Dust vs Langflow (2026): Pricing, Features & Verdict
Dust and Langflow both score 6.9/10 on our AI Software criteria. Both Dust and Langflow have a free plan.
Last updated: November 2026
Dust
6.9/10
Dust is a Paris-founded platform where companies build custom AI agents that work on their internal data across tools like Slack, Notion and GitHub.
Langflow
6.9/10
Langflow is an open-source, Python-based visual builder that developers use to create, test and deploy AI agents, RAG pipelines and MCP servers as APIs.
Feature-by-Feature Comparison
| Feature | | |
|---|---|---|
| Scores | ||
| Overall Rating | 6.9/10 | 6.9/10 |
| Integration | 7/10 | 8/10 |
| Analytics | 6/10 | 5/10 |
| Customization | 8/10 | 9/10 |
| Ease of Use | 7/10 | 7/10 |
| Support | 6/10 | 5/10 |
| Cost | 6/10 | 9/10 |
| Scalability | 7/10 | 5/10 |
| Security | 8/10 | 4/10 |
| Output Quality | 7/10 | 6/10 |
| Pricing | ||
| Free plan | Yes | Yes |
| Cheapest paid plan | €30/user/mo Business - Pro seat | Contact for pricing |
| Estimated cost for 10 users | €300/mo Business - Pro seat | Free Langflow OSS (self-hosted) |
| Features | ||
| AI Agents | ||
| API Access | ||
| Chatbots | ||
| Enterprise Controls | ||
| Knowledge Base Search | ||
| Private Deployment | ||
| Workflow Automation | ||
| Text Generation | Not listed | |
Dust vs Langflow cost by team size
| Team size | Dust | Langflow |
|---|---|---|
| 1 user | €30/moBusiness - Pro seat | FreeLangflow OSS (self-hosted) |
| 5 users | €150/moBusiness - Pro seat | FreeLangflow OSS (self-hosted) |
| 10 users | €300/moBusiness - Pro seat | FreeLangflow OSS (self-hosted) |
| 25 users | €750/moBusiness - Pro seat | FreeLangflow OSS (self-hosted) |
| 50 users | €1,500/moBusiness - Pro seat | FreeLangflow OSS (self-hosted) |
The plan that fits each team size, billed monthly, before add-ons and usage charges. Each cost opens that tool's pricing calculator for the team size.
Who Dust and Langflow suit
Dust fits small business and enterprise better; Langflow fits developers better.
| Audience | Dust | Langflow |
|---|---|---|
| Developers | 5/10A GitHub connector, API access and MCP servers support engineering use. | 9/10It is Python-based and open source, with editable component code, a REST API, MCP server and client support, and pip, Docker and Desktop installs. |
| Small Business | 7/10Per-seat pricing, a free seat and a Business plan for teams up to 100 suit smaller companies. | 4/10Without a managed hosted service and with AI concepts such as embeddings to learn, non-technical small firms will struggle. |
| Enterprise | 8/10Enterprise adds SCIM, audit logs, single-tenant deployment and a dedicated CSM, and Datadog and 1Password are named customers. | 6/10IBM sells SLA-backed support, and version 1.13 adds audit logging and user, team and role management, but the company must self-host and patch it. |
| IT Teams | 5/10Inherited permissions, SCIM, audit logs and single-tenant deployment help IT govern it. | 6/10IT teams can run it on their own infrastructure with OpenTelemetry monitoring, but they carry the hardening and upgrade work. |
| Startups | 7/10Free seats and monthly per-seat billing make it easy to start, though connector limits apply. | 8/10There is no license fee, and a basic RAG prototype can be built in minutes, so it suits teams with engineers but a small budget. |
| Agencies | Not rated | 7/10An independent reviewer used it for client agent projects and reported much faster delivery than hand-coding. |
| Customer Support Teams | 5/10Agents can answer from internal knowledge drawn from connected tools. | Not rated |
| Freelancers | 3/10It is built as a shared company workspace, although a free seat exists. | Not rated |
| Mid-Market | 9/10The Business plan targets teams of up to 100 people and includes SSO, and named customers include fast-growing companies such as Qonto and PayFit. | Not rated |
| Remote Teams | 6/10Agents work inside Slack and Notion, the shared tools distributed teams rely on. | Not rated |
| Sales Teams | 6/10Dust connects to Salesforce and lets non-technical sales staff build agents. | Not rated |
Which One Should You Choose?
Why choose Dust
- Higher Security score (8/10 vs 4/10)
- Higher Scalability score (7/10 vs 5/10)
- Better fit for small business (7/10 vs 4/10)
- Better fit for enterprise (8/10 vs 6/10)
Why choose Langflow
- Higher Cost score (9/10 vs 6/10)
- Higher Integration score (8/10 vs 7/10)
- Better fit for developers (9/10 vs 5/10)
Pros & Cons
Dust
Pros
- Model-agnostic: more than 20 models from OpenAI, Anthropic, Google, Mistral and DeepSeek, with none locked behind a higher plan.
- Agents inherit permissions from connected sources, which reduces the risk of leaking data.
- SOC 2 Type II and a choice of US or EU data residency, with single-tenant deployment on Enterprise.
- G2 reviewers rate it highly, with 22 reviews averaging 4.9 out of 5, and say non-technical staff can build agents.
- Monthly seats can be cancelled anytime, and seat types can be changed per user.
Cons
- The Business plan is capped at 3 connectors, 5 MCP servers and 5 Spaces.
- Agent answers are only as good as the structure and freshness of the connected data.
- Its native integration catalogue is smaller than Microsoft Copilot's or Glean's, and some G2 reviewers ask for more integrations.
- Credits that run out need admin-approved overage, and unused credits do not roll over.
- Business customers get email support only.
Langflow
Pros
- The MIT license means no software fees and full source access. Teams can change any component in Python instead of being limited to the built-in nodes.
- Flows can be served as REST APIs or exposed as MCP servers, so agents built on the canvas plug straight into other apps and MCP clients.
- It includes ready-made RAG building blocks such as document loaders, chunking, embeddings and many vector store connectors. One review found a basic RAG pipeline took about 10 to 15 minutes, against 1 to 2 hours in LangChain code.
- Developers can test each component or flow on its own in the Playground before connecting it, which speeds up iteration.
- It is very popular open-source software, with about 156,000 GitHub stars, and is now backed by IBM, which sells SLA support.
Cons
- DataStax shut down its hosted Langflow on Astra on April 9, 2026, so production use usually means self-hosting and running it yourself.
- Its security record is weak. Two CVSS 9.8 flaws covering authentication bypass and code execution affected versions 1.0.0 to 1.12.8, and several older Langflow flaws are in CISA's Known Exploited Vulnerabilities catalog.
- Users report instability between versions and slow responses, with some flows taking 10 to 30 seconds or more, so pinning versions and testing upgrades is recommended.
- The canvas becomes hard to manage beyond roughly 20 to 30 nodes, and reviewers describe limited multi-agent orchestration.
- Reviewers say the documentation and error messages are thin, which makes debugging tedious.
Not sold on either?
Frequently Asked Questions
Dust and Langflow both score 6.9/10 on our AI Software criteria. The largest gap is in Security: 8/10 for Dust and 4/10 for Langflow.
Yes, both Dust and Langflow have a free plan.
Langflow is the better fit for developers: we rate it 9/10 for them, against 5/10 for Dust.
