds permission-aware queries, sensitive content detection and AI security monitoring
As shown in the demo (timestamp 12:45), this foundation enables agents that understand not just information but how it connects across your business. For example, when an employee asks "How can I get a new laptop?", Glean:
- Identifies the user's department and location
- Checks recent policy updates in SharePoint
- References similar resolved tickets in ServiceNow
- Ensures only approved vendors are suggested
Real-World Results
Glean's approach delivers measurable business impact across industries:
Canva: Achieved 70% deflection in internal IT tickets by using Glean agents to automatically answer common employee questions about software, permissions and equipment requests.
Uber: Realized approximately $200 million in annual productivity savings by deploying Glean to their engineering teams. Agents automate documentation lookup, code context retrieval and cross-team coordination.
Financial Services Firm: Reduced new hire ramp time from 3 months to 3 weeks by using Glean agents as personalized onboarding assistants that surface relevant training materials and introduce key contacts.
Glean Agent Architecture
Glean agents follow a structured workflow architecture demonstrated at 18:30 in the video:
- Trigger: Manual launch, chat message, content update or scheduled
- Context Gathering: Search across connected systems using the enterprise graph
- Document Processing: Read and analyze relevant files, tickets and communications
- Personalization: Incorporate user role, projects and activity history
- Response Generation: Apply appropriate LLM with prompt engineering
- Action: Create tickets, send messages or update systems
This modular approach allows non-technical users to build agents through Glean's visual workflow builder while giving developers API access for advanced customization.
Building Agents Without Code
The demo (starting at 20:15) shows how Glean's natural language agent builder enables business teams to create sophisticated workflows:
Example: An "Intelligent Reminders" agent that automatically generates daily briefings by:
- Searching emails, chats and calendar
- Reading call transcripts
- Analyzing personal activity patterns
- Generating prioritized action items
- Posting to Slack with relevant documents
Key features that make agent building accessible:
- Natural language instructions instead of code
- Pre-built actions for common systems (Slack, Jira, Salesforce)
- Model selection per step (Claude for analysis, GPT for responses)
- Testing and debugging within the interface
Security & Governance
Glean addresses critical enterprise requirements through:
Permission-Aware Queries: Agents only access data the initiating user could see in the source system. If you can't view a Salesforce record directly, the agent can't either.
Sensitive Content Protection: Automatic detection and redaction of PII, financial data and other confidential information before processing.
AI Security Tools: Monitoring for prompt injection attempts and other adversarial attacks with enterprise-grade logging.
Ryan emphasizes: "We're also providing AI security tools that are looking for things such as prompt injection and more. Really at the end of the day, this foundation is what's going to provide the base for Glean agents."
Implementation Path
Successful Glean deployments follow a phased adoption approach:
Phase 1: Work Faster (Weeks 1-2)
Agents answer questions quickly by retrieving existing information
Phase 2: Work Smarter (Weeks 3-6)
Agents begin synthesizing information across systems to provide insights
Phase 3: Work Different (Months 2-3)
Agents automate entire processes like ticket resolution or onboarding
Glean's professional services team helps define success metrics and quantify ROI at each stage, ensuring leadership sees the impact of AI investments.
Watch the Full Tutorial
See Glean's agent platform in action during the full 29-minute demo. Key moments include the IT ticket automation workflow at 22:40 and the knowledge base article generator at 25:15 that automatically documents solutions from support tickets.
Key Takeaways
Glean represents the next generation of enterprise AI - moving beyond generic chatbots to context-aware agents that understand your business. Three critical insights:
In summary: 1) Enterprise AI requires deep context about data relationships 2) Glean's knowledge graph provides this foundation while maintaining security 3) Non-technical teams can build powerful agents through natural language instructions.
Companies seeing the greatest ROI focus first on high-impact use cases like IT support and employee onboarding before expanding to other departments.
Frequently Asked Questions
Common questions about Glean AI agents
Glean uniquely combines enterprise search with AI agents through its knowledge graph technology. Unlike standalone chatbots, Glean connects to over 100 SaaS data sources to build context about your organization's data relationships, permissions, and workflows.
This enables agents that understand not just information but how it connects across teams and systems. Companies like Canva achieved 70% ticket deflection by leveraging this contextual understanding.
- Pre-built connectors for all major enterprise systems
- Permission-aware queries that respect existing access controls
- Personalized results based on user role and activity history
Glean Protect provides three layers of security: 1) Permission-aware queries that respect existing access controls at the source system level 2) Sensitive content detection that can redact or exclude confidential information from agent processing 3) AI security tools monitoring for prompt injection and other vulnerabilities.
All agent interactions are governed by the same permissions as the human user initiating them. The platform never elevates access beyond what's granted in the connected systems.
- SOC 2 Type II certified infrastructure
- Data never leaves your existing storage locations
- Enterprise-grade audit logging for all agent activities
Glean agents excel at three categories of automation: 1) Information synthesis like creating daily briefings from emails, chats and documents 2) Process automation such as ticket routing and KB article generation (Uber saved $200M annually here) 3) Context-aware assistance like IT support workflows that understand your role and past tickets.
The platform includes pre-built templates for common use cases across departments including IT, HR, sales and customer support.
- Employee onboarding assistants
- Automated RFP responders
- Intelligent IT help desk agents
No - Glean's natural language agent builder allows non-technical users to create workflows through conversational instructions. The demo showed how sales and finance teams build agents without coding.
For advanced use cases, developers can use Glean's APIs to integrate with custom systems. The platform supports a citizen developer approach where business teams prototype agents that IT can later harden and scale.
- Visual workflow builder with drag-and-drop steps
- Natural language instructions for non-coders
- Pre-built actions for common enterprise systems
Glean provides quantified impact metrics including: Ticket deflection rates (Canva: 70%), Productivity savings (Uber: $200M/year), Time-to-proficiency reductions for new hires, Support cost per case reductions.
The implementation process includes defining success metrics upfront and instrumenting workflows to track them. Glean's professional services team helps customers translate AI adoption into business KPIs.
- Pre-built dashboards for common metrics
- Custom measurement frameworks per use case
- ROI calculators for leadership reporting
Glean is model-agnostic, supporting Claude, Llama, GPT and Gemini through your organization's preferred API keys. Unique to Glean is the ability to use different models for different steps in an agent workflow - for example, Claude for document analysis and GPT for response generation.
This prevents vendor lock-in while allowing performance optimization per task. Enterprises maintain control over which models are used and how they're accessed.
- Switch models per workflow step
- Bring your own API keys
- Private model deployment options
Simple agents can be built in under 30 minutes as shown in the demo. Enterprise deployments typically follow a 3-phase rollout: 1) 2-week pilot connecting core systems and testing high-impact use cases 2) 4-6 week department-level deployment with 5-10 agent workflows 3) 3-6 month org-wide scaling.
Glean's pre-built connectors accelerate setup - most customers see value within the first month. The platform includes change management resources to drive user adoption.
- Rapid prototyping capability
- Phased deployment framework
- Pre-built adoption playbooks
GrowwStacks provides Glean implementation services including: Use case identification and ROI analysis, System integration with your existing tech stack, Custom agent workflow development, Change management and user adoption programs.
Our AI automation experts can build your first 3 agent workflows during a free 30-day pilot. We'll help quantify the impact and develop a roadmap for scaling across your organization.
- Free consultation to assess automation potential
- Hands-on workshops to train your team
- Ongoing optimization and support
Ready to Deploy Context-Aware AI Agents in Your Enterprise?
Generic AI tools waste time with irrelevant responses and create security risks. Glean's platform delivers agents that understand your business context and automate workflows securely.