Skill UI

A professional tool for building Discounted Cash Flow (DCF) valuation models directly in Excel. This skill generates a comprehensive, multi-sheet model including FCF projections, WACC calculations, terminal value analysis, and two-way sensitivity tables. It is designed for investment banking and corporate finance professionals needing to determine intrinsic or enterprise value.

This workflow is designed for comprehensive industrial asset and location management within the MaintainX platform. It enables users to establish detailed facility location hierarchies, register complex equipment assets (including serial numbers and models), query asset lists, and initiate maintenance work orders. Use it for managing equipment lifecycles, tracking physical assets, and maintaining structured facility records.

Build comprehensive 3-5 year financial models essential for startup planning and fundraising. This skill meticulously projects revenue using cohort-based methods, details cost structures (COGS, S&M, R&D, G&A), plans headcount, and performs detailed cash flow analysis. It calculates critical metrics like LTV, CAC, and burn rate, providing three scenarios (conservative, base, optimistic) for robust strategic decision-making.

Build comprehensive 3-5 year financial models crucial for early-stage startups. This guide covers revenue projections using cohort-based methods, detailed cost structuring (COGS, S&M, R&D, G&A), robust cash flow analysis, and multi-scenario planning (Conservative, Base, Optimistic). It provides the quantitative foundation needed for fundraising, strategic planning, and investor presentations.

This guide provides a comprehensive framework for early-stage companies to track, calculate, and optimize their key performance indicators (KPIs). It covers best practices for various startup business models, guiding teams from the initial seed stage through to Series A funding. Use this skill when developing, analyzing, or refining a structured startup metrics strategy.

This skill is designed to help users optimize the operational costs of the TwinMind AI platform. It provides detailed usage monitoring and guidance for selecting the most appropriate subscription tier (Free, Pro, or Enterprise). Users can manage advanced features such as high-accuracy transcription (Ear-3) and AI summarization across multiple models (GPT-4, Claude, Gemini), ensuring efficient resource utilization and cost control for large-scale meeting AI operations.

A comprehensive guide to setting up TwinMind Enterprise for large-scale corporate environments. This includes configuring on-premise deployment, integrating custom AI models (GPT-4, Claude, Gemini), and enabling Single Sign-On (SSO) using Okta. It is essential for implementing strict Role-Based Access Control (RBAC) and managing team-wide meeting intelligence and transcript sharing in a secure, enterprise setting.

Guides creation and revision of investor-facing pitch decks, memos, financial models, and accelerator answers, stressing consistent facts, clear assumptions, and cross-checked funding plans whenever teams prepare fundraising documentation.

This guide provides expert knowledge on Revenue Operations (RevOps), focusing on optimizing the handoffs and systems that connect marketing, sales, and customer success. It covers defining lead lifecycles, implementing robust lead scoring models (combining fit and engagement), setting MQL-to-SQL SLAs, and establishing single sources of truth to ensure the entire revenue funnel operates efficiently and consistently.

This skill provides comprehensive strategies and technical blueprints for monetizing digital products, especially SaaS platforms. It covers everything from defining advanced pricing models (freemium, value-based pricing) and optimizing revenue flows (LTV/CAC, churn prevention) to practical Stripe integrations. Use it when you need to set up subscription plans, process webhooks, or implement automated billing cycles for your software.

A systematic framework for launching and validating new products and business models. It guides users through the Build-Measure-Learn loop, emphasizing validated learning over vanity metrics, and structuring Minimum Viable Product (MVP) experiments to test core assumptions and determine if a pivot or perseverance is necessary.

Helps founders and GTM teams set metrics, build tiers, and manage margins for AI products by grounding pricing choices in compute cost realities, credit systems, and buyer personas so revenue models scale with value.