Maskin is a shared workspace where teams and their AI agents collaborate to turn insights into measurable business outcomes. It provides pre-built closed-loop workflows that connect signals from tools like HubSpot, PostHog, and social media into prioritized bets, with human review and automated execution. The platform is MCP-native, supports bring-your-own-model, and can be self-hosted or managed with EU and US data residency options.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Developer Tools
- Software Only
Funding
Founders
Product
Problem
Teams increasingly rely on AI for insights, but these outputs often live in private chats, never get shared, and fail to translate into better decisions. Companies invest heavily in AI tools yet see faster output without improved outcomes, as insights get lost in DMs and Slack threads, and decisions start from scratch each sprint. This disconnect means AI spend doesn't show up in the P&L.
Solution
Maskin provides a shared workspace where teams and AI agents work together to convert signals into decisions, actions, and measurable results. The platform uses pre-built closed-loop workflows that wire together agents, objects, and handoffs—for example, monitoring churn signals in PostHog or HubSpot, synthesizing closed-lost reasons into product insights, or scanning Reddit and X for market noise. Each workflow produces a "bet" that a human reviews and approves before agents execute, and outcomes are measured and fed back into the system's memory. Maskin is MCP-native, supports bring-your-own-model (Anthropic, OpenAI, Ollama), and offers both self-hosted and managed deployment options with EU and US data residency.
Target Audience
Primary customers are product, sales, and growth teams at technology companies that use AI tools and want to close the loop between insights and business outcomes, particularly those already using platforms like HubSpot, PostHog, or community monitoring tools.
Features
- Pre-built closed-loop workflows (e.g., Intel Monitor, Bet Strategist, Churn Monitor, CS Advisor) that connect agents and objects for automated signal-to-action pipelines
- Human-in-the-loop review and approval before agents ship changes, with outcome measurement and memory updates for continuous learning
- MCP-native architecture designed for the agentic era, enabling seamless integration with external tools and data sources
- Bring-your-own-model support for Anthropic, OpenAI, and Ollama, giving teams flexibility over model choice and cost
- Self-hosted open-source option or managed cloud with EU and US data residency, with tenant isolation for agent sessions and no training on workspace content
- Integration with HubSpot, PostHog, Reddit, X, LinkedIn, and community forums to capture signals across sales, product, and market channels