Comparison

BeforeQuery vs Guru

Guru is an internal knowledge management platform where teams author and verify knowledge cards. BeforeQuery ingests the sources you already have — docs, Slack, help desk, Drive, GitHub, and more — and answers questions for both your team and your customers via widget, API, and bots. This comparison is based on publicly available information.

Feature comparison

Information about Guru is based on their public website and documentation.

Feature
BeforeQuery
Guru
Product category
AI knowledge assistant — RAG answers over your existing sources for your team and your customers
Internal knowledge management / wiki with AI search for teams
Content model
Ingests sources you already have — docs sites, GitHub/GitLab, Notion, Confluence, Slack, help desks, Drive, files
Knowledge cards and pages authored in Guru, plus connected app search
Customer-facing answers
Yes — public web widget, REST API, SDKs, and support-form deflection for your users
Internal-first; built for employees
Website / docs crawling
Yes — sitemap and link discovery, incremental sync, HTML→markdown normalization
Sites can be added as sources for AI search
GitHub & GitLab repo indexing
Yes — READMEs, docs/, ADRs, changelogs. Git-push webhook for incremental sync. Self-hosted GitLab supported.
Not a core focus
Retrieval method
Hybrid: pgvector semantic + BM25 full-text, RRF fusion, LLM query rewrite, cross-encoder re-ranking
AI-powered enterprise search across cards and connected apps
Answer citations
Yes — every answer links to the exact source passages it was grounded in
Yes — answers reference source cards and documents
Slack bot
Yes — /askai slash command and @mention. Included on Pro and Enterprise.
Yes — Slack integration is a core Guru strength
Discord bot
Yes — slash command and @mention. Included on Pro and Enterprise.
Not documented
Web widget & SDKs
Yes — embeddable widget, @beforequery/react component, @beforequery/sdk for web, React Native, and Node
Browser extension and in-app knowledge for employees
MCP server
Yes — per-knowledge-base MCP endpoint (search_docs, ask_question, list_sources), client-key auth
Not documented
Content freshness
Scheduled source syncs keep the index current automatically; doc proposals draft updates from knowledge gaps
Verification workflows — experts periodically re-verify cards
Support ticket deflection
Yes — helpdesk integrations, form deflection endpoint with confidence scores, copilot drafts
Agent-assist for support teams
AI evals (groundedness, citation quality)
Yes — automated LLM-as-judge evals, scores exportable via API
Not documented
Pricing model
Public pricing. Free plan included. Scales with usage, not per-seat fees.
Public per-seat pricing

Where BeforeQuery focuses differently

No re-authoring — your existing sources are the knowledge base

Guru's model centers on knowledge cards your team writes and verifies inside Guru. BeforeQuery indexes what you already maintain — docs sites, GitHub repos, Notion, Confluence, Slack threads, resolved help desk tickets, Drive files — and keeps the index current with scheduled syncs. The docs stay where they live.

Answers for customers, not only employees

BeforeQuery ships a public 'Ask AI' widget, React component, SDKs, Slack and Discord bots, and a support-form deflection endpoint — so the same knowledge base answers your customers on your docs site and your team in Slack, each with the right permissions.

Developer-grade APIs and open protocols

An open REST API with streaming, public client keys for the browser, and a per-knowledge-base MCP server plus A2A endpoint mean your knowledge is queryable from AI IDEs, custom apps, and external agents — not just inside one product's UI.

Quality as a metric

Automated LLM-as-judge evals score groundedness and citation quality per knowledge base, gap analytics cluster unanswered questions, and doc proposals draft content to close gaps — your team reviews and accepts instead of writing from scratch.

Frequently asked questions

How is BeforeQuery different from Guru?

Guru is an internal wiki and knowledge management product: teams author knowledge cards in Guru, experts verify them, and employees search them. BeforeQuery ingests the sources you already have — docs sites, repos, wikis, Slack, help desks, Drive — and answers questions with citations for both your team (internal Ask assistant, Slack bot) and your customers (widget, API, bots).

Can BeforeQuery replace Guru for internal knowledge?

If your knowledge already lives in docs, Notion, Confluence, Google Drive, SharePoint, or repos, yes — BeforeQuery indexes those directly with per-knowledge-base permissions, restricted document visibility, and SSO. If your team prefers authoring and verifying knowledge inside a dedicated wiki product, Guru's card model may fit better.

Does BeforeQuery have something like Guru's verification workflows?

BeforeQuery approaches freshness differently: scheduled syncs keep the index matching the live sources automatically, gap analytics surface questions your content doesn't answer, and doc proposals draft new or updated documentation that your team reviews and accepts or dismisses.

Does BeforeQuery support the same integrations?

BeforeQuery ships a web widget, React component, JavaScript/Node SDK, Slack and Discord bots, an open REST API with WebSocket streaming, an MCP server per knowledge base, and helpdesk integrations for ticket deflection and copilot drafts.

Do answers include citations?

Yes. Every answer links to the exact source passages it was grounded in, and automated LLM-as-judge evals continuously score groundedness and citation quality.

Is my data used to train AI models?

No. Your connected content and your users' conversations are never used to train models. Content is indexed solely to answer questions for your knowledge base, and PII masking and retention controls are built in.

Is this comparison up to date?

The Guru column is based on publicly available information from their website and documentation. If you spot something outdated, contact us and we'll correct it.

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