Top knowledge management tools for AI chatbots & agents [2025 Review]

Looking for the best knowledge management tools to power AI chatbots and agent workflows? This guide breaks down the top platforms for unified search, smart wikis, and instant answers, so your team can get clarity on the best pick for your use case(s).

Inside, you’ll find an up-to-date comparison of Notion, Gumloop, Slab, and Glean, including strengths, drawbacks, pricing, and data-backed insights you won’t get from generic reviews. You’ll also see non-obvious factors that make or break real-world adoption, straight from user feedback and industry data.

Here’s the TL;DR 👇

Non-obvious things to look for in a knowledge management tool

Factor 1: How invisible is the friction to add and update knowledge?

AKM tools often sound great, but teams complain about forgotten, outdated documentation.

One Redditor notes, "We ended up with stale wikis because it was just too clunky to edit." Choose a platform where adding or editing info feels as easy as messaging.

Too much structure can kill contributions:

• Seek inline editing and easy “add new” buttons.
• Check if mobile and browser clipper extensions are rated highly by users.
• Look for integrations with existing workflows (Slack, Gmail) to lower barriers.

Factor 2: Does the tool surface forgotten or buried content, or does it let knowledge rot?

Many solutions promise powerful search, but few proactively highlight old yet valuable insights.

As one G2 user puts it, “No point in storing gold if nobody sees it.” Prefer platforms that:

• Use intelligent recommendations to resurface relevant docs.
• Offer alerts for outdated or low-read content.
• Allow auto-suggestions to keep teams aware of what exists.

Factor 3: What’s the real-world context switching cost?

Even if technically integrated, switching apps kills flow. Multiple YouTube reviews warn, “I spend more time toggling than actually reading.”

Assess:

• Presence of in-context pop-ups, tooltips, or AI chat that pulls answers without leaving your current app.
• Quick preview capabilities in chat or tickets.
• Real user reviews on context switching pain: “With Notion, I finally stopped losing my place every time I need an answer.”

💡 Honorable mentions: Audit logs for compliance, robust permission structures, and customizable analytics frequently come up as bonus deal-makers.

The best knowledge management tools in 2025

Notion

Public reviews: 4.7 ⭐ (G2, Capterra average)

Our rating: 9/10 ⭐

Similar to: Coda, Confluence

Typical users: Product teams, startups, agencies, creators

Known for: All-in-one workspace for note-taking, docs, and collaboration

Why choose it? Offers unmatched flexibility and customization for organizing knowledge and workflows

What is Notion?

Notion is a flexible workspace to model knowledge and workflows with linked docs, wikis, and databases.

Build specs, SOPs, and roadmaps; switch views (table, board, calendar); enforce permissions; embed anything; connect via API; accelerate with Notion AI.

Why is Notion a top knowledge management tool?

Docs, wikis, and linked databases in one place.

Switch table, board, calendar views, set page permissions, embed sources, connect via API, and use Notion AI to summarize and keep knowledge current.

Notion's top features

• Docs and wikis: Create hierarchical pages with a block-based editor (text, headings, lists, toggles, code, callouts) and nest subpages to structure internal wikis and reference hubs.

• Databases with flexible views: Model knowledge as relational databases with properties (text, select, multi-select, date, people, files) and switch between table, board, calendar, timeline, gallery, or list views; filter, sort, group, relate databases, and compute rollups and formulas.
• Linked databases and references: Insert linked database views across pages to reuse the same data with different filters and views; create inline page links, @mentions, and backlinks to connect topics and surface related content.
• Permissions and sharing controls: Set workspace, group, guest, page, and database-level access (view, comment, edit), lock pages to prevent edits, and share public links for read-only access when needed.
• Notion AI: Ask questions across workspace content (Q&A), generate page summaries, rewrite or translate text, extract action items, and autofill database properties using page and database context.

💡 Summary: Notion provides a wiki editor, relational databases with multi-view displays, cross-page linking and search, granular access controls, and workspace-aware AI to structure, reference, and query organizational knowledge.

Pros and cons of Notion

Pros: Why do people pick Notion over other knowledge management tools?

✅ Unified wiki + relational databases

Link pages to DB items, use relations/rollups, and switch table/board/calendar without duplicating content.

✅ Reusable linked views per audience

Surface the same DB with scoped filters and properties for product, support, or execs—no new tables.

✅ Workspace-aware Notion AI

Q&A over docs/DBs, page summaries, and property autofill keep knowledge current with less manual work.

Cons: What do people dislike about Notion?

❌ Performance at scale

Large, filtered linked views lag and stall pages, especially in big workspaces.

❌ Permissions and governance gaps

No field/block-level permissions or approval workflows; limited audit logs for compliance.

❌ Lossy export and migration

Exports drop relations, comments, and history; moving data via API rarely preserves structure.

Is there data to back Notion as the best knowledge management tool?

Pricing: How much does Notion really cost?

Notion uses a freemium, seat-based model with discounted annual billing and an optional AI add‑on priced per member.

Choose between these 4 plans (plus an AI add‑on):

• Free - $0, for individuals and light collaboration; includes core docs and wikis with basic sharing limits.
• Plus - $10 per user/month billed annually ($12 monthly), for small teams; includes unlimited file uploads, collaborative workspaces, and page history.
• Business - $18 per user/month billed annually ($20 monthly), for growing teams; includes advanced permissions, private teamspaces, longer page history, and admin controls.
• Enterprise - Custom pricing, for large organizations; includes enterprise security, unlimited page history, audit logs, and enterprise user provisioning.
• Notion AI add-on - $10 per member/month, adds Q&A across workspace content, summaries, rewriting/translation, and property autofill in databases.

Price limitations & potential surprises

Seats are billed for every member in a workspace, so costs rise as you add collaborators; the AI add‑on is charged per person you enable it for.

--> Some governance features (like unlimited version history, audit logs, and enterprise-grade identity management) require higher tiers, which can force an upgrade as security needs grow.

Gumloop

Public reviews: 4.6 ⭐ (G2, Capterra average)

Our rating: 8.2/10 ⭐

Similar to: Guru, Notion

Typical users: Support, operations, and customer success teams

Known for: AI-powered knowledge base with ultra-fast search and smart automations

Why choose it? Excellent for teams needing real-time knowledge retrieval and seamless AI integrations.

What is Gumloop?

Gumloop is an AI knowledge base for support, ops, and CS teams. It indexes docs, tickets, and wikis, delivers instant answers via semantic search, and runs automations. Plug it into chatbots and agents for real-time, source-backed replies.

Why is Gumloop a top knowledge management tool?

It indexes docs, tickets, and wikis, returns sourced answers fast, and triggers actions.

--> Plug into chatbots or agents to cut handle time and keep responses current.

Gumloop's top features

• Unified indexing across docs, tickets, and wikis: Connects to knowledge sources and continuously ingests and normalizes content into a single searchable index.
• Semantic search and instant answers: Retrieves relevant passages with vector-based search and returns concise, conversational answers to queries.
• Source-backed responses: Attaches citations and links to original documents so each answer includes its supporting sources.
• Automations and action triggers: Executes predefined workflows or triggers actions based on queries, intents, or events.
• Chatbot and agent integrations: Exposes APIs/SDKs to embed real-time, source-backed answers in chatbots and agent assist interfaces.

💡 Gumloop centralizes knowledge from docs, tickets, and wikis, retrieves cited answers with semantic search, runs automations from queries, and integrates directly into chatbots and agent tools.

Pros and cons of Gumloop

Pros: Why do people pick Gumloop over other knowledge management tools?

✅ Unified indexing across tickets, docs, and wikis

Continuous sync normalizes disparate systems into a single, fast semantic index.

✅ Source-backed answers for agent assist and bots

Every reply includes citations and links, reducing hallucinations and compliance risk.

✅ Automations triggered by queries and intents

Route tickets, update CRMs, or run workflows directly from knowledge searches.

Cons: What do people dislike about Gumloop?

❌ Connector breadth and depth

Fewer native connectors and shallow field mapping mean partial coverage for niche tools and custom schemas.

❌ Automation flexibility

Complex, multi-step workflows often need custom code or external orchestration beyond built-in triggers.

❌ Permissions and governance

ACL sync across sources can be brittle, making least-privilege, audit-ready setups harder than in Guru/Confluence.

Is there data to back Gumloop as the best knowledge management tool?

Pricing: How much does Gumloop really cost?

Gumloop uses a freemium, credit-based model with seat and feature tiers, offering discounted annual billing (20% off) when paid yearly.

Choose between these 4 plans (credit tiers + feature-based):

• Free – $0, includes 2 000 credits/month, 1 seat, 1 active trigger, 2 concurrent runs; includes Gummie Agent, forum support, unlimited nodes & flows.
• Solo – $37 / month (billed monthly; annual not explicitly priced but includes 20% off), includes 10 000+ credits/month; adds unlimited triggers, 4 concurrent runs, webhooks, email support, and the ability to bring your own API key.
• Team – $244 / month, includes 60 000+ credits/month; includes everything in Solo plus 10 seats, 5 concurrent runs, unlimited workspaces, unified billing, dedicated Slack support, and team usage & analytics.
• Enterprise – Custom pricing, for large organizations; includes all Team features plus role-based access control, SCIM/SAML support, admin dashboard, audit logs, custom data retention rules, regular security reports, data exports, incognito mode, AI model access control, and Virtual Private Cloud.

Price limitations & potential surprises

• Workflows consume credits. AI, scraping, enrichment, and flow executions all use credits, and consumption can scale quickly.
• Overage is possible (up to twice your plan’s credits); excess credits cost $0.005 each.
• Bringing your own API key for AI models drastically reduces credit costs for those nodes, from around ~20 credits per call with Gumloop's key to just 1 credit if you bring your own.

Glean

Public reviews: 4.7 ⭐ (G2, Capterra)

Our rating: 9/10 ⭐

Similar to: Guru, Confluence

Typical users: Enterprise teams, especially in fast-scaling tech and knowledge-driven organizations

Known for: Unified AI-powered search across company apps and documents

Why choose it? Delivers fast, personalized answers from across your entire company knowledge base

What is Glean?

Glean is an AI-powered search and answer engine that connects to Google Drive, Slack, Jira, Confluence, and more to unify knowledge and surface permission-aware, personalized answers. Cuts switching between apps for fast-scaling teams and powers AI chatbots.

Why is Glean a top knowledge management tool?

Connects to Drive, Slack, Jira, and Confluence to give personalized, permission-aware answers fast. Cuts app switching and powers AI chat with current, trusted docs.

Glean's top features

• Unified, permission-aware search: Indexes content across Google Workspace, Microsoft 365, Slack, Confluence, Jira, Salesforce, and other connected apps; runs queries that respect source-system permissions and user/file access.
• AI answers with citations: Uses generative AI over indexed content to return direct answers to natural-language questions, with inline citations and links back to original documents, tickets, and messages.
• People and expertise search: Surfaces people profiles, team context, and inferred expertise from documents and activity; lets users locate owners, subject-matter experts, and related teams.
• Workplace assistants and extensions: Provides a Slack bot, browser extension, and in-app side panel to search or ask questions from within existing tools; returns results and answer snippets with source links in place.
• Admin controls and analytics: Offers an admin console to manage connectors, indexing scope, and access controls; includes usage and search analytics to monitor queries, adoption, and content coverage.

💡 Summary: Glean delivers permission-aware enterprise search, generative answers with citations, people/expertise discovery, in-workflow assistants, and admin analytics for managing company knowledge.

Pros and cons of Glean

Pros: why do people pick Glean over other knowledge management tools?

✅ Permission-aware, cross-app search

Indexes without migration and preserves source ACLs across Google, Microsoft, Slack, Jira, Confluence, Salesforce.

✅ Grounded AI answers with citations

Returns permission-scoped answers with inline citations and deep links back to the exact doc, ticket, or message.

✅ People and expertise graph

Infers owners/SMEs from activity to route questions faster and reduce tribal-knowledge bottlenecks.

Cons: What do people dislike about Glean?

❌ Not a system of record

Search-first; lacks robust wiki-style authoring, review, and governance workflows.

❌ Limited relevance tuning

Few admin controls to boost sources, define synonyms, or pin results; manual curation needed.

❌ Total cost of ownership

Per-seat pricing and connector limits add up fast for org-wide deployments.

Is there data to back Glean as the best knowledge management tool?

Pricing: How much does Glean really cost?

Glean uses quote-based, per-seat enterprise pricing with add-ons for connectors and usage; it does not publish prices on its site.

Price limitations & potential surprises

Pricing is seat-based with limits by connectors, data sources, and allowances, so costs can rise as you add users, apps, and advanced AI features.

Expect minimum seat commitments and possible implementation or overage fees that increase the total cost.

Pinecone

Public reviews: 4.7 ⭐ (G2, Capterra average)

Our rating: 8.5/10 ⭐

Similar to: Weaviate, Milvus

Typical users: Developers, data scientists, enterprise teams building AI and search applications

Known for: Vector database and similarity search for AI-powered applications

Why choose it? Exceptional scalability and speed for semantic search and real-time recommendations

What is Pinecone?

Pinecone is a managed vector database for semantic search and RAG. It stores embeddings, supports real-time upserts, metadata filtering, and scalable, low-latency queries so chatbots and agents retrieve relevant knowledge fast across large corpora.

Why is Pinecone a top knowledge management tool?

Real-time sync, meaning-based search, and metadata filters let chatbots find precise answers fast at any scale, keeping knowledge fresh, accurate, and responsive across large content sets.

Pinecone's top features

• Vector indexing and similarity search: Store high‑dimensional embeddings and run top‑k nearest‑neighbor queries using cosine, dot‑product, or Euclidean distance across large indexes.
• Real-time upserts, updates, and deletes: Ingest new vectors, modify vectors or metadata, and remove items via upsert, update, and delete APIs with low write‑to‑read latency.
• Metadata filtering and namespaces: Attach structured fields to vectors and apply boolean logic and numeric comparisons at query time; segment datasets or tenants using namespaces.
• Hybrid dense + sparse search: Index dense embeddings alongside sparse representations and issue hybrid queries that combine semantic and keyword signals with adjustable weighting.
• SDKs and RAG framework integrations: Use official Python and JavaScript clients and plug into popular RAG toolchains like LangChain, LlamaIndex, and Haystack via maintained integrations and examples.

💡 Summary: Pinecone provides vector indexing, real-time writes, metadata filtering, hybrid dense+sparse querying, and developer integrations for building retrieval over organizational knowledge.

Pros and cons of Pinecone

Pros: why do people pick Pinecone over other knowledge management tools?

✅ Low-latency at scale

Managed vector infra delivers low p95 latency across large, multi-tenant corpora.

✅ Real-time freshness

Low write-to-read latency keeps KB updates searchable in seconds, not hours.

✅ Policy-aware retrieval

Metadata filters and namespaces enable tenant isolation and role-based scoping at query time.

Cons: What do people dislike about Pinecone?

❌ Pricing at scale

Usage-based costs spike with vector counts, dimensions, and QPS—hard to forecast at enterprise scale.

❌ No self-hosting

No self-hosted option; vendor lock-in can block strict data residency or on‑prem requirements.

❌ Limited KM features

No native facets, relevance analytics, or synonym/typo tooling—needs extra systems to match KM UX.

Is there data to back Pinecone as the best knowledge management tool?

Pricing: how much does Pinecone really cost?

Pinecone uses usage-based serverless pricing that bills for vector storage and request units, with dedicated and enterprise options for reserved capacity and controls.

Choose between these 3 plans:

• Starter - pay as you go, billed for vector storage (GB-month) and request units for reads and writes; fully managed, autoscaling, and multi-tenant with per-region rates on the pricing page.
• Standard - $50/month minimum usage after, single-tenant capacity with reserved pods for predictable performance plus private networking and region choice.
• Enterprise - $500/month minimum usage after, enterprise security and compliance, SSO, advanced governance, higher SLAs, and priority support.

Price limitations & potential surprises

Costs scale directly with storage size, embedding dimensions, and query/write volume, so spend can rise quickly as usage grows if you don’t monitor request units.

Dedicated involves reserved capacity and longer commitments typical of single-tenant clusters, while some controls and SLAs are only available on Enterprise.

Slab

Public reviews: 4.7 ⭐ (G2, Capterra average)

Our rating: 8.5/10 ⭐

Similar to: Notion, Guru

Typical users: Product teams, engineering departments, fast-growing startups

Known for: Simple, intuitive wiki interface and strong search

Why choose it? Streamlined documentation and team knowledge sharing with minimal learning curve

What is Slab?

Slab is a team wiki for product and engineering teams. It pairs a clean editor with opinionated hierarchy, granular permissions, and fast, relevance-ranked search across content and integrations (Slack, GitHub, Drive). Ideal for lightweight docs and onboarding.

Why is Slab a top knowledge management tool?

Clean editor, clear structure, precise permissions, fast ranked search across Slack, GitHub, and Drive. Strong for onboarding and light docs.

Slab's top features

• Clean, fast editor: Compose and format docs with a minimal editor that supports rich text, Markdown-style shortcuts, slash commands, code blocks, tables, checklists, mentions, and reusable templates.
• Structured hierarchy and wiki linking: Organize content into nested topics and subtopics; create wiki-style links between pages for consistent navigation and cross-referencing.
• Relevance-ranked, unified search: Search across Slab and connected tools (Google Drive, GitHub, Slack), with ranked results that surface the most relevant pages and files.
• Granular permissions and access: Set view, comment, and edit permissions at the post or topic level; manage access for teams, groups, and guests; control external sharing.
• Integrations and embeds: Connect Slack, Google Drive, and GitHub to embed files and references, unfurl links, receive notifications, and search/share Slab content from Slack; import existing docs from tools like Confluence, Google Docs, or Notion.

💡 Summary: Slab focuses on authoring, structuring, finding, securing, and connecting knowledge via a clean editor, topic hierarchy, unified search, fine-grained permissions, and integrations with Slack, Google Drive, and GitHub.

Pros and cons of Slab

Pros: Why do people pick Slab over other knowledge management tools?

✅ Unified, ranked search across tools

Find answers across Slab, Slack, GitHub, and Drive with relevance that beats basic keyword search.

✅ Opinionated hierarchy that curbs sprawl

Nested topics and wiki links create predictable navigation and keep fast-growing docs coherent.

✅ Developer-friendly Slack/GitHub workflows

Unfurl, embed, and search from Slack; embed PRs and files so docs stay in sync with work.

Cons: What do people dislike about Slab?

❌ Rigid hierarchy

Lacks tags/knowledge graph and flexible taxonomies, making cross-cutting organization harder.

❌ Shallow integrations

Embeds/unfurls, but little two-way sync or automation versus Notion, Confluence, or Guru.

❌ Limited lifecycle governance

Sparse review/verification workflows and content health analytics, so pages can go stale.

Is there data to back Slab as the best knowledge management tool?

Pricing: How much does Slab really cost?

Slab prices are seat-based per month with a free tier for small teams and paid tiers for growing and enterprise needs;

Choose between these plans:

• Free - $0, core wiki for small teams to create and search docs.
• Startup - $8/mth, includes everything in Free plus more collaboration and integrations suited for growing teams.
• Business - $15/mth, includes advanced admin controls and security for larger organizations.
• Enterprise - custom pricing, includes enterprise-grade security, compliance, and premium support.

Price limitations & potential surprises

Seat-based pricing scales with headcount, and advanced security (like SSO/SCIM) is typically locked to higher tiers.

Limits on guests, verification workflows, or advanced analytics may require upgrading as usage grows.

💡 In short: expect per-seat costs to rise with team size and plan-gated security/governance features that may prompt an upgrade.

Why consider Big Sur AI for knowledge management and agent automation

Deliver personalized, conversion-optimized answers and recommendations in real time beyond what traditional knowledge bases, wikis, or unified search platforms can achieve.

1. Dynamic, on-brand conversational agents that drive outcomes
Big Sur AI's Web and Sales Agents go beyond static search or FAQ bots by guiding users to specific answers, product recommendations, and actions based on intent, real-time website context, and your business goals. They do this with conversion-optimized AI prompts and seamless hand-offs, improving both customer satisfaction and business KPIs (see AI Web Agent and AI Sales Agent).

2. Adaptive, conversion-focused knowledge delivery
Unlike generic wikis or chatbots, Big Sur AI incorporates adaptive quizzes, product recommendation engines, and tailored content journeys.

This means teams can surface helpful knowledge and the right offers in a customized flow based on user behavior, boosting lead capture and sales.

Review Adaptive AI Quiz, AI Content Marketer, and AI Product Recommendations.

3. Instant insights and optimization, not just knowledge storage
While most tools index knowledge for retrieval, Big Sur AI generates closed-loop analytics and merchant insights, allowing you to see exactly which answers, prompts, quizzes, and recommendations are driving conversions.

If you want knowledge management that directly connects content, conversation, and conversion, give Big Sur AI a try for free.

Which knowledge management tool is right for you?

• If you want maximum flexibility for building and organizing wikis, docs, and workflows, choose Notion.
• For the best plug-and-play, real-time, source-cited answers in agent and chatbot workflows, go with Gumloop.
• If unified, permission-aware search across all your company’s apps (with instant AI answers and minimal context switching) matters most, Glean is your pick.
• Prefer a clean, no-frills wiki that makes structured docs and team onboarding simple? Slab is the way to go.
• For teams that need lightning-fast, scalable semantic search or RAG infrastructure for custom AI assistants, Pinecone is ideal.

Ready to see what instant, AI-powered answers can do for your team? Give Big Sur AI a try here.