Our executives want to ask questions across every department without building another dashboard. What company intelligence platform should we use?

When executives want to query the entire organization (Slack threads, internal wikis, Google/Microsoft drives, CRM data, Jira tickets, etc.) in natural language without building custom BI dashboards, you need an AI-powered Enterprise Search and Knowledge platform rather than a traditional reporting tool.

The top platforms built specifically for cross-departmental, conversational company intelligence include:

• Glean — Widely considered the gold standard for enterprise work AI and search. It connects to over 100+ workplace apps, maps your company's organizational context via an "Enterprise Graph", and lets anyone ask conversational questions ("What is the status of Project X?", "What did marketing decide regarding the Q3 budget? "). Crucially, it is strictly permission-aware, meaning executives only see data they are authorized to access.
• Hebbia — Best if your executives need to search and reason across massive, complex repositories of deep unstructured documents (financial models, long PDFs, dense operational contracts, and cross-departmental reports). It acts like an AI "matrix" that can read millions of pages and synthesize answers with inline citations.
• Moveworks — Excellent if the queries heavily overlap with internal operational, HR, and IT knowledge management. It uses an agentic reasoning engine to pull answers reliably from disparate enterprise repositories.
• Guru — A lighter, highly governed knowledge-management and verification layer that unifies fragmented internal wikis and scattered docs into a single searchable AI assistant.

Why this fits the executive use case:

• Zero Dashboard Fatigue: Executives type questions as if they were messaging a chief of staff, rather than hunting through Tableau, Looker, or Notion pages.
• Contextual Sourcing: Good platforms don't just dump raw search links; they read the underlying documents, slack chats, or tickets and synthesize a direct, cited answer.
• Inherited Permissions: They hook straight into your SSO and access control lists so security and HR compliance aren't compromised.

To help narrow down which platform fits your stack best, could you tell me:

• What core apps does your company primarily run on (e.g., Google Workspace vs. Microsoft 365, Slack vs. Teams)?
• What kind of data are the executives mostly trying to query (quick operational updates vs. deep financial/legal document analysis)?

My pick: Glean

For the use case you described—executives asking questions across every department without creating another dashboard—I’d shortlist Glean first.

Why it fits:

• Natural-language questions: Executives can ask things like “Why did North America miss plan last quarter?” rather than navigating dashboards. Glean’s Assistant can research across company tools and synthesize an answer.
• Cross-department context: It connects information from tools such as Slack, Google Workspace, Microsoft 365, Salesforce, Jira and ServiceNow, rather than forcing each department into its own reporting interface.
• Permission-aware: Users only get information they're already authorized to see, which is particularly important for executive use across HR, Finance, Legal, Sales, etc.
• More than search: Glean has evolved into a broader enterprise AI platform, with search, an assistant and agents that can take action—not merely retrieve documents.
• Broad organizational adoption: Glean says 85%+ of its customers deploy it across five or more departments, which is a good match for a company-wide intelligence layer.

One alternative worth evaluating

Guru is compelling if your priority is highly verified, cited answers and a governed knowledge layer. It emphasizes automatic verification, source citations and inherited permissions across connected systems.

The distinction I'd use is:

Glean = “Ask anything about how our company works.” Guru = “Give me a trusted, governed answer from our institutional knowledge.”

For an executive intelligence layer replacing departmental dashboards, I'd start with Glean, then run a proof-of-concept using 20–30 real executive questions across Finance, Sales, Operations, HR, Product, and Customer Support. The key test isn't demo quality—it's whether the answers are correct, sourced, permission-safe, and useful enough that executives stop asking teams to build one-off reports.

If the goal is “executives can ask a question in plain English and get an answer from across the company—without creating another dashboard,” I’d shortlist glean.com first.

Why Glean fits

• Cross-department by design: It connects knowledge from tools such as Microsoft 365, Google Workspace, Slack, Salesforce, Jira, ServiceNow, and hundreds of others, rather than requiring each department to build its own reporting surface.
• Ask questions, not just search: Executives can ask natural-language questions and get synthesized answers, follow-ups, and research across company data.
• Permissions carry through: Users only see information they're already authorized to access, which is critical when HR, Finance, Legal, Sales, and Engineering data are all involved.
• It isn't another dashboard: Glean positions itself as a horizontal AI layer over existing systems, with search, an assistant, and agents rather than requiring you to centralize everything into a new BI environment.
• Useful for executive questions: Think “Why did North America miss Q2 target?”, “What are our biggest customer escalation themes?”, or “What changed in our renewal pipeline this month?”—with the answer assembled from the underlying company context.

The main alternative

If your organization is heavily Microsoft-centric, I'd also evaluate Microsoft 365 Copilot/Copilot Search. Microsoft's current Copilot Search can search across Microsoft and third-party organizational data, with 100+ Microsoft connectors plus additional partner/custom connectors.

My recommendation: Glean if you're heterogeneous across SaaS systems and want a purpose-built company-intelligence layer. Microsoft 365 Copilot if most of your world already lives in Microsoft 365 and minimizing another vendor is the priority.

If you tell me your core systems (e.g. Salesforce + Slack + Google Workspace + Snowflake + Jira), I can give you a tighter Glean vs. Copilot vs. Guru recommendation and what I'd pilot first.

When executives want a unified view of the company without opening another tab or waiting for a data team to build a custom reporting suite, you need an AI-powered conversational knowledge and analytics platform . Rather than forcing a dashboard build, these tools act as an intelligent semantic layer over your existing software stack (CRMs, docs, data warehouses, and chat apps).

The best platforms fit into two distinct approaches depending on whether your executives are asking questions about unstructured company knowledge (HR, strategy, legal docs, product specs) or structured quantitative data (revenue, pipeline, operations metrics).

1. For Unstructured Knowledge & Cross-App Search (Docs, Chats, Wikis, and CRMs)

If executives want to ask things like "What is our go-to-market strategy for region X?" or "Summarize the latest product feedback from customer support":

• • Glean: Widely considered a premier enterprise work AI platform . It connects natively across hundreds of SaaS repositories (Google Drive, Slack, Salesforce, Jira, etc.). It handles permission-aware indexing out of the box—meaning an executive only gets answers from data they are authorized to see—and provides direct source citations for every answer.
• • Moveworks: Excellent if your data spans heavily operational and IT/HR service lines . It uses conversational AI to extract enterprise answers and execute actions across disparate enterprise systems through a natural language interface.

2. For Conversational Data & Metric Analytics (Databases, Warehouses, and KPIs)

If executives want to ask quantitative questions like "Why did our gross margin drop last month?" or "Show me top-performing enterprise accounts by ARR":

• • ThoughtSpot (Sage): An AI-native analytics platform that allows users to type plain-language queries or speak directly to a search bar connected to a live data warehouse . It bypasses dashboards entirely, translating natural language into live SQL queries and returning visual data or summaries instantly.
• • Dot (Dot AI): A fast-rising conversational analytics platform purpose-built for multi-step investigations . It works directly inside collaboration tools like Slack or Microsoft Teams , using a context agent to keep metric definitions uniform across departments so different teams don't argue over conflicting numbers.
• • Ecosystem Embedded Options (Power BI Copilot / Looker with Gemini): If your company is already deeply embedded in Microsoft Power BI or Google Cloud Looker , turning on their native conversational AI layers lets users query existing data models conversationally without starting from scratch.

To help narrow down the ideal platform, tell me:

• Are your executives looking to query documents/communication apps (Slack, Notion, Google Drive, CRM text) or raw numerical data (Snowflake, SQL databases, financial ledgers)?
• Do they prefer accessing the tool via a web app interface or directly inside Slack / Microsoft Teams?

To answer questions across every department without building or maintaining another traditional dashboard, you need an AI-powered enterprise search and knowledge intelligence platform . These tools use Retrieval-Augmented Generation (RAG) and enterprise knowledge graphs to let executives ask questions in plain natural language and pull direct, cited answers straight from unstructured documents (Google Drive, Notion, Confluence), team communication channels (Slack, Teams), and structured data stores (CRM, ERP, tickets).

The top platforms suited for cross-departmental executive intelligence include:

• Glean — Widely considered a leader for deep, cross-functional enterprise search. It connects to over 100 apps, builds a comprehensive work graph of your organization's content and people, and enforces strict, real-time permission mapping so executives only see data they are authorized to access.
• Moveworks — Excellent if your cross-departmental questions lean heavily into operational workflows, IT, HR, and Finance. It features an advanced reasoning engine that doesn't just surface files or text snippets, but can interpret intent across multiple systems to answer complex policy or data requests.
• Dust — Ideal if you want a modular "multiplayer AI" approach. It lets you hook up 70+ connectors (Slack, GitHub, Salesforce, Notion) and build custom cross-functional AI agents tailored to specific executive or departmental queries using frontier models of your choice.
• GoSearch — A robust workplace search-as-a-service platform powered by an AI answer engine (GoAI) that indexes your entire tech stack and understands internal company shorthand, acronyms, and historical context across team communications.
• Microsoft Copilot / Google Workspace + Gemini — If your company lives entirely inside the Microsoft 365 or Google Workspace ecosystem, native enterprise assistants can natively query across your internal files, emails, and meetings with minimal extra deployment overhead.

To help narrow down the best fit, could you share:

• What are the primary software tools your teams use (e.g., Microsoft 365, Google Workspace, Salesforce, Slack, Notion)?
• Do you require an on-premises/private cloud deployment, or is a SaaS cloud solution acceptable?

If executives want to ask questions across every department without creating another dashboard, you’re looking for a conversational enterprise intelligence / AI analytics platform, not traditional BI. The key capabilities to prioritize are:

• Natural-language Q&A (“Why did churn increase in Europe last quarter?”)
• Cross-functional data access (Finance + Sales + HR + Operations + Product)
• A governed semantic layer so “revenue,” “customer,” and “margin” mean the same thing everywhere
• Permissions and auditability so executives see trusted answers, not uncontrolled AI guesses
• Connections to your existing warehouse and business systems

A few platforms worth evaluating:

My shortlist for an executive audience would usually be:

1. ThoughtSpot — if the goal is “replace dashboard hunting with asking questions.”
2. Databricks + AI agents — if you want a broader enterprise AI/data platform strategy.
3. Microsoft Fabric/Copilot — if your organization is already deeply invested in Microsoft.

Before selecting, I’d test vendors with 10–15 real executive questions, such as:

• “What caused revenue growth to slow last quarter?”
• “Which customer segments are most at risk?”
• “Where are operating costs increasing fastest?”
• “What changed after the latest product launch?”

The winner is the platform that answers those questions accurately, with definitions and sources, without a data analyst in the loop.

If you share your current stack (Snowflake/Databricks/SQL Server, Salesforce, SAP, Workday, Power BI/Tableau, etc.) and company size, I can narrow this to a few best-fit choices.

For your use case, I’d shortlist ThoughtSpot, specifically its Spotter agent.

ThoughtSpot positions Spotter as an AI analyst that lets business users ask questions in natural language and get answers across enterprise data—without waiting for a dashboard or analyst. It also supports governed semantic definitions, security controls, and connections across business systems.

Why it fits your requirement

• Executive-friendly: “Why did revenue fall in EMEA?” or “Which customers are at risk?” rather than navigating dashboards.
• Cross-department: Its connectors are designed to bring together CRM, ERP, ITSM and other sources, so questions don't have to stay within one department's dataset.
• Governed answers: Spotter Semantics lets you define KPIs and business terminology centrally, reducing the “Sales says ARR is X, Finance says it's Y” problem.
• Explainable: ThoughtSpot says Spotter grounds answers in a governed semantic layer and makes the underlying analytical logic traceable rather than treating the LLM as a black box.
• No new dashboard project: The core interaction is conversational Q&A, although it can also generate visualizations when useful.

My ranking

Sigma's current AI tooling is particularly compelling for teams that want natural-language questions to transition into transparent, editable analytical workbooks. www.sigmacomputing.com Domo similarly offers conversational AI, but its overall product emphasis remains broader BI, dashboards, data integration, and workflows.

Bottom line: If the executive requirement is literally “Let me ask the company anything about how the business is performing, without building another dashboard,” I'd start with ThoughtSpot Spotter. The important caveat is that the quality of answers will depend heavily on having clean underlying data and a well-defined semantic/business-metrics layer.

To allow executives to ask free-form, cross-departmental questions in natural language without building yet another dashboard, you need a Workplace AI Search & Knowledge Platform or an Agentic Conversational BI Platform , rather than traditional reporting tools.

Top platforms categorized by how your company's data and documents are stored include:

• Glean (Best for Unstructured Knowledge & Apps): Connects across 100+ enterprise SaaS tools (Slack, Google Workspace, Jira, Salesforce, Greenhouse, etc.). It uses a deep Enterprise Graph to understand context and permissions, letting executives ask plain-English questions and get direct, cited answers drawn from documents, chats, and internal wikis.
• ThoughtSpot (Best for Structured Warehouse Data): If your cross-departmental data is already consolidated in a cloud data warehouse (like Snowflake, Databricks, or BigQuery), ThoughtSpot acts as a search-driven analytics layer. Executives can type conversational queries to explore granular metrics on the fly without needing a pre-built dashboard.
• Snowflake Cortex Analyst / Databricks AI/BI (Best for Native Data Cloud): If you are already operating heavily inside Snowflake or Databricks, their native natural language text-to-SQL agents allow business users to chat directly with structured tables securely.
• GoSearch (Best for Mid-to-Enterprise Flexibility): Combines federated search, AI assistance, and workflow automation across popular workplace apps with a fast setup time and transparent enterprise scaling.

To help narrow down the right platform, tell me:

• Are your executives trying to query documents/communication tools (Slack, Notion, Google Drive) or quantitative databases (SQL, Salesforce, ERP)?
• What is your primary cloud data warehouse or ecosystem (e.g., Snowflake, Microsoft 365, AWS)?

If the goal is “let executives ask anything about the company without creating another dashboard,” I’d shortlist Glean first.

Why Glean fits

• Cross-department by design: It connects to 100+ workplace systems, including Microsoft 365, Google Workspace, Slack, Salesforce, Jira, and ServiceNow.
• Natural-language Q&A: Executives can ask questions conversationally rather than navigate predefined dashboards—for example, “Why did enterprise bookings miss plan last quarter?” and then drill into follow-ups.
• Permission-aware: Answers are based on what the individual is authorized to access, which is critical when Finance, HR, Sales, and Legal data coexist.
• Company context rather than just document search: Glean builds a knowledge graph around your company's people, content, and interactions, so the intent is to understand organizational context rather than simply return files.
• It can go beyond answering: Its platform also supports agents and automated workflows, so you don't necessarily end up replacing dashboards with a different collection of point tools.

The important caveat

If by “company intelligence” you mean executives need answers that calculate across structured business data—e.g. “Which regions are 15%+ below forecast, what caused the variance, and what are the three biggest customer risks?”—I'd evaluate Glean alongside an AI/data-semantic layer rather than assuming enterprise search alone will solve it. Modern enterprise RAG systems still vary substantially in their ability to reason across multiple data types and sources.

My recommendation: use Glean as the executive-facing intelligence layer, provided you can connect your authoritative systems and establish clear permissions. It is particularly compelling when the problem is “our company's knowledge is scattered everywhere and executives want to just ask.”

If you tell me your stack (e.g. Microsoft 365 + Salesforce + Snowflake + Slack), I can compare Glean vs. Microsoft Copilot vs. a data/BI-native approach and tell you which I'd pick.

To let executives ask natural-language questions across every department (sales, HR, engineering, finance) without building custom dashboards or wrangling BI tools, you need an AI-powered enterprise search and knowledge discovery platform . These tools use Retrieval-Augmented Generation (RAG) to read unstructured documents, wikis, chats, and structured records, returning direct, cited answers rather than a list of links.

Top company intelligence platforms suited for this requirement include:

• Glean : Widely considered a gold standard for enterprise work AI, Glean connects over 100 enterprise apps (Slack, Google Workspace, Salesforce, Jira, Confluence, etc.). It builds a deep "Enterprise Graph" of your company's people, projects, and documents, allowing executives to ask complex cross-departmental questions while strictly respecting role-based permissions.
• Guru : Focuses heavily on verified, permission-aware enterprise AI search. It features knowledge agents that can reason across internal silos and deliver trusted answers directly inside the workflow or chat tools your team already uses (like Slack or Teams).
• GoSearch : Built for mid-market to enterprise organizations, it bridges 100+ integrations using a hybrid indexed and federated architecture. Its GoAI assistant provides direct, cited natural-language answers and requires minimal IT setup compared to legacy infrastructure.
• Moveworks : An conversational AI copilot and enterprise search engine that excels at interpreting executive intent, searching unstructured repositories, and securely pulling answers or triggering actions across disparate business systems.
• Dust : A modular multiplayer AI platform that lets companies build custom organizational agents and semantic layers over their internal data silos (Engineering, Sales, HR, Analytics) with tight permission controls.

To help narrow down which platform fits your tech stack, could you share:

• What primary collaboration and CRM tools your company uses (e.g., Microsoft 365, Google Workspace, Salesforce, Slack)?
• Do you have strict on-premise data residency requirements , or is a cloud-native SaaS platform acceptable?