Glean Alternatives: 12 AI Enterprise Search Platforms Compared (2026)

Over the past decade, companies have aggressively expanded their use of specialized SaaS applications, Glean being at the forefront of this having even hit $300 million ARR as on June 2026.
Essential corporate data is now scattered blindly across platforms such as Slack, Jira, Confluence, Salesforce, and Google Workspace.

Today’s Glean competitors cut through the noise, connect your scattered data with reliable permission syncing - but more importantly come at entry price point than is much lower than 60K annually.

To help you pick the right option, in this article we’ll cover the top Glean alternatives to look at.

What is Glean?

Glean is an enterprise search platform powered by artificial intelligence technology, which helps companies to retrieve information from various integrated applications, including Confluence, Slack, Salesforce, and Google Drive. Glean uses semantic search along with personalization for developing its knowledge base. Although Glean is effective within complex and data-intensive environments, it requires a lengthy deployment period (6 to12 weeks).

Why Look for a Glean Alternative in 2026?

Teams are moving beyond Glean for several reasons:

• Slow deployment: Glean's implementation can take months, while modern alternatives launch in days.
• Opaque pricing: Glean uses quote-based models with high seat minimums, making budgeting difficult.
• Limited automation: Glean focuses on retrieval, not action. Newer platforms like Thunai turn search into automated workflows.
• Rigid architecture: Glean’s cloud-only approach does not work well for businesses that require on-premises installations.
• Increased costs: As more AI capabilities are added to the software, Glean’s higher-end pricing is an issue for medium-sized businesses.

‍Glean Alternatives Compared

1. Thunai

If I had to pick one of the top Glean alternatives that serves as the operational heart of a modern enterprise, it would be Thunai.

Founded in 2025, Thunai is an advanced automation layer rather than just a conversational search engine.

That said, it comes with Thunai Brain (a complete AI knowledge base) that automatically detects and flags contradictions, as well as real-time agent assist that helps agents while they are on calls.

Its core philosophy asserts that search should merely be the precursor to autonomous action. Not to mention, Thunai is also ISO 42001 certified, as well as GDPR and SOC-II compliant.

Features:

1. Thunai Brain. This self-learning knowledge architecture continuously ingests unstructured company data, acting as a single, dynamic source of truth for its fleet of AI agents.
   
2. Thunai MCP: Connect with 50+ apps natively and any apps you want with it’s custom MCP layer for instant insight pulled from these tools like Jira, HubSpot, Google Docs, or any tool you keep for data.
   
3. Role-Based Access: Control which employees have access to sensitive information for compliance reasons and client sensitivity.
   
4. Autonomous Agentic Functions. What distinguishes Thunai is its execution capability. Agents can actively guide customers to resolutions using real-time screen sharing and autonomously update CRM systems with sentiment data and resolution logs.
   
5. Business Workflow Automation. The platform specifically targets high-friction departments like customer support, HR onboarding, and sales enablement, functioning to eliminate the cognitive load that causes "invisible agent burnout".

Pros:

• Provides true agentic functionality that eliminates manual data entry and executes multi-step workflows.
• Utilizes custom enterprise pricing targeted directly at driving ROI through operational cost reduction.
• Highly praised on G2 for its AI-driven call intelligence and multilingual support capabilities.

Cons:

• Relatively newer market entrant established in 2025

2. Coveo

Coveo is a highly established Canadian AI veteran with deep historical roots in both e-commerce product discovery and massive internal workplace knowledge management.

This Glean alternative is built on the premise that search must be dynamically tuned based on user behavior rather than static keywords.

Features:

• Behavioral AI and ART. Coveo uses advanced machine learning techniques to keep on learning from billions of interactions to provide dynamic navigation and Automatic Relevance Tuning (ART).
  
• Omnichannel Architecture. The Glean alternative platform is structurally divided into Commerce (for B2B/B2C) and Knowledge/Workplace offerings designed for sprawling employee intranets.
  
• Relevance Generative Answering. Coveo has modernized its stack with generative AI modules and Coveo for Agentforce, allowing it to generate synthesized conversational responses.

Pros:

• This rival of Glean offers amazing depth of native integration with Salesforce, allowing articles that are linked together to dramatically decrease case resolution times.
• Offers an advanced analytics solution with built-in dashboards and effortless data sharing using Snowflake.

Cons:

• Administrative staff always mention that the learning curve is very high and extremely difficult to navigate through the backend side.
• Creating a custom search experience can become too heavy on integration, when compared to modern solutions.

3. Guru

Guru approaches the enterprise search problem from a fundamentally different philosophical perspective: rigorous curation. 

Instead of attempting to index the entire, unfiltered digital footprint of a company, Guru is one of the Glean competitors that focuses on creating a tightly controlled, verified single source of truth.

Features:

• Proprietary Verification Engine. Guru allows organizations to designate subject matter experts who are periodically prompted to verify the accuracy of specific knowledge "cards".
• Embedded Workflow Integration. The platform brings verified knowledge directly into a user's operational context via highly refined browser extensions and native plugins for Slack and Microsoft Teams.
• AI Knowledge Agents. Guru utilizes private AI models with strict zero-data-retention policies, mathematically ensuring that proprietary corporate data is never used to train third-party LLMs.

Pros:

• The intense focus on verified information fosters high trust and eliminates the most common search failure mode: acting upon deprecated information.
• Offers transparent base pricing at $25/seat/month on its Predictable Plan.

Cons:

• Because it prioritizes documented knowledge over raw indexing, it can fail to surface the "deeper story" buried in casual Slack conversations or unverified email threads.
• Users report that search results can occasionally become slow or feel limited when handling exceptionally large volumes of unstructured data.

4. Elastic Enterprise Search

Built upon the robust Apache Lucene foundation, Elastic Enterprise Search provides a highly flexible engineering toolkit rather than a closed-box SaaS application.

This is one of the Glean competitors that is positioned almost exclusively for companies with large internal engineering teams.

Features:

• Hybrid Search Engine. Elastic combines traditional BM25 keyword scoring with advanced semantic vector search using its proprietary ELSER (Elastic Learned Sparse EncodeR) model.
• ES|QL (Elasticsearch Query Language). This technical leap brings real-time analytics, piping, and query flexibility similar to Splunk's SPL syntax to the platform.
• Limitless Scalability. It is arguably the most massively scalable solution available, officially capable of scaling to billions of vectors with options for fully managed serverless, cross-cloud, or strictly air-gapped on-premises deployments.

Pros:

• Adored by Information Security (InfoSec) professionals for its unparalleled ability to simultaneously function as an EDR tool, a SIEM system, and an enterprise search engine.
• Provides ultimate deployment flexibility and raw API power.

Cons:

• Highly unpredictable pricing based on Virtual Compute Units (VCUs) and data egress, causing costs to become difficult to forecast at scale.
• Features a punishingly steep learning curve requiring dedicated administrators just to keep the cluster optimized and healthy.

5. Microsoft Copilot + Graph Search

To companies that have used the Microsoft platform for some time now, Copilot is nothing short of revolutionary when it comes to conducting business.

The Microsoft Graph is what enables the use of generative AI in applications like Word, Excel, Teams, and Outlook.

Features:

• Microsoft Graph Context. The underlying web of mathematical relationships maps a user's emails, documents, and meetings to provide deeply personalized search parameters.
• Multimodal Content Generation. Copilot moves far beyond search; it can summarize Teams meetings, synthesize unread emails, and reference Excel files to autonomously build PowerPoint presentations.
• Frictionless Ecosystem Security. It requires virtually zero setup for M365 users, automatically inheriting the tenant's enterprise-grade security, sensitivity labels, and compliance boundaries.

Pros:

• Offers immense utility for daily administrative tasks, rapidly generating action items and presentations with light editing required.
• Enterprise IT architects value the deep governance capabilities provided by Azure AI Foundry and Copilot Studio.

Cons:

• Creates severe vendor lock-in to the Microsoft ecosystem.
• The high financial investment, universally set around $20 to $21 per user per month on top of existing M365 licenses, limits widespread deployment.

6. GoSearch

Developed by the team behind GoLinks (founded by Jorge Zamora), GoSearch has rapidly positioned itself as a highly aggressive, direct competitor to opaque legacy platforms.

It relies heavily on contrasting its radically transparent pricing against expensive legacy vendors.

Features:

• Hybrid Search Architecture. GoSearch mathematically blends indexed data for speed with federated search for real-time querying, perfectly balancing instant retrieval with strict security.
• Strict Permission Mirroring. The platform boasts robust RBAC and a "principle of least privilege" implementation, dynamically mirroring source permissions so users only see authorized data.
• No-Code AI Agents. The platform provides over 100 pre-built connectors and an intuitive no-code builder for creating custom AI agents capable of triggering external workflows.

Pros:

• Highly celebrated on Reddit for its transparent, cost-effective pricing: a Freemium tier, a $20/user/month Pro plan, and Enterprise plans starting at just $25/user/month.
• Offers massive time savings through instantaneous AI summaries and remarkably fast setup.

Cons:

• Power users note that advanced query filtering functionalities are still maturing compared to veteran platforms.

7. Workato

Workato is an enterprise AI control and execution plane rather than a simple integration tool.

This Glean alternative pushes past passive semantic search, using a governed Model Context Protocol to let Claude, ChatGPT, or custom-built agents safely execute an organization's proven business processes.

Features:

• Enterprise MCP Gateway. Transforms verified business processes into governed, agent-ready skills that any AI agent can execute safely, closing the shadow-AI and ungoverned API access gap.
• Agent Studio and Genies. A low-code environment for deploying policy-grounded autonomous agents that use patented, real-time OAuth 2.0 authorization to act strictly on behalf of verified individual users.
• Workato GO. Described by the company as enterprise search with Deep Action, letting users query across more than 10,000 enterprise applications and execute tasks directly from the search bar.

Pros:

• Easy-to-use and intuitive visual builder makes complex automations simple by converting them into clear flowcharts that can be created by non-technical business analysts.
• Comes with a wide variety of 14,000+ pre-built connectors for SaaS apps, on-premise applications, and legacy mainframes.

Cons:

• It may be costly and complex to adopt in smaller teams.

8. Onyx

Previously known as Danswer, Onyx is an open source software and provides solutions to the business requirement of total data sovereignty.

It targets highly regulated industries that require fully self-hosted search engines.

Features:

• Infrastructural Freedom. Onyx connects natively to over 40 workplace applications and allows organizations to plug in any public LLM or deploy entirely air-gapped, self-hosted models to guarantee zero data leakage.
• Strict Compliance. The architecture maintains strict document-level permissions inherited from origin systems like Slack and Google Workspace.
• Enterprise Edition Upgrades. The Enterprise tier adds critical features such as granular usage dashboards, white-labeling, region-specific deployments, and advanced SSO.

Pros:

• Offers great cost-effectiveness; one Reddit user observed that using Onyx on GCP for 100 to 200 users is just a small fraction of what Glean charges.
• Eliminates vendor lock-in while providing a clean UI, deep research tools, and manageable deployment.

Cons:

• Lacks the final layer of flawless enterprise polish found in commercial giants, with users reporting occasional AI "hallucinations".
• Core features like RBAC syncing are locked behind a proprietary paid subscription, sparking debate over its open-source purity.

9. Claude Cowork

Claude Cowork, developed by Anthropic, targets the local desktop rather than the cloud API layer, turning a user's own computer into a persistent, agentic workspace.

Positioned as a Glean alternative for individual knowledge workers rather than IT departments, Cowork is built to produce actual finished files instead of merely surfacing links to them.

Features:

• Sandboxed Execution Model. Tasks run inside an isolated Linux virtual machine on Anthropic's servers, letting Claude execute code and shell commands without exposing the user's local operating system.
  
• Content-Aware File Organization. Sorts hundreds of files by analyzing their actual semantic contents rather than filename or metadata, spinning up parallel sub-agents to synthesize research across many documents at once.
  
• Real Deliverable Generation. Produces working Excel spreadsheets with active formulas, formatted PowerPoint slides, and organized folder structures instead of text a user must copy and paste.

Pros:

• Built-in permission checks require explicit approval before permanently deleting local files, with adjustable Manual, Auto, and Skip trust modes.
• Highly accessible pricing, bundled directly into Anthropic's existing $20/month Pro subscription tier alongside Claude Code.
• System administrators note that VM sandboxing sharply limits the agent's blast radius compared to locally installed alternatives.

Cons:

• Currently limited to macOS, and the agent retains no memory between sessions outside of dedicated Projects.
• External connectors such as Gmail and Calendar remain unstable, and heavy parallelized tasks can quickly exhaust Pro plan usage limits.

10. ClickUp Enterprise AI Search (Formerly Qatalog)

Qatalog was recently acquired by project management giant ClickUp, Qatalog highlights the market trend of converging enterprise search directly into work execution platforms.

As a top Glean alternative, ClickUp Enterprise AI Search aims to eliminate work sprawl by blending search, asynchronous updates, and profiles into a unified UI.

Features:

• Brain MAX Technology. This proprietary technology allows users to search across disparate work apps and synthesize contextual answers using top-tier AI models.
• Talk to Text. Users can dictate natural language commands that the AI translates directly into queries and actionable workflow steps.
• Ambient Agents. Qatalog autonomously handles repetitive background busywork, ensuring team alignment and documentation occur asynchronously.

Pros:

• Users consistently praise its incredibly clean UI and its effectiveness in supporting globally distributed, asynchronous teams.
• Benefits from a massive ecosystem advantage, including a generous "Free Forever" tier tied to ClickUp's broader pricing.

Cons:

• Search functionality and future development are now inherently tied to the adoption of the broader ClickUp ecosystem.
• Historically suffered from occasional text formatting bugs.

11. Dust AI

Dust AI, a Paris-based platform backed by Sequoia, positions itself as a foundational operating system for scattered enterprise knowledge rather than a single search box.

This Glean competitor aggregates sources like Notion, Google Drive, Slack, and GitHub into a centralized, collaborative multiplayer agent environment built for Slack-native teams.

Features:

• Synthetic Filesystem Architecture. Maps disparate, unstructured data sources into a unified, Unix-inspired navigable structure, grounding custom agents strictly in a company's internal data.
• Dust Apps. Programmatic, deterministic actions, such as creating Jira issues or updating Salesforce records, that agents trigger directly from the semantic context of a conversation.
• Native Slack Integration. Agents can be invoked directly inside Slack channels, seamlessly inheriting a thread's conversational context without forcing users into a separate browser tab.

Pros:

• Holds a formidable 4.8 rating on G2, with the agent-builder interface praised for letting non-technical employees launch custom assistants without IT bottlenecks.
• Backend Temporal workflows process over 10 million activities daily, ensuring complex, multi-step information tasks execute reliably.
• The "Frames" feature makes it easy to format and present AI outputs, fostering a genuinely multiplayer collaborative environment.

12. Kore AI

Kore.ai operates at the extreme upper end of the enterprise spectrum, trusted by regulated giants like Morgan Stanley and Pfizer for mass-scale conversational deployments.

This top Glean alternative combines deterministic, scripted logic with generative reasoning through its proprietary, dual-brain XO Platform, engineered for absolute auditability at scale.

Features:

• Agent Blueprint Language (ABL). A compilable language that sets hard runtime constraints and compliance controls, keeping the AI within strict deterministic boundaries instead of relying on prompt-based guardrails alone.
• SearchAssist. A generative, RAG-based search engine offering faceted search, synonym recognition, typo tolerance, and global language support for querying massive enterprise databases conversationally.
• Agent-to-Agent (A2A) Protocol. Passes full conversational context and task history when handing work off between specialized agents, preventing users from having to repeat their issue.

Pros:

• Drag-and-drop visual builder successfully balances low-code accessibility with robust pro-code flexibility for experienced developers.
• Natural language understanding engine is highly regarded for parsing messy, colloquial user input rather than requiring precise keyword matching.
• Holds a strong 4.6 rating on G2, driven by its exceptional ability to handle enterprise scale and deflect support tickets.

Cons:

• Notoriously steep learning curve with a cluttered interface, and node management lacks a simple copy-paste function for refactoring dialog connections.
• Billing is based on unpredictable 15-minute session blocks, meaning extended troubleshooting chats can multiply costs significantly.

Buyer's Guide: Key Capabilities to Look for in Modern AI Enterprise Search

When evaluating Glean alternatives, prioritize these capabilities:

• Agentic automation: Can the platform act on insights, not just retrieve them?
• Deployment speed: Look for solutions that launch in days, not months.
• Pricing transparency: Avoid quote-based models with hidden costs.
• Integration depth: Ensure support for your core apps (CRM, helpdesk, communication tools).
• Knowledge unification: A single "brain" that connects all data sources reduces silos.
• Human-like AI: Natural, context-aware responses improve user trust and adoption.
• Security and compliance: SOC 2, GDPR, and ISO 27001 certifications are essential for enterprise use.

Using AI Tools in Steering the Future of Enterprise Search

The future of enterprise software will not be won by the companies that can ingest chaotic data, honor complex access permissions, and translate retrieved knowledge into accessible information

This is where Thunai stands apart in terms of top Glean alternatives.

Instead of adding a passive search interface, Thunai becomes the intelligence layer of your enterprise, unifying conversations and triggering real operational outcomes. 

• Contradiction Resolution Engine: Thunai scans your documents to catch contextual conflicts as they appear. It surfaces contradictions for human review instead of resolving them silently.
• Real-Time Agent Assist: Thunai listens live across voice, chat, and email to catch context in the moment. Co-Pilot Intelligence surfaces customer history instantly so agents have instant insight and never have to keep customers or clients waiting while on call.
• Thunai MCP: Thunai MCP connects out of the box with 50+ enterprise tools like CRMs and helpdesks. For anything unsupported, it builds custom connectors so no system gets left behind.
• AI Agents: Built in Thunai Common Agent, these no-code workflows come from drag-and-drop or AI prompts. They plug into Brain, MCP, Canvas, and WebSearch, with every action fully logged.
• Call Scoring Based on Your SOPs: Thunai scores every call against your own configurable parameters, not generic keywords. Dashboards and reporting turn those scores into a clear read on call quality.
• Thunai Safemind: Safemind manages sensitive data like payment info and delivery addresses within Thunai Brain. It enforces role-based access controls so only authorized personnel can view it.

Want to see true autonomous workflow execution in action? 

Schedule a free demo to see how Thunai unifies your enterprise today!

FAQs on Glean Alternatives

Why are organizations looking for Glean alternatives?

Enterprise architects are actively seeking Glean alternatives driven by the high, opaque total cost of ownership associated with legacy leaders. Additionally, organizations require transparent tiered pricing, on-premises options for data sovereignty, and autonomous AI agents that can execute multi-step workflows rather than just finding information.

What is the difference between indexed and federated enterprise search?

Indexed architectures pull and store all enterprise data into a centralized vector database for sub-second retrieval. Federated architectures query the source systems (like Slack or Salesforce) in real-time, ensuring absolute adherence to transient data residency and permission protocols.

How does AI enterprise search reduce operational costs?

By automating execution layers and unifying collective intelligence, glean alternatives like Thunai can facilitate massive decreases in operational costs (up to 35%) and deliver exceptional ROI by completely eliminating the manual data entry and repetitive ticket handling that cause agent burnout.