GITNUXSOFTWARE REVIEW
AI In IndustryTop 10 Best Bots Software of 2026
Compare bots software options for chat and automation use cases, including how tools like Tidio fit different business workflows.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
AI search agents find sources, extract figures with provenance, and aggregate written reviews. They also transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Landbot is the best pick for SMB teams that need visual chatbot flows with reusable conversation blocks because it lets you standardize prompts, questions, and validation across multiple bots while still keeping webhook integrations handy; Voiceflow is the better alternative for API-minded teams with frequent updates since its production-ready versioning ties publishing to testable flow states.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Landbot
Reusable conversation blocks let teams standardize prompts, questions, and validation steps across multiple bots.
Best for: Fits when teams need visual chatbot flows with webhook integrations and iterative publishing.
Tidio
Editor pickNative handoff and shared conversation view lets agents take over without switching tools.
Best for: Fits when teams need web-chat bot triage with human handoff and webhook-driven automation.
Voiceflow
Editor pickProduction-oriented versioning and publishing workflow for conversation changes tied to testable flow states.
Best for: Fits when teams need visual bot workflows with frequent updates and external system actions.
Comparison Table
Landbot
SMBLandbot lets teams create conversational forms and chatbots for websites, WhatsApp, and APIs.
Reusable conversation blocks let teams standardize prompts, questions, and validation steps across multiple bots.
Landbot is a strong fit for teams that want a drag-and-configure flow editor and a preview loop for conversation changes. The editor supports branching logic, rich prompts, and structured user inputs so multi-step journeys can be built without custom UI development. Integration depth is practical through webhooks and connected actions that can pass user context to external services and return responses to the flow.
A key tradeoff is that advanced AI orchestration usually needs more care than rule-first bots because the flow still drives routing, fallback, and escalation. Landbot works well when the main value is collecting requirements, qualifying users, or guiding customers while triggering backend actions at specific steps. It is less ideal when the primary goal is fully dynamic agent behavior with minimal conversation design constraints.
- +Visual flow builder reduces time-to-iterate on conversation changes
- +Reusable blocks simplify building multi-step forms and guided dialogs
- +Webhook-based actions let bots call external services at exact steps
- +Preview and publish flow support quick validation of user journeys
- –Complex escalation and fallback logic can become hard to reason about
- –Deep agent-grade orchestration requires careful configuration around flow routing
Customer support teams
Handle FAQs with guided resolutions
Faster resolution and fewer manual tickets
Revenue operations teams
Qualify leads through stepwise forms
Higher-quality leads in CRM
Show 2 more scenarios
Product teams
Guide users to setup tasks
Reduced onboarding friction
Uses branching dialogue to collect configuration details and start onboarding actions.
E-commerce teams
Assist shoppers and route to orders
More supported purchases
Runs guided selection questions and sends order-related requests to fulfillment services.
Best for: Fits when teams need visual chatbot flows with webhook integrations and iterative publishing.
Tidio
SMBLive chat platform with AI chatbot builder for small and mid-size online businesses.
Native handoff and shared conversation view lets agents take over without switching tools.
Tidio’s bot builder focuses on chat-first automation inside the same interface used for live agents, which reduces the split between automated and handled conversations. Flow configuration supports scripted branching, canned response management, and escalation to human agents when rules match. For integration depth, the automation layer can call out through webhooks so chat events can drive external systems and status updates.
A key tradeoff is that Tidio’s bot logic is best suited to rule-based and templated dialogue rather than fully custom agent reasoning. It fits teams that need fast deployment for FAQ-style flows and support triage on web messaging channels. For high-precision conversational experiences, teams may need to keep intents and fallback behavior tightly curated to avoid irrelevant bot replies.
- +One workspace combines bot flows and live agent conversation handling
- +Webhook integration supports event-driven automation with external systems
- +Escalation rules route matching sessions to human agents
- +Conversation-level reporting helps teams review bot and agent outcomes
- –Dialogue depth is limited compared with agentic tool-calling frameworks
- –Large numbers of intents require careful upkeep to avoid misrouting
- –Advanced orchestration needs external logic behind webhooks
- –Bot behavior relies on configured rules and fallback design
Customer support teams
Automate ticket triage and handoff
Faster resolution with fewer repeats
Ecommerce operations teams
Answer order and policy questions
Lower support queue volume
Show 2 more scenarios
RevOps and systems teams
Sync leads from chat to CRM
Automated follow-up for captured users
Webhook events push conversation outcomes into external lead workflows.
Helpdesk administrators
Moderate bot responses and escalation
Consistent tone and routing
Admin controls manage bot behavior and review bot-driven conversations with agents.
Best for: Fits when teams need web-chat bot triage with human handoff and webhook-driven automation.
Voiceflow
API-firstVoiceflow supports collaborative design, testing, and deployment of AI agents and chat experiences.
Production-oriented versioning and publishing workflow for conversation changes tied to testable flow states.
Voiceflow is a strong fit for bot teams that need a visual conversation workflow with programmable behavior such as variables, conditional routing, and scripted tool calls. Conversation testing supports validating dialog paths before publishing, and the release workflow helps keep revisions aligned with ongoing changes. Integration options support connecting external services through webhooks and API-based actions.
A key tradeoff is that deeper customization often moves work into integration code or external services rather than purely in the flow editor. Voiceflow works best when a team can model the conversation as a maintainable flow and then delegate retrieval, data updates, or complex logic to connected systems.
- +Visual flow builder with branch logic and reusable components
- +Conversation testing supports catching broken states before publishing
- +Integration hooks enable webhook or API-driven bot actions
- +Publishing workflow helps manage revisions for active assistants
- –Complex reasoning often requires external services and extra plumbing
- –Large bot states can become harder to maintain in a single flow
customer support operations teams
Handle policy questions with guided flows
Fewer manual transfers
product teams
Assist with feature onboarding steps
Higher onboarding completion
Show 2 more scenarios
revenue operations teams
Qualify leads and route follow-ups
Faster lead handoff
Teams collect structured inputs in-dialog and trigger CRM updates via integration calls.
internal enablement teams
Answer IT questions using knowledge lookups
Reduced support workload
Teams use a conversation flow to gather context, then call retrieval services for responses.
Best for: Fits when teams need visual bot workflows with frequent updates and external system actions.
Manychat
SMBManychat automates customer conversations across Instagram, WhatsApp, Messenger, and SMS.
Tag-driven audience updates tied to conversation flow execution, with webhook-triggered entry for event-based automation.
Manychat focuses on messaging-first automation for Meta and other chat channels, with visual flow building plus API access. It supports chatbot logic using configurable steps like message sending, branching, and tags that track conversation state.
- +Visual flow builder for multi-branch messaging sequences
- +Tag-based segmentation supports keeping user state across flows
- +Webhook entry points enable external systems to trigger automation
- +Conversation logs support practical debugging of step-by-step execution
- –Generative AI tooling is not as general-purpose as LLM-centric bot frameworks
- –Complex orchestration across many channels can require careful flow design
- –Limited native depth for custom dialog state compared with code-first frameworks
- –Webhook and integration logic increases operational overhead for larger deployments
Ecommerce and retail teams
Guide shoppers through product questions
Structured purchase path
Sales and marketing teams
Qualify contacts with branching questions
Clearer handoff signals
Show 2 more scenarios
Support and operations teams
Triage inbound requests with rules
Faster escalations
Collects initial details, classifies requests, and routes conversations based on configured triage rules.
Customer service teams
Hand off to humans when needed
Automated first response
Transitions conversations from automated flows to agent assistance for manual resolution of complex requests.
Best for: Fits when teams need messaging-channel automations with fast visual flow iteration and tag-based state tracking.
Botpress
API-firstBotpress provides a visual platform for building, deploying, and managing AI agents.
Workflow-driven orchestration lets bot designers chain custom actions with LLM results through deterministic steps and configurable handoff points.
Botpress targets teams that need conversational automation with editable conversation flows and programmable integrations. It provides a visual builder for bot logic plus an extensibility layer for custom actions, external API calls, and chat channel connections.
- +Visual flow builder with strong hooks for custom actions and external calls
- +Workflow-style execution supports multi-step orchestration around model outputs
- +Extensibility via code modules for channel adapters and business logic
- +Built-in analytics for monitoring conversation outcomes and fallbacks
- –Advanced orchestration requires nontrivial workflow and state design
- –Channel setup often needs custom work for edge-case message formats
- –Large bot projects need governance discipline to keep flows maintainable
- –Model behavior tuning can be slower than intent-first, rules-only bots
Bot developers and operations teams
Improve flows using conversation analysis
More maintainable bots
Digital experience platform teams
Deploy one assistant across channels
Consistent assistance
Show 2 more scenarios
Customer support and service teams
Automate Q&A and troubleshooting
More automated support
Builds assistants that answer questions, guide troubleshooting, and reduce routine ticket volume with clear escalation paths.
Sales and marketing teams
Route leads after conversational data capture
More consistent lead routing
Uses structured conversational flows to collect qualification inputs and trigger follow-up actions and routing.
Best for: Fits when teams need visual bot flows plus code-driven integrations and controlled orchestration across multiple channels.
SnatchBot
SMBCloud-based chatbot creation platform for building bots across multiple channels.
Channel deployment support with workflow versions tied to scripted integrations via webhooks and action steps.
SnatchBot focuses on production bot building with visual conversation flows that can be deployed across common messaging channels. The editor supports workflow-like logic, reusable components, and scripted integrations through webhooks and REST-facing endpoints for external actions.
- +Visual flow builder maps dialogue branches to deployable bot versions
- +Webhook and API-oriented actions integrate external systems into bot steps
- +Built-in bot analytics support iteration on conversation outcomes
- +Human handoff steps can be inserted into scripted conversation flows
- –Advanced behaviors require more configuration than code-first frameworks
- –Maintaining complex branches can slow iteration without strong version discipline
Customer support operations teams
Triage tickets and route to agents
Faster resolutions with fewer manual steps
Ecommerce customer service teams
Answer order and return questions
Lower support volume
Show 2 more scenarios
Lead gen marketing teams
Qualify prospects through conversational flows
More qualified pipeline
Captures answers in dialog flows and triggers CRM actions through webhook endpoints.
IT automation and DevOps teams
Integrate bots with internal tooling
Automated workflows at scale
Uses REST-facing endpoints to run scripted actions during conversations and logs outcomes in analytics.
Best for: Fits when operations teams need visual conversation automation with external system calls and monitoring.
Microsoft Copilot Studio
enterpriseMicrosoft Copilot Studio enables organizations to build custom copilots and workflow agents.
Topic-based generative and action orchestration inside Copilot Studio, with enterprise-ready governance through Entra-backed controls.
Microsoft Copilot Studio focuses on building copilots and chatbots with guided authoring, topic-based conversation flows, and integrated generative responses. It pairs conversation design with Microsoft 365 and Azure connectors for actions like querying content, triggering workflows, and calling external services through configurable connectors.
- +Deep Microsoft 365 and Azure integration for retrieval and action workflows
- +Guided authoring for topics, handoff, and fallback behaviors
- +Configurable connectors and APIs for tool calling from bot conversations
- +Enterprise identity alignment via Microsoft Entra and tenant governance controls
- –Complexity rises quickly when mixing generative behavior with multi-step flows
- –Governance discipline is needed to keep knowledge and permissions consistent
- –Some advanced custom dialogue logic can require more scaffolding work
- –Debugging prompt orchestration and action failures can take multiple cycles
Customer support operations teams
Deflect tickets with guided bot triage
Lower resolution time
IT service desk teams
Automate requests through Entra governed access
Fewer manual escalations
Show 2 more scenarios
Operations analysts
Answer questions with policy-controlled data actions
Faster operational decisions
Connect copilots to governed data endpoints for actions like querying dashboards and triggering internal workflows.
HR and internal communications
Provide employee guidance with conversation flows
Improved self-service
Build chat experiences that follow scripted topics and return generative responses grounded in approved documents.
Best for: Fits when Microsoft-centric teams need managed bot deployment with connector-based actions.
Botsify
SMBChatbot platform for creating AI bots for websites and messaging apps.
Conversation-step execution that ties each flow node to webhooks so actions run with predictable inputs.
Botsify builds conversational bots by combining a visual conversation editor with connectors for common messaging channels. It supports intent-style routing and scripted dialogue steps, plus automation hooks like webhooks and API calls for business actions.
- +Visual flow editor maps conversation steps to webhooks for real actions
- +Channel connectors reduce the effort to publish the same bot across messaging
- +Conversation analytics highlight where users abandon flows and fail routing
- +Role-based access separates bot authoring from publishing and administration
- –Advanced multi-step logic can become verbose compared with code-first frameworks
- –External system integrations depend on webhook payload design and testing discipline
- –Large knowledge workflows need careful configuration to avoid shallow responses
- –Deep platform-level extensibility is limited versus frameworks with full control
Customer support ops teams
Deflect repetitive tickets via chat bot
Reduced ticket volume
Ecommerce growth teams
Guide shoppers with decision-tree conversations
Higher conversion rates
Show 2 more scenarios
IT and integration teams
Automate workflows from bot interactions
Faster process automation
Webhooks and API calls trigger business actions, with analytics showing failed steps and routing behavior.
Contact center supervisors
Manage bot roles with admin visibility
Improved bot governance
Role-based controls support governance while admin activity visibility helps audit configuration changes.
Best for: Fits when mid-size teams need visual bot automation with controlled integrations and basic governance.
Pandorabots
API-firstConversational AI platform for building and hosting chatbot agents.
Hosted AIML runtime for deterministic dialogue that can be controlled through APIs for session-level behavior.
Pandorabots focuses on hosted chatbot orchestration using a programmatic AIML runtime and a bot-building workflow oriented around knowledge sources and dialogue scripts. It is distinct for teams that need deterministic intent routing and response generation, rather than only prompt-driven conversation.
- +AIML-based logic gives deterministic responses for scripted dialogue
- +Hosted bot runtime reduces infrastructure work for conversational services
- +Programmatic conversation control supports integration into existing apps
- +Knowledge source separation supports reuse across multiple bots
- –Generative LLM behavior is limited compared with prompt-first agent builders
- –Complex flows require more authored content than intent-first tools
- –Advanced analytics and governance controls are less explicit than in enterprise suites
- –Tool-calling style integrations depend on external wiring work
Customer support automation teams
Route intents to scripted responses
Lower handling time
Knowledge management teams
Ground answers in managed knowledge sources
Fewer incorrect answers
Show 2 more scenarios
Automation engineers
Integrate bots via APIs and webhooks
Faster workflow completion
Executes programmatic bot control for external actions like ticket creation and status checks.
Enterprise developers
Manage sessions and deterministic dialogue
More reliable conversations
Supports hosted conversation session management for controlled stateful interactions at scale.
Best for: Fits when deterministic, authored conversational flows matter more than generative reasoning.
Crisp
SMBCrisp combines shared inboxes, chat automation, and customer messaging for support teams.
Agent handoff uses shared conversation state so bot questions and agent replies stay in one thread.
Crisp runs conversational support with live chat, message threads, and bot-assisted workflows inside its customer messaging UI. It supports automated bot flows that can trigger on user events, collect structured inputs, and route chats to agents.
- +Conversation routing and assignment keeps automated and human handling in one inbox view
- +Webhooks let external systems react to bot and conversation lifecycle events
- +Bot flows support collecting inputs and branching based on captured answers
- +Unified messaging UI reduces handoff friction between bots and agents
- –Bot logic is less suited for deep LLM orchestration than full agent frameworks
- –Automation governance depends heavily on correct trigger configuration and inbox rules
Support operations teams
Auto-route chats and cases to teams
More consistent queue handling
Customer support teams
Turn active chats into ticket records
Continuous issue handling
Show 2 more scenarios
Website support teams
Provide live chat with pre-chat intake
Centralized real-time visitor support
Offers web visitors operator replies with conversation history and structured pre-chat context collection.
Support and documentation teams
Guide customers with chatbot workflows
Fewer basic tickets
Combines knowledge base content and bot flows to resolve routine questions before agent handoff.
Best for: Fits when teams want bot-assisted support in the same messaging workspace as agent chat.
Conclusion
After evaluating 10 bots software, Landbot stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Bots Software
Bot software used for chatbots and conversational automation spans visual flow builders, workflow orchestrators, and API-driven runtimes that connect to messaging channels and webhooks. This guide covers Tidio, Voiceflow, Landbot, SnatchBot, Botsify, Botpress, Manychat, Microsoft Copilot Studio, Crisp, and Pandorabots using the same practical lens across integration depth and control over execution.
Each tool card emphasizes how bot logic runs, how teams publish updates, and how human handoff and event triggers behave in production. The ranking also reflects friction points such as state complexity, orchestration setup, and how well advanced multi-step behaviors map to the workflow model.
Bots Software for building conversational chatbots with automation, routing, and API-connected actions
Bots software is software for designing dialogue flows that route messages, collect inputs, and call external actions through webhooks or connector steps. It also includes execution controls such as handoff to human agents, trigger-based automation entries, and deterministic routing for specific dialogue paths.
In practice, Tidio pairs a shared conversation view with native handoff so agents can take over without switching tools, while Botsify binds each flow node to webhook actions so bot steps run with predictable inputs. Other platforms such as Voiceflow focus on a production publishing workflow with versioning tied to testable flow states, which matters when updates must be controlled across branching conversation logic.
Bots Software evaluation: integration, execution control, and governance
Execution control determines whether a bot runs deterministic steps, routes to a human agent inside the same conversation thread, or hands off at a controlled point in a workflow. Integration depth determines whether bot actions can call external systems through webhook-driven steps, connector actions, or API-controlled runtime behavior.
Human handoff inside the same conversation surface
Tidio keeps bot questions and live agent handling in one workspace via native handoff and a shared conversation view. Crisp provides agent handoff using shared conversation state so automated and human replies stay in one thread.
Versioning and publish workflow tied to testable states
Voiceflow uses production-oriented versioning and a publishing workflow connected to testable flow states. Microsoft Copilot Studio focuses on guided authoring for topics with managed deployment behavior that can increase governance needs when mixing generative behavior with multi-step flows.
Webhook-driven actions mapped to specific dialogue steps
Botsify ties each visual flow node to webhook execution so actions run with predictable inputs. SnatchBot supports channel deployment with workflow versions linked to scripted integration steps through webhooks and action steps.
Reusable conversation components for multi-bot consistency
Landbot provides reusable conversation blocks so teams standardize prompts, questions, and validation across multiple bots. Manychat uses tag-based segmentation tied to flow execution so user state can persist across messaging sequences.
Workflow orchestration around model outputs with deterministic steps
Botpress supports workflow-driven orchestration that chains custom actions with LLM results through deterministic steps and configurable handoff points. Microsoft Copilot Studio orchestrates generative topics with connector-based actions and guided handoff and fallback behaviors for managed deployment.
Deterministic authored runtime with API-controlled session behavior
Pandorabots runs hosted AIML logic that returns deterministic responses for scripted dialogue and exposes session-level control through APIs. Tidio favors dialogue depth and routing behavior that can outperform strict determinism for complex conversational triage.
How to choose Bots Software by execution model and control depth
Start by choosing the execution model that matches the way operational support and automation must behave when users ask off-script questions. Then validate integration and governance needs by mapping how bot steps call external systems and how teams publish changes without breaking routing or permissions.
Pick the runtime behavior for off-script requests
If off-script handling must switch into live agent support without leaving the conversation, choose Tidio for native handoff with a shared conversation view or Crisp for shared conversation state in the same messaging workspace. If off-script behavior must stay deterministic and authored, choose Pandorabots because hosted AIML runtime focuses on deterministic dialogue with API-controlled session-level behavior.
Choose your automation binding style for external actions
If each dialogue step must call external systems with predictable webhook payloads, choose Botsify because each flow node executes webhook actions with controlled inputs. If integration steps must also be packaged into deployable workflow versions per channel, choose SnatchBot because it links workflow versions to channel deployment and scripted webhook action steps.
Decide how changes move from test to production
If frequent conversation edits must be tied to testable flow states and controlled publishing, choose Voiceflow because its versioning and publish workflow maps to flow states. If knowledge and permissions must be governed inside a Microsoft-centric environment, choose Microsoft Copilot Studio because it uses Entra-backed controls tied to topic authoring and connector-based actions.
Select a design surface that matches long-term maintainability
If teams need standardization across many bots and multi-step guided dialogs, choose Landbot for reusable conversation blocks that reduce duplicated prompts and validation steps. If teams need orchestration where multi-step logic spans visual workflows plus code-driven hooks, choose Botpress because its workflow-style execution supports multi-step orchestration around model outputs with deterministic step chaining.
Match orchestration depth to team setup capacity
If advanced orchestration is required but teams can invest in state and workflow design, choose Botpress because complex orchestration requires nontrivial workflow and state design. If the focus is on keeping operations teams moving fast with visual branch logic tied to deployable versions, choose SnatchBot because workflow versions map dialogue branches to channel deployments.
Who should buy each Bots Software tool
Teams with support operations need a clear handoff boundary and shared context so agents can answer without re-entering the customer journey. Teams with system automation needs require step-level action wiring, stable inputs, and publish controls that prevent broken routing after updates.
Customer support teams adding bot triage to existing messaging channels
Tidio fits because it combines bot flows with live agent conversation handling using native handoff and a shared conversation view.
Product teams shipping frequent conversation updates with strict release control
Voiceflow fits because production-oriented versioning and publishing tie updates to testable flow states.
Operations teams that need visual branching plus webhook-based system calls
SnatchBot fits because it maps dialogue branches to deployable bot versions and integrates external calls through webhook and action steps.
Messaging marketers building multi-branch sequences with persistent user state
Manychat fits because tag-based audience updates tie to conversation flow execution and tag segmentation keeps user state across flows.
Automation teams in Microsoft environments that require governed connector-based action workflows
Microsoft Copilot Studio fits because it provides Entra-backed governance controls and guided authoring for topics, handoff, and fallback behaviors.
Common Bots Software mistakes that break production behavior
Most implementation failures come from mismatched execution control, weak action wiring discipline, or state designs that become unmanageable as flows grow. The mistakes below correspond to specific failure modes visible in the tools’ workflow models and governance requirements.
Treating complex multi-branch escalation as easy to reason about in visual flow tools
Landbot warns that complex escalation and fallback logic can become hard to reason about, so simplify fallback paths or modularize logic using reusable blocks.
Letting intent counts grow without maintaining routing hygiene
Tidio’s dialogue depth is limited compared with agentic tool-calling frameworks, and its handling of large numbers of intents requires careful upkeep to avoid misrouting.
Building advanced orchestration without planning workflow and state design effort
Botpress flags that advanced orchestration requires nontrivial workflow and state design, so define state boundaries and handoff points early.
Assuming webhook actions will work without payload and input validation discipline
Botsify ties each flow node to webhook execution, so weak webhook payload design and insufficient testing will cause predictable input failures.
Relying on deterministic authored logic when generative behavior is the primary need
Pandorabots focuses on deterministic AIML dialogue, so generative LLM behavior will be limited compared with prompt-first agent builders.
How We Selected and Ranked These Tools
We evaluated each bots software tool by execution control fit, integration depth for external actions, and the friction teams face when publishing changes. We weighted features at 40% and used ease and value at 30% each to reflect how quickly teams can reach stable behavior in production.
Tidio ranked highest because native handoff and a shared conversation view let agents take over without switching tools, and webhook integration supports event-driven automation with external systems. The ranking also considered how each workflow model handles state complexity, since Voiceflow and Botpress can require stronger design discipline when flows grow.
Frequently Asked Questions About Bots Software
How do Microsoft Copilot Studio, Dialogflow, and Rasa differ in workflow control for chatbot behavior?
Which bots software options support webhook-driven automation for external system actions?
How do handlers implement human handoff while keeping the conversation state consistent?
What breaks if a bot needs deterministic intent routing instead of prompt-driven responses?
How do admin controls and audit visibility work in Botsify, Bots software, and Crisp?
Which tools support environment-ready configuration across multiple deployments?
How does dialog testing work for teams shipping frequently updated bots in Voiceflow and Landbot?
Where does Rasa fall short compared with Microsoft Copilot Studio for connector-based action orchestration?
How do bots software platforms handle structured inputs and validation inside a conversation flow?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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