Sim vs Langflow
Sim is the open-source AI workspace where teams build, deploy, and manage AI agents visually, conversationally, or with code. Here is how Sim compares to Langflow on platform architecture, AI capabilities, integrations, pricing, security, and support. Every fact below is sourced and dated.
Sim is an open-source AI workspace for building, deploying, and managing AI agents. This page compares Sim to Langflow across platform architecture, AI capabilities, integrations, pricing, security and compliance, observability, and support, using sourced, dated facts for buyers evaluating both platforms.
What is Sim?
Sim is the open-source AI workspace where teams build, deploy, and manage AI agents, connecting 1,000+ integrations and every major LLM to automate real work visually, conversationally, or with code.
What is Langflow?
Langflow is an open-source, Python-based visual builder for creating and deploying AI agents and RAG (retrieval-augmented generation) applications, owned by DataStax (an IBM company).
Sim vs Langflow: feature-by-feature comparison
CompareSim vs Langflow
Sim
Langflow
Platform
Builder type
Visual canvas, chat, or codeVisual drag-and-drop canvas, natural-language (Chat), or code (API/SDK)
Visual canvas plus editable Python code, some NL assistLangflow is primarily a visual drag-and-drop canvas builder for connecting components into a flow. Every component's Python source is directly editable for code-level customization, and a Langflow Assistant can help build or edit flows conversationally.. Core paradigm is visual; code editing and an AI assistant are supplementary.
Learning curve
Low, plus natural-language Chat for non-technical usersLow for visual building; natural-language Chat surface for non-technical builders. Chat lets users describe a workflow in plain language and have Sim build it.
Moderate to steep, aimed at developersLangflow targets developers comfortable with Python and LangChain concepts such as embeddings, vector stores, chunking, and prompt chains. Non-technical users can use starter templates, but customizing components or debugging chains requires a technical background.
Self-hosting
Deployment options
Cloud-hosted or self-hosted, no mid-tier VPC optionCloud-hosted (managed, multi-tenant SaaS) or self-hosted (Docker/Kubernetes). No documented managed single-tenant/VPC hosting tier in between. The Enterprise plan's only hosting-related row in the pricing comparison table is a boolean "Self Hosting" flag; there is no dedicated-instance/VPC offering.
Desktop, local, Docker/K8s, cloud, self-hostedLangflow can run as a desktop app on Windows/macOS, a local pip/uv install, a Docker container, or a Kubernetes deployment, plus a hosted Langflow Cloud option with a free account tier. Multi-worker setups are documented for scaling self-hosted instances.
Templates
License
Apache 2.0Apache License 2.0
MIT licenseLangflow's core is MIT licensed, a permissive open-source license, per its public GitHub repository.
Environment promotion
Yes: fork a whole workspace into a dev/qa/prod-style child, diff it, and promote or roll back changes in either direction. Credential and env-var remapping is required before every promote, so secrets are never silently copied across environments. Gated to Enterprise plan on hosted Sim, or a FORKING_ENABLED flag on self-hosted deployments.
Unknown, no project-level env promotion documentedUnknown: no public documentation describes forking or cloning a full project or workspace and promoting changes between separate dev/qa/prod environments. Langflow's version history operates at the single-flow level, not the project or environment level.. Version history is per-flow snapshotting, not multi-environment promotion.
Version control
Deployment rollback plus Copilot edit diff/revertDeployed-version history with rollback for every workflow; server-persisted checkpoint/revert and visual diff (accept/reject) specifically for Copilot AI edits. Manual drag-and-drop undo/redo is client-side/localStorage only (capped at 100 ops, 5 stacks), not server-synced across devices. Deployment history does not include an arbitrary version-to-version diff tool, and knowledge base documents have no version history.
Yes: Langflow has a Version History menu for saving named snapshots of a flow, previewing a saved version in read-only mode, and restoring it, with an optional auto-backup of the current draft first. Auto-save of the working draft runs separately from these explicit versions.. No diff/compare view or branching documented.
Realtime collaboration
Native file storage
Yes: a native Files area with folder hierarchy, link-based sharing (public, password, email OTP, or SSO auth), and a workspace-level Recently Deleted view covering workflows, tables, knowledge bases, files, and folders. Admins can restrict which share-auth modes (public/password/email/SSO) a permission group is allowed to use.
Basic shared file store, no folders/sharing/trashPartial: Langflow has a per-server File Management system with a local or S3 storage backend, letting files be uploaded once and reused across flows. There is no documented folder hierarchy, link-based sharing with auth options, or deleted-item recovery.
Sub-workflows (composition)
Yes: Langflow's Run Flow component runs another saved flow as a subprocess of the current flow, dynamically generating input and output fields from the target flow's graph so the parent flow passes data in and receives the child flow's outputs back. It can also be attached to an Agent component as a callable tool.
Pricing
Pricing model
Credit-based billing, BYOK exempt from capsCredit-based usage billing (Stripe), with bring-your-own-key exemption from metered caps
Free open-source core; cloud free tier plus paid/enterprise tiersLangflow's core software is free and open source, with no license fee for self-hosting. Third-party sources describe Langflow Cloud as offering a free account tier plus a paid tier around $25 per month for higher usage limits, and separate enterprise pricing; Langflow's official pricing page does not confirm these figures directly.. Based on third-party summaries; the official pricing page doesn't confirm these figures.
Entry paid plan
Pro plan at $25/user/monthPro: $25 per user/month
Unverified; third parties cite roughly $25/monthUnknown: the exact entry paid-plan price and inclusions aren't confirmed on Langflow's own official pricing page. Third-party summaries cite a cloud paid tier starting around $25 per month.. Not confirmed against an official Langflow source.
Free tier
Bring your own key
Security & compliance
SOC 2
Unknown, no SOC2 certification documentedUnknown: no public documentation or official page states a SOC 2 certification for Langflow. The docs' Security page discusses infrastructure-level responsibility for operators, not a compliance certification.. Security docs place isolation and compliance burden on the deploying organization.
Data residency
Full control via self-hosting; Cloud region toggle is global, not per-customerFull data control via self-hosting (Docker/Kubernetes); data never leaves customer infrastructure when self-hosted. On Sim Cloud, async job execution has an internal US/EU region toggle, but it is deployment-wide, not a customer-selectable per-workspace residency option
Role-based access control
Unknown/limited, docs say isolation is infra-level not built-inUnknown: Langflow's own Security documentation states it neither enforces isolation between users within a single Langflow process nor restricts access to local disk or network resources, relying on infrastructure-level security for multi-tenant deployments. No native role-based access control system with distinct roles or scopes is documented.
Audit logging
Unknown, only general execution logs documentedUnknown: no official documentation describes a queryable or exportable audit log of user actions gated by plan. Langflow does document general execution and system logging for debugging, which is distinct from a security audit trail.
Additional compliance
SOC2SOC2. Self-hosting is the primary lever Sim offers for data-residency-sensitive compliance needs beyond SOC2, rather than additional certifications.
Unknown, no compliance certifications documentedUnknown: no public documentation or official page confirms HIPAA, ISO 27001, GDPR-specific attestation, PCI, or FedRAMP certification for Langflow.
Model & tool governance
Yes: enterprise "permission groups" let an admin allow-list/deny-list specific LLM providers and models, and separately deny specific tools/integrations (or disable all MCP or custom tools) per group, layered on top of workspace admin/write/read roles. This does not control whether an LLM provider retains prompts. Sim offers no "zero data retention" mode or governed AI gateway. A separate, Enterprise-gated feature lets orgs set a log-retention window and redact PII, but that only controls how long Sim itself keeps execution logs.
Unknown, no per-role model/tool restriction documentedUnknown: no public documentation describes an admin-configurable restriction on which LLM providers, models, or tools a given role or user may use. Model Providers configuration in Settings appears to be workspace-wide rather than per-role gated.
Credential governance
Yes: shared credentials (connected accounts, service accounts, workspace secrets) are their own nested permission level (Member/Admin) below organization and workspace roles, and enterprise permission groups can further allow-list specific integrations and restrict which file-share auth modes (public/password/email/SSO) a group may use. A user's personal environment variables/secrets are never shared or inherited by anyone, including org owners/admins.
Unknown, no per-role credential restriction documentedUnknown: no public documentation describes restricting which specific stored credentials a role or permission group may use, beyond standard per-user API key configuration.
Single sign-on (SSO)
Unknown, not confirmed as a documented shipped featureUnknown: no official Langflow documentation confirms SAML or OIDC single sign-on with organization auto-provisioning. Authentication docs cover API-key-based authentication, and third-party summaries mention SSO as a roadmap item, not a shipped, documented feature.. Some community sources describe SSO as planned rather than confirmed shipped.
Vetted first-party integrations
Yes: every one of Sim's 302 blocks is first-party authored and code-reviewed through the standard pull-request process in the main Sim repository; there is no public marketplace where an arbitrary third party can publish and have other users install executable tool code without going through Sim's own review. Custom code steps run inside Sim's own isolated-vm sandbox rather than as an installable third-party skill package, so the supply-chain trust boundary is Sim's codebase review, not an open registry.
Partial: reviewed bundles plus a lighter-vetted community Store and custom codePartial: most built-in integration bundles are contributed as pull requests to the official langflow-ai/langflow codebase and merged by core maintainers, but Langflow also ships a community Store where users can share and install flows and components with lighter, informal vetting, plus a custom-component system that lets any user author and run their own Python code with full server access. This code-execution model has a disclosed security incident: CVE-2025-3248, an unauthenticated remote code execution flaw in the custom-component code-validation endpoint (fixed in 1.3.0), actively exploited in the wild to deploy the Flodrix botnet on unpatched instances.. Langflow documents that it does not enforce isolation between users or restrict local disk/network access, so both bundle and custom-component code run with the same trust level as the core server.
PII redaction
Yes: the built-in Guardrails component includes a documented PII category that uses an LLM check to detect names, addresses, phone numbers, emails, social security numbers, and credit card numbers in workflow content. This is detection and validation, not confirmed automatic redaction of retained logs.. Documented as detection and validation; automatic redaction of stored logs specifically was not confirmed.
Custom data retention
Unknown, retention managed at self-hosted infra levelUnknown: no public documentation describes an org-configurable retention window for execution logs or soft-deleted resources. Self-hosters control their own database and log retention at the infrastructure level, since Langflow stores data in a configured database plus local or S3 file storage.
White-labeling
Unknown; only chat-widget style props documented, not full rebrandUnknown: no public documentation describes replacing Langflow's branding, such as logo, product name, or theme, in the self-hosted UI or embedded chat widget, beyond basic widget style customization exposed as embed props.. The embed widget supports styling props but full logo and name replacement across the whole app was not confirmed.
AI capabilities
Multi-LLM support
21 providers incl. OpenAI, Anthropic, Google, Bedrock21 provider integrations (OpenAI, Anthropic, Google/Gemini, Azure OpenAI, Azure Anthropic, Groq, Cerebras, Mistral, xAI, Bedrock, Vertex, Ollama, OpenRouter, and more). apps/sim/providers/models.ts defines 21 provider entries; openrouter/litellm/vllm/ollama resolve models dynamically at runtime rather than from a hardcoded model list.
Multiple providers via global Model Providers settingsLangflow supports configuring multiple LLM providers globally via Settings > Model Providers, each with its own API key, including OpenAI and Ollama for local or self-hosted models. The full list of supported providers is only shown in the running app's UI, not enumerated in the docs.. Exact provider count not fully published in docs.
Agent reasoning blocks
Natural-language building
Knowledge base / RAG
MCP support
Evaluation & guardrails
LLM-judge Evaluator plus Guardrails validation blockEvaluator block (LLM-judge scoring against user-defined named metrics) and Guardrails block (JSON validity, regex, RAG/hallucination scoring, PII detection/masking). These are per-call scoring/validation primitives, not a batch golden-dataset eval-suite runner or A/B prompt-testing harness.
Yes: Langflow has a Guardrails component that uses an LLM to check input against built-in categories such as PII, tokens and passwords, jailbreak attempts, offensive content, malicious code, and prompt injection. It also has evaluation components and integrations like Cleanlab Evaluator and LangWatch Evaluator for scoring responses.
Human-in-the-loop
Unknown, not documented as a built-in featureUnknown: no official Langflow documentation describes a dedicated pause-and-wait-for-human-approval mechanism mid-run. A community GitHub discussion asking how to implement human-in-the-loop suggests it is not a standard built-in feature, unlike LangGraph or FlowiseAI, which do document this.. A user discussion asked how to build this, implying no first-class component exists.
Generative media
Unknown, no native generative media blocks documentedUnknown: no official Langflow documentation describes built-in image, video, or audio generation components. Community discussions show users integrating image generation via custom components or external APIs, not a native block.
Dynamic tool use
No: an Agent block calls tools the workflow author explicitly added to it at build time, rather than browsing and picking from a broader pool (e.g. an entire MCP server catalog) at inference time. Runtime MCP "discovery" exists to resolve/refresh the schema of an already-configured tool. The model does not browse or choose from the server's full tool list.
Yes: Langflow agents receive a registered list of tools at setup, and the connected LLM decides at run time which registered tool to call based on each tool's description. This includes flows exposed as tools and MCP-server tools.. Tool pool is whatever is registered to that agent, not the entire platform.
Automatic model fallback
No: a failed or rate-limited LLM call is retried using Sim's own hosted API keys for the same model, rather than automatically switching to a different model or provider. A "fallback" comment in the provider layer refers to rotating among Sim's own hosted API keys for the same model, not switching models.
Unknown, no built-in automatic model fallback documentedUnknown: no public Langflow documentation describes automatic fallback or retry to a different model or provider on a failed or rate-limited LLM call. A blog post shows manually building smart model routing as a custom flow rather than a built-in fallback feature.. Users can hand-build routing flows, but it is not an automatic platform feature.
Agent skills
Yes: named, reusable "Agent Skills" (built on the open Agent Skills / SKILL.md format) that agents load on demand via progressive disclosure, editable in-app or imported from a SKILL.md file or GitHub URL. Only the skill name and description sit in the agent's system prompt (~50-100 tokens each); the full instructions load into context only when the agent calls load_skill.
Unknown, no named reusable skill library documentedUnknown: no public documentation describes a reusable, named prompt or knowledge-snippet library invokable by reference across agents, distinct from a one-off system prompt field on each agent component.
Native chat deployment
Parallel execution
Yes: a native Parallel block fans a run out into concurrent branches (fixed count or one per list item) and joins their results back into the workflow automatically. Contained blocks run concurrently instead of sequentially, either a fixed number of times or once per item in a list/collection, and each branch's output aggregates for downstream blocks.
Agent2Agent (A2A) protocol
No. Native A2A protocol support is not shipped in Langflow core. A community member submitted a working implementation and feature request in November 2025, but it remains an open enhancement request (closed as a duplicate of an earlier tracking issue), not a merged feature. The only path to A2A interoperability is third-party custom components.
Loop / iteration block
Yes: Langflow ships a dedicated Loop component that takes a list of JSON or Table items (for example CSV rows), passes items one at a time through its Item output port to a chain of connected components, and loops back until every item is processed sequentially, before emitting the aggregated result from its Done port.
Integrations
Integrations
302 blocks, ~3,900 tool actions302 first-party blocks, ~3,900 underlying tool actions. Sim's landing page cites "1,000+ integrations," a broader figure counting individual API actions rather than top-level blocks. Both numbers describe the same integration surface.
Dozens of provider bundles; full count only in-appLangflow organizes third-party integrations as component bundles grouped by provider, such as Google, OpenAI, LangChain, Elastic, and Composio. The full current list of bundles and components is only visible in the app's Bundles panel, not enumerated on the docs site.
Trigger types
Webhook, cron, chat, REST API, triggers for 61 appsWebhook, schedule/cron, chat, REST API, and event-based triggers for 61 apps (Slack, Gmail, GitHub, Stripe, etc.)
Yes: Langflow flows can be triggered via the REST API run and advanced run endpoints, a dedicated Webhook component for event-driven HTTP POST triggers, the Playground or chat interface, or external schedulers like cron or Airflow calling the API.. Scheduling itself is via external tools, not a native in-app scheduler.
Custom code steps
API publishing
SDKs & extensibility
Yes: Langflow supports custom Python component development with documented input and output classes, plus a separate open-source Embedded Chat widget package for embedding. Community members can also contribute components, bundles, and templates back via GitHub, but there is no formal third-party marketplace documented.. No formal marketplace documented.
Publish as MCP server
Observability & durability
Tracing & observability
Yes: execution logs include a per-block/per-span trace view (duration, cost, token counts, and latency stats like TTFT/TPS) with expandable nested iteration groups, plus a "View Snapshot" frozen copy of the workflow structure and block states at run time for debugging. This trace view is built directly into Sim rather than a raw export browsable in an external tool like Jaeger, and does not expose aggregate latency-percentile charts (p50/p95/p99). The run snapshot serves as a log-detail/debugging artifact rather than a resumable mid-run checkpoint.
Yes: Langflow automatically captures step-by-step execution traces within a flow run. It can forward detailed traces, including prompts, responses, token usage, latency, and intermediate steps, to external observability platforms such as LangSmith, Langfuse, and LangWatch via environment-variable configuration.. Deep trace visualization relies on integrating an external observability platform.
Durability & retries
Tool-call retries (up to 10x); single-attempt job orchestrationIndividual tool/API calls have configurable exponential-backoff retry (up to 10 attempts). The background job-orchestration layer itself retries only once by design. Durability instead comes from consecutive-failure tracking on schedules and the human-in-the-loop snapshot pause/resume mechanism. Sim does not offer guaranteed-once-only block execution, a failed-run holding queue for manual recovery, or a "replay a past execution with its original inputs" feature. The per-execution debugging snapshot serves as a log-detail artifact rather than a resumable mid-run checkpoint.
Unknown, no documented replay/checkpoint model for flowsUnknown: no public documentation describes automatic retries, checkpointing, or replaying a past execution with its original inputs at the platform level. This is a documented LangGraph capability, not confirmed for Langflow flows specifically.
Failure alerting
Unknown, no proactive failure alerting documentedUnknown: no public documentation describes proactive notification, such as email, Slack, or webhook alerts, when a flow run fails or crosses a cost or latency threshold. Available integrations focus on logging and tracing rather than alerting.
Data drains
Yes: Enterprise orgs can continuously export workflow logs, job logs, or audit logs on a schedule to a customer-owned S3 bucket, GCS bucket, Azure Blob container, BigQuery table, Snowflake table, Datadog logs intake, or an HTTPS webhook. Each drain exports exactly one data source; multiple drains are created to export multiple sources. Viewing drain config/run history is restricted to org owners/admins.
Trace export to LangSmith/Langfuse/LangWatch onlyPartial: Langflow supports continuously forwarding execution trace data to external observability platforms such as LangSmith, Langfuse, and LangWatch via configuration. No general-purpose data drain to arbitrary destinations like S3, BigQuery, or a generic webhook for audit or usage data was found documented.
Async execution
Yes: a workflow can be triggered in fire-and-forget async mode, returning HTTP 202 with a job ID immediately, then polled via a dedicated jobs endpoint through queued/processing/completed/failed states. Async jobs are tracked via polling the job endpoint rather than a completion webhook/callback option.
Some support via webhook trigger plus monitor endpointsPartial: Langflow documents a webhook-triggered flow execution pattern and a Monitor endpoints page for checking flow build and run status, giving some support for background triggering and later status checks. A dedicated async job-polling API pattern isn't fully documented.
Execution limits
5-50 min sync timeout, 90 min async, 15-300 concurrentPlan-gated: synchronous API calls time out at 5 minutes on the free plan and 50 minutes on paid plans, async calls at 90 minutes on every plan, with 15 to 300 concurrent executions per billing entity depending on plan. These limits are not published in docs; request bodies are separately capped at 10 MB.
Unknown, no published execution/concurrency limitsUnknown: Langflow's official documentation publishes no concrete numbers for maximum single-execution duration or concurrent run limits. Self-hosted deployments are bounded only by the operator's own infrastructure and worker configuration.
Partial-failure handling
Unknown, no documented per-step error-routing featureUnknown: no public documentation describes routing a single failing step to an error-handling path while the rest of the flow continues; this was not confirmed as a native feature in the documentation reviewed.
Support
Support channels
Community support plus Enterprise 'Dedicated Support'Community (open source, GitHub) plus an unquantified "Dedicated Support" flag on the Enterprise plan. Enterprise and pricing pages do not include CSM, onboarding/enablement, or professional-services details beyond a plan-comparison-table "Dedicated Support" flag.
Discord and GitHub community support; no confirmed paid tierLangflow's primary support channel is a public Discord community server, plus GitHub Discussions and Issues for questions and feature requests. No official documentation confirms a paid or dedicated enterprise support tier separate from DataStax or IBM commercial channels.
SLA
Unknown, no SLA documentedUnknown: no public documentation confirms a formal SLA for response time or uptime guarantee offered for Langflow, on any plan.
Community
100,000+ buildersOver 100,000 builders use Sim
About 150,700 GitHub stars, 9,400 forksLangflow's GitHub repository has approximately 150,700 stars and 9,395 forks, alongside an active public Discord server. Industry coverage frequently describes it as a widely used open-source AI-agent and RAG (retrieval-augmented generation) builder.
Academy / training
No official academy; only third-party courses foundUnknown: Langflow doesn't run an official structured course, certification, or academy program. Third-party paid courses exist on platforms like Udemy that teach LangChain and Langflow, but these aren't an official Langflow product.
Sim standout features
AI Copilot / Chat agent-building surface
Chat and in-editor Copilot suggest and build workflow changes directly.
A natural-language surface (Chat) and in-editor Copilot that can explain, suggest, and build workflow changes directly, backed by a dedicated copilot module with its own tool registry.Hybrid semantic + keyword knowledge base
Combines vector and full-text search with configurable chunking across 11 file formats.
Built-in RAG with pgvector embeddings and a generated tsvector column for combined vector + full-text search, plus a token-based chunker with configurable chunk size/overlap and 11 supported file formats (csv, doc, docx, html, json, md, pdf, pptx, txt, xlsx, yaml).Native MCP client and server
Call external MCP servers as tools, or expose Sim workflows as an MCP server.
A dedicated MCP block lets any workflow call external MCP servers as a tool, and a serve/workflow-servers API surface lets Sim expose its own workflows as MCP servers.Fork a workspace into dev, qa, and prod environments
Fork, diff, and promote environments with mandatory credential remapping.
Fork a whole workspace into a dev/qa/prod-style child environment, preview a diff, and promote changes bidirectionally. Credential and env-var remapping is required on every promote, so secrets never cross environments silently.Human-in-the-loop approvals with durable resume
Pause a run for human approval and resume later via a durable snapshot link.
A dedicated block pauses a run and waits for a human-submitted approval form, backed by persisted execution snapshots so the run can resume later via a link, even after a server restart.Self-hostable under Apache 2.0
Fully open source with Docker Compose and Helm deployment options.
Fully open source (Apache 2.0), with Docker Compose files and a Helm chart for Kubernetes deployment, alongside a managed cloud-hosted option.Documented Langflow limitations
No real-time multiplayer editing
No live multi-user co-editing; only JSON export/import or shared accounts.
Multiple users cannot co-edit the same flow with live cursors or synced operations. There's an open community feature request for real-time collaboration like Figma or n8n's. Current practice is exporting flows as JSON and merging changes like code, or sharing an account.Lowest enterprise-readiness scores in third-party benchmark
Scored lowest on codability (35%) and enterprisiness (30%) in n8n's 2026 report.
n8n's 2026 AI Agent Development Tools report scored Langflow 35 percent on Codability and 30 percent on Enterprisiness, the lowest of the vendors evaluated, citing gaps in agent sandboxing, security guardrail maturity, and evaluation frameworks.Bottom line
Choose Sim if you want an open-source, self-hostable AI workspace that treats AI agents as first-class citizens: native multi-LLM support, real-time multiplayer editing, environment promotion (dev/qa/prod), human-in-the-loop approvals, and enterprise governance (SSO, credential-level permissions, audit logs) built in rather than bolted on.
Choose Langflow if you specifically need deep LangChain/Python component ecosystem: Langflow ships hundreds of drag-and-drop components organized into core groups and provider bundles (Google, OpenAI, LangChain, Elastic, Composio, and more). Any component's underlying Python code can also be edited directly for full customization.
Frequently asked questions
Sim is an open-source AI workspace where teams build, deploy, and manage AI agents visually, conversationally, or with code. Langflow is an open-source, Python-based visual builder for creating and deploying AI agents and RAG (retrieval-augmented generation) applications, owned by DataStax (an IBM company). Teams considering a switch typically weigh licensing (Sim is Apache 2.0 and self-hostable), pricing model, and how AI-native the platform's agent-building experience is.