A visual automation platform for building AI agents and workflows with hosted models, connectors, and governance.
A visual automation platform for building AI agents and workflows with hosted models, connectors, and governance.
Gumloop is a visual automation platform for building AI agents and workflows with hosted models, connectors, and governance. It is aimed at people who want a practical way to move from an idea or business task to a repeatable result. The vendor pages describe capabilities including Visual workflow orchestration, Unlimited agents on listed paid plans, 35+ models and bring-your-own keys, Company Brain knowledge, Custom MCP server hosting and proxying. Together, those features make the product useful beyond a one-off demonstration: a team can fit it into an existing process, hand work between people and AI, and keep the output connected to the systems where work actually happens.
The strongest use cases are Automating research and operations, Connecting company systems, Building internal AI agents, Deploying governed team workflows. A sensible rollout starts with a bounded workflow whose inputs and expected output are easy to inspect. Teams should test accuracy on their own data, decide when a person must approve an action, and measure whether the tool saves completion time rather than merely generating more material to review. Technical buyers should also evaluate identity controls, auditability, retention, export options, and how usage limits behave during busy periods.
Pricing found on the vendor site was: Pro: Starts at $37/month; 20,000 included credits; Enterprise: Custom. These figures are snapshots from the September 2026 research run and can vary with annual billing, region, taxes, consumption, seats, or negotiated enterprise terms. Usage-based plans deserve a small production trial because agent loops, model calls, browser time, credits, or workflow executions may grow differently from ordinary seat-based software. Where a page did not expose a dependable figure in curl-fetched HTML, the profile says so and is flagged for manual verification.
MCP compatibility is a prominent part of the product: Gumloop lists custom MCP server hosting and MCP server proxying, supporting both exposed tools and connections to other MCP services. This can reduce one-off integration work, but teams should still scope permissions and review every tool the agent can invoke. Overall, Gumloop is best evaluated against a real project using the listed capabilities, with a clear budget ceiling and success criteria. Its value is highest when the surrounding workflow, ownership, and review rules are defined before broad deployment.
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Strong no-code positioning: “understanding a task” is the prerequisite, not writing code Main caution: Credit-based usage needs monitoring; high-volume document or research workflows may require careful budgeting
Deploy intelligent agents directly in Slack, Microsoft Teams, and email that understand natural language requests and execute complex workflows behind the scenes, enabling teams to automate tasks through simple @mentions and conversational interactions.
Use Case:
Sales team tags @Gumloop in Slack to automatically research prospect companies, scrape websites for key information, analyze social media presence, and generate personalized outreach sequences based on extracted data.
Native support for Model Context Protocol with 50+ pre-built servers for GitHub, Slack, Notion, HubSpot, and custom server connectivity. Supports both native MCP execution through OpenAI/Anthropic and backend connector approaches for all model providers.
Use Case:
Development team connects custom MCP server to integrate with internal APIs, enabling agents to automatically create GitHub issues, update project documentation, and sync data across development tools through standardized protocol.
Sophisticated drag-and-drop interface supporting complex automation logic including conditional branching, parallel execution, loops, error handling, and AI processing nodes powered by multiple LLM providers with transparent credit consumption tracking.
Use Case:
Marketing team builds content moderation pipeline processing user-generated content through multiple AI models for sentiment analysis, toxicity detection, and automatic categorization with human review triggers for edge cases.
SOC 2 Type II certified platform with role-based access control, VPC deployments, comprehensive audit logging, SSO/SCIM integration, and organization-wide AI usage tracking across all systems including third-party AI tools.
Use Case:
Financial services company deploys automated customer onboarding workflows processing sensitive documents while maintaining regulatory compliance through audit trails, data retention controls, and secure multi-tenant infrastructure.
Advanced scraping capabilities using AI to automatically identify and extract relevant content from websites without manual configuration, handling JavaScript rendering, anti-bot measures, and adapting to website structure changes intelligently.
Use Case:
Competitive intelligence team monitors competitor pricing, product launches, and press releases across multiple websites, automatically extracting structured data for analysis while adapting to anti-bot measures and site redesigns.
Process large datasets through AI workflows with automatic rate limiting, error recovery, transparent credit consumption tracking, and bring-your-own-API-key support for cost optimization and budget control.
Use Case:
HR team processes thousands of job applications through AI screening workflows that extract qualifications, assess cultural fit from cover letters, rank candidates automatically, and generate interview scheduling recommendations.
Starts at $37/month; 20,000 included credits
Custom
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In 2026, Gumloop announced a $50M Series B led by Benchmark, accelerating investment in its enterprise Gumstack tier and multi-agent canvas. Native Model Context Protocol (MCP) support has been added so agents can plug into the broader MCP tool-server ecosystem without custom integration work. The pre-built agent library has expanded to include specialized templates for CRM management, meeting prep with cross-tool context, and call analysis that surfaces objection patterns and coaching insights. Slack and Teams conversational deployment has been deepened, positioning Gumloop agents as in-channel teammates rather than external dashboards.
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