Dust Alternatives 2026: 7 Enterprise AI Platforms Compared (Ranked)

Last updated May 2026

Dust (dust.tt) describes itself as an operating system for AI agents — a workspace-scoped platform that lets companies build, deploy, and govern AI assistants and agents across their organization. It has adopted the Model Context Protocol (MCP), positions on enterprise data connectivity, and targets the buyer who wants to give every team AI-powered workflows without losing control of what the AI can access. People searching for Dust alternatives in 2026 are typically looking for either a similar enterprise workspace platform with stronger governance, or a more specialized tool for their primary vertical (sales, HR, operations). This guide ranks the most-evaluated options.

Conflict of interest disclosure. This comparison is published on Knowlee.ai. Knowlee is included and reviewed below. Where Dust is the better choice — particularly for buyers who want a polished workspace-first AI platform for knowledge workers — we say so. Knowlee's positioning is different: cross-vertical brain plus AI Act-shaped governance for operators running agent fleets, not a team collaboration layer.

For the full landscape of enterprise agentic platforms, see agentic workforce platforms comparison 2026. For context on governance, see our AI orchestration glossary.

Methodology

Evaluation dimensions: workspace integration (how deeply the platform connects to existing knowledge bases, docs, Slack, email), agent governance (risk classification, human-oversight controls, audit logs, AI Act posture), cross-vertical scope (single-function vs. multi-vertical orchestration), EU deployment (legal entity, data residency, on-prem option), and deployment model (SaaS vs. self-hosted). We do not run live benchmarks — this is a vendor-comparison guide using public documentation and pricing pages as of May 2026.

Verdict: which alternative wins for which buyer

The 7 alternatives reviewed

1. Knowlee — cross-vertical agent OS with AI Act governance

Knowlee shares the "operating system for AI agents" framing with Dust but is architecturally different. Dust focuses on workspace-scoped AI for knowledge workers — giving teams AI assistants that know your docs, your Slack, your Notion. Knowlee focuses on running agent fleets across multiple business verticals — sales automation, talent acquisition, content intelligence, legal review — with a Neo4j Brain that accumulates shared memory across all agents and all runs.

The governance story is where Knowlee most directly differentiates. Every job in Knowlee's registry carries risk_level, data_categories, human_oversight_required, approved_by, and approved_at as first-class fields. This is not a compliance dashboard layered on top — it is the data model. The audit layer surfaces any unapproved run of a human-oversight-required job. For enterprises that need to file an AI Act conformity assessment in 2026, this structure is a meaningful head start.

Strengths. AI Act-shaped governance as a first-class data model. Neo4j Brain for cross-run, cross-vertical memory compounding. EU-deployable (Hetzner, on-prem). Single kanban board across all agent workloads. MCP fabric for scraping, search, and database access.

Trade-offs. Not a knowledge-worker workspace platform — does not replace Notion, Confluence, or Slack as the collaboration layer. Heavier operator overhead than Dust for teams that want one AI assistant, not a fleet. Pricing on request.

Pricing. On request. Indicative annual engagements from low-five-figure euro range.

See agentic OS glossary for conceptual framing.

2. Sana (Workday) — HR-led AI for people operations

Sana (sana.ai), acquired by Workday in 2024, is an AI platform for learning, knowledge management, and HR-adjacent workflows. It integrates with Workday data natively, which is its primary strength. For enterprises standardized on Workday HCM, Sana offers the lowest-friction AI layer for people operations. It is not a general-purpose agent platform — it is a specialized HR and learning intelligence product.

Strengths. Native Workday data integration. Strong L&D and onboarding use cases. HR-specific AI features (skills gap analysis, learning path generation). Enterprise SaaS with SSO and role-based access.

Trade-offs. Not a multi-vertical agent platform. No fleet orchestration layer. Governance metadata is HR-scoped, not general AI Act governance. Requires Workday HCM investment to unlock full value.

Pricing. Enterprise pricing, contact for quote. (sana.ai/contact)

3. Glean — enterprise search with an AI layer

Glean (glean.com) is an enterprise search and AI assistant platform: it indexes all your company's data sources (Google Drive, Confluence, Salesforce, Jira, Slack, 100+ connectors) and provides a unified search and conversational AI interface. It added "Glean Agents" for workflow automation on top of the search foundation. For enterprises whose primary pain is knowledge fragmentation — the right info trapped in ten siloed tools — Glean is the most practical answer.

Strengths. Broadest connector library for enterprise knowledge sources (100+ integrations). Mature permission-aware search. Strong enterprise security posture (SOC 2 Type II, GDPR compliance). Glean Agents for workflow automation built on the same knowledge layer.

Trade-offs. Not a general-purpose agent runtime — agents are constrained to the Glean knowledge layer. No fleet orchestration view. Governance is access-control-centric (who can see what) rather than AI Act-shaped (risk classification, oversight metadata). Primarily US-hosted; EU data residency options available for Enterprise.

Pricing. Enterprise pricing, contact Glean sales. (glean.com/pricing)

4. Microsoft Copilot Studio + Agent Framework

Microsoft Copilot Studio (microsoft.com/copilot-studio) is the Microsoft low-code platform for building AI agents and copilots that run within the Microsoft 365 ecosystem. It now includes the Copilot Agent Framework for orchestrating multiple agents. For buyers already on Microsoft 365 / Teams / Azure, it is the path of least resistance: agents that operate inside Outlook, Teams, SharePoint, and Dynamics with SSO and governance inherited from the M365 tenant.

Strengths. Native M365 and Azure integration. Low-code builder — accessible to IT generalists. Enterprise governance via M365 admin center and Azure policy. Good fit for regulated industries that are already Microsoft shops.

Trade-offs. Locked to the Microsoft ecosystem — not the right choice for Google Workspace or multi-cloud buyers. Agent customization is constrained by the studio model. No standalone deployment outside Microsoft infrastructure. Pricing tied to M365 licensing.

Pricing. Copilot Studio: from $200/month per tenant (25 users). Copilot for M365: $30/user/month add-on. (microsoft.com/copilot-studio/pricing)

5. Salesforce Agentforce — CRM-native agent platform

Salesforce Agentforce (salesforce.com/agentforce) is Salesforce's agentic platform built on top of Salesforce Data Cloud and the Einstein AI layer. Agents operate on Salesforce CRM data natively — accounts, contacts, opportunities, cases, service records — and are configured via Salesforce flows and Apex. For buyers whose data gravity is in Salesforce, Agentforce is the lowest-friction path to AI agents for sales, service, and marketing.

Strengths. Native Salesforce data access — no ETL required. Agents inherit Salesforce's RBAC and permission model. Pre-built agent templates for sales, service, and marketing. Einstein Trust Layer for data governance. Large Salesforce SI ecosystem.

Trade-offs. Requires existing Salesforce investment to unlock value. Agents operate on Salesforce data — limited cross-vertical reach outside the Salesforce ecosystem. Governance is Salesforce-scoped, not general AI Act classification. Complex licensing.

Pricing. Agentforce: $2/conversation (consumption-based). Requires Salesforce base licenses. (salesforce.com/agentforce/pricing)

6. Lindy — lightweight no-code agent builder

Lindy (lindy.ai) is the fastest no-code path to a working AI agent: visual builder, template marketplace, integration with common business apps. It is the right tool for a small team that wants one or two AI assistants running without involving engineering. It does not compete with Dust at the enterprise governance level — it is a lighter tier.

Strengths. Genuinely fast onboarding (minutes to first agent). Wide template library. Good integrations (email, calendar, Notion, Slack, CRM). Free tier available. No engineering required.

Trade-offs. No fleet orchestration. No cross-agent shared memory. No governance metadata beyond basic logging. SaaS-only (no self-hosted option). Not designed for regulated enterprise deployments.

Pricing. Free tier (limited tasks). Pro: from $49/month. (lindy.ai/pricing)

7. Relevance AI — no-code agent workforce builder

Relevance AI (relevanceai.com) positions as a "no-code AI workforce" platform: build AI agents (tools + skills + prompts) and deploy them as a team. It sits between Lindy (individual agents) and Knowlee/Dust (enterprise fleet platforms) in terms of sophistication. A growing library of pre-built agent templates for sales, support, and ops makes it practical for business teams without engineering resources.

Strengths. No-code agent builder with tool and skill primitives. Agent team concept (multiple agents with defined handoffs). Growing template library. Integrations with CRM, email, and data sources. Free tier.

Trade-offs. No AI Act-shaped governance metadata. No cross-run compounding memory (Brain equivalent). Cloud-only; EU data residency not prominently documented. Governance is access-control-centric, not risk-classification-centric.

Pricing. Free tier (100 credits/month). Team: from $199/month. Business and Enterprise: on request. (relevanceai.com/pricing)

Comparison matrix

FAQ

Is Dust open-source? Dust (dust.tt) is open-source — the core is available on GitHub. It also offers a managed cloud service and enterprise contracts with EU data residency. If self-hosting is a requirement, Dust is one of the few workspace AI platforms where this is a documented option.

What is the best Dust alternative for EU-regulated enterprises? Knowlee (EU legal entity, deployable on Hetzner or on-prem, AI Act-shaped governance) or Dust itself (EU entity, self-hostable). Microsoft Copilot Studio has EU data residency via Azure but requires M365 investment. Glean's EU data residency is available on Enterprise plans.

Which platform is closest to Dust in product philosophy? Glean is the closest in "enterprise knowledge + agents" terms — both focus on connecting to existing company data sources and building AI on top. The difference is that Glean comes from a search-first architecture while Dust comes from an agent-first architecture.

Does Knowlee replace a platform like Glean or Dust for knowledge management? No. Knowlee does not replace your knowledge base, search, or collaboration layer. It runs agent fleets against your data. For teams whose primary need is "AI that knows our docs," Glean or Dust are the right tools. For teams whose primary need is "AI agents running sales, hiring, and content pipelines with audit trails," Knowlee is the right tool.

What is MCP and why does Dust adopt it? MCP (Model Context Protocol) is an open standard for connecting AI agents to external data sources and tools. Dust's MCP adoption means its agents can use the same connection layer as other MCP-compatible platforms, including Knowlee. See AI orchestration glossary for more.

Next steps

If the decision is workspace AI for knowledge workers, evaluate Dust, Glean, or Sana based on your existing tool stack. If the decision is a governance-grade multi-vertical agent OS, read agentic workforce platforms comparison 2026 and best AI agent platforms 2026 before shortlisting Knowlee.