At a glance

• What’s new: Glean now integrates with Vercel’s v0 and AI SDK 6 stack to ground AI-generated apps in live enterprise knowledge.

• How it works: Uses the Model Context Protocol (MCP) to let apps securely pull company context (docs, tickets, PRDs, release notes) with permissions respected.

• Why it matters: Moves AI apps from generic answers to policy-aware, role-aware outputs that reflect how your business actually operates.

• Who benefits: Product, engineering, CX and ops teams shipping AI UIs/agents on Vercel that must stay on-brand, up-to-date, and compliant.

The story

Vercel is pushing hard on agentic apps (AI SDK 6; v0 for AI-generated UIs). Glean’s integration slots into that direction by providing enterprise context—everything from architecture docs and SOPs to CRM notes—so generated flows, components and copy are grounded, current and permissioned. For builders, that means you can spin up an AI interface on Vercel that already “knows” your systems, decisions and vocabulary.

How it works

1. Connect Glean to your stack: point Glean at your SaaS/tools (e.g., Drive, Confluence, Jira, GitHub, Slack, etc.).

2. Enable Glean in Vercel: add the integration for v0 or wire via AI SDK 6/MCP so your prompts/agents can call Glean as a tool.

3. Ground prompts & agents: prompts can reference Glean as a context source; agents fetch facts, snippets and links with user-level permissions.

4. Ship: deploy on Vercel; your AI UI or agent responds with company-specific detail (owners, policies, latest docs) rather than generic boilerplate.

Why this matters for enterprises

• Relevance & trust: Outputs come from your knowledge base, honouring RBAC/ABAC and doc permissions.

• Freshness: Context updates as your knowledge changes—no stale fine-tunes.

• Velocity: v0 accelerates UI scaffolding; Glean supplies credible content. Together, teams get to value faster.

• Governance: Centralise connectors, auditing and data controls inside Glean while shipping on Vercel infra.

Practical steps

• Pilot in a narrow lane: e.g., “policy Q&A for Support” or “release-note summariser for Sales”.

• Template a v0 flow: generate a simple UI that calls a Glean-powered retrieval step.

• Add guardrails: refuse outside scope; cite sources; log decisions.

• Measure: track answer usefulness, containment rate, time-to-first-value.

Example use cases

• Engineering: PRD/diff explainer that cites internal docs and repos.

• Support: policy-aware assistant that honours entitlements and surfaces the latest fixes.

• Sales/CS: auto-compose account notes from recent tickets, Slack threads and knowledge articles.

• Operations: SOP co-pilot that outputs step-by-step actions with links to owners and systems.

FAQs

What is the main benefit?
AI apps answer with company-specific, permission-aware context instead of generic text.

How does it affect performance?
Grounding reduces hallucinations and improves relevance, which typically boosts resolution rates and trust.

Who can benefit?
Any team building on Vercel that needs AI to reflect internal processes, policies and language.