Glean + Snowflake unify account data by pairing Snowflake’s structured datasets (queried via Cortex Analyst) with Glean’s enterprise knowledge graph of documents, tickets, emails and chats. The result is permission-aware, explainable insights for sales and service teams—delivered in natural language and grounded with citations.

Why this matters

Most “account 360” views miss the rich context living outside tables—briefs, proposals, support threads, meeting notes. Glean captures that unstructured knowledge and permissions; Snowflake houses governed facts and metrics. Together, they generate context-rich, explainable answers for account teams.

Snowflake now supports unstructured data (files on stages, Document AI, processing patterns) and promotes RAG for grounding LLMs in enterprise context—complementary to Glean’s graph and hybrid search.

How it works (at a glance)

• Structured data (Snowflake): Revenue, product usage, pipeline, support KPIs—queried with Cortex Analyst in SQL or natural language, and orchestrated by agents.

• Unstructured knowledge (Glean): Contracts, QBR decks, tickets, notes, emails—indexed with permissions into Glean’s enterprise/company knowledge graph.

• RAG & context: For a user question (“What risks for ACME this quarter?”), an agent calls Snowflake for metrics and Glean for context, then assembles a permission-aware answer with citations. (Glean’s update also describes Snowflake Intelligence agents calling Glean for context.)

What’s new

• Direct Glean ↔ Snowflake Cortex Analyst integration so users/agents query Snowflake from Glean with NL/SQL and receive grounded summaries.

• Snowflake unstructured workflows (stages, Document AI) broaden what can sit near your facts—useful for lineage and audit.

• Glean’s “context graph” direction highlights modelling work relationships for agent reliability and personalisation.

Practical examples (account teams)

1) QBR readiness
Prompt: “Prepare an ACME QBR brief.”

• Snowflake: ARR trend, product adoption, open renewals.

• Glean: last EBR deck, support escalations, executive emails.
  Output: a one-pager with citations to Snowflake rows and linked docs; risks and next best actions.

2) Renewal risk scan
Prompt: “What could jeopardise Q2 renewals?”

• Snowflake: usage drop, support MTTR, NPS.

• Glean: incident postmortems, complaint threads, contract clauses.
  Output: risk list with owners and permission-aware links.

3) Exec briefing
Prompt: “Summarise ACME’s last 90 days for a C-suite email.”

• Combines Snowflake metrics with key decisions pulled from Glean; returns a short narrative with inline sources.

Implementation roadmap (60–90 days)

Weeks 1–2 — Scope & security

• Pick one journey (renewals or QBRs).

• Confirm data classifications and permission mapping (what each role may see). Glean connectors fetch both content and permissions; Snowflake provides governed access to tables.

Weeks 3–5 — Connect & model

• Enable Glean connectors (docs, tickets, email, wiki) and configure Snowflake Action Pack/Cortex Analyst in Glean to run NL or SQL queries against Snowflake.

• Define the account graph: Accounts ↔ Contacts ↔ Opportunities ↔ Tickets ↔ Docs.

Weeks 6–8 — Build RAG flows

• For each prompt, specify: Snowflake query, Glean search scope, and citation rules.

• Store outputs with source links; test precision/recall with SMEs. (Follow Snowflake’s RAG guidance.)

Weeks 9–12 — Pilot & measure

• Roll to a small AE/CSM cohort.

• Track: time-to-brief, answer precision, citation coverage, and meeting prep time saved.

Success metrics & governance

Measure P95 answer latency, citation rate, benefit realisation (hrs saved), and data access violations (zero). Keep provenance and access controls intact across both systems; review prompts and outputs for explainability.

FAQs

Q1. How does this integration benefit businesses?
It merges Snowflake’s governed metrics with Glean’s unstructured, permission-aware knowledge to deliver explainable account insights directly in the flow of work—via NL/SQL and agents.

Q2. What types of data are integrated?
Structured: tables and views in Snowflake. Unstructured: files, docs, emails, tickets, wikis and chats indexed in Glean; Snowflake also supports unstructured files on stages and Document AI.

Q3. Is this suitable across industries?
Yes—particularly where account, service and compliance narratives must blend metrics with documents (e.g., SaaS, FS, healthcare). RAG patterns and Cortex + Glean apply broadly.