Decker

Decker is an AI-powered Deliverable Operating System (OS) purpose-built for mid to senior-level professionals in private equity, consulting, and financial services. It addresses the core challenge these professionals face: transforming messy, unstructured inputs such as call notes, transcripts, data dumps, and legacy templates into polished, review-ready deliverables. Unlike generic AI chat tools that produce only drafts, Decker provides specialized agents that handle the heavy lifting behind high-stakes outputs, including board decks, IC memos, financial models, proposals, and diligence trackers. The platform is designed for the work that happens after the initial prompt, offering structured workflows that allow users to direct AI like a senior operator rather than prompting randomly. Decker’s value proposition centers on a 4-pillar framework: Build, Learn, Belong, and Monetize. In the Build phase, users create editable PPTX decks, memos, models, and reports with expert help on demand. The Learn pillar, launching in July 2026, will offer operator-led cohorts and masterclasses focused on producing better work with AI. The Belong pillar will cultivate a peer network of consultants, investors, and operators for knowledge sharing and support. Crucially, the Monetize pillar enables users to redact, label, and package their deliverables as AI training data, turning one-off project work into recurring income through partnerships with model providers. Decker is already used by operators from MBB firms, Big Four, bulge-bracket banks, middle-market PE, growth equity, Fortune 500 companies, and family offices, with testimonials highlighting its ability to turn messy diligence notes into IC-ready narratives and improve user skill in directing AI effectively.

AI-Powered Deliverable Agents

Decker deploys specialized AI agents that go beyond simple text generation to handle the complete lifecycle of a deliverable. These agents are trained to perform research, analysis, narrative construction, financial modeling, and production formatting for high-stakes documents. Users can input raw materials like call transcripts, data tables, or previous reports, and the agents autonomously structure the content into a coherent, professional output. This feature dramatically reduces the time spent on repetitive formatting and synthesis, allowing professionals to focus on strategic thinking and client interaction. The agents are designed to produce outputs that are review-ready, meaning they require minimal editing before presentation to investment committees, boards, or clients.

Structured Workflows for Senior Operators

Unlike generic AI tools that rely on single prompts, Decker provides pre-built, operator-led workflows that guide users through the creation of complex deliverables. These workflows incorporate best practices from top-tier consulting and finance firms, ensuring that every deck, memo, or model follows an established logical structure. For example, a workflow for an IC memo might include steps for summarizing key findings, building a financial thesis, identifying risks, and formatting for executive presentation. This feature empowers mid-senior professionals to direct AI with precision, transforming them from prompt engineers into effective managers of AI agents. It also serves as a learning tool, helping users internalize better work structures over time.

Expert Help on Demand

When a deliverable requires additional expertise or a second set of eyes, Decker provides access to a network of experienced operators and subject matter experts. This feature is integrated directly into the platform, allowing users to request peer reviews, specialized analysis, or quality assurance checks without leaving their workflow. The expert network includes professionals from MBB consulting, private equity, and financial services who can validate assumptions, refine narratives, or provide technical input on complex models. This on-demand support ensures that even the most challenging deliverables meet the highest standards of accuracy and persuasiveness, reducing the risk of errors in client-facing or investment-critical documents.

Deliverable Monetization Engine

A unique cross-cutting feature of Decker is its ability to turn completed deliverables into a source of recurring income. Users can redact sensitive client information, label and categorize their work, and package it as AI training data. Decker facilitates this through partnerships with model providers who pay for high-quality, structured data derived from real-world consulting and finance work. This feature transforms one-off project outputs into a monetizable asset, creating a new revenue stream for individual professionals and firms. It also encourages the systematic capture and annotation of expertise, ensuring that institutional knowledge is preserved and can be reused or licensed over time.

Investment Committee Memo Creation

A private equity associate receives 50 pages of messy diligence notes, financial data, and interview transcripts from a target company. Using Decker, they upload all raw materials and select the IC memo workflow. The AI agents automatically synthesize the information into a structured narrative covering market analysis, financial projections, key risks, and investment thesis. The associate can then refine the output with operator-led prompts, request a peer review from a senior partner, and export the final memo as a polished document. This process reduces memo creation time from days to hours while improving narrative coherence and analytical depth.

Strategy Deck Production for Consulting Engagements

A strategy consultant at an MBB firm needs to produce a board-ready deck summarizing a multi-month engagement. They input raw data, prior analyses, and executive summaries into Decker. The platform’s agents build out a logical slide structure, generate data visualizations, and draft executive narratives. The consultant uses Decker’s workflows to ensure the deck follows the firm’s standard framework for strategy recommendations. They can also access expert help for a quality check on the final narrative. The output is an editable PPTX file that requires only minor customization, saving the consultant significant production time and allowing them to focus on client relationship management.

Financial Model and Sensitivity Analysis

A finance professional in a growth equity firm needs to build a DCF model with multiple sensitivity scenarios for a portfolio company review. Using Decker, they input historical financials, market assumptions, and key drivers. The platform’s modeling agents construct the model, calculate key outputs like IRR and NPV, and generate sensitivity tables. The user can direct the agents to test specific scenarios or adjust assumptions using structured prompts. The final model is delivered in an editable format, complete with documentation of assumptions and methodology. This use case accelerates model building from a multi-day process to a few hours while maintaining analytical rigor.

Diligence Tracker and Evidence Management

An investment team conducting due diligence on a complex acquisition uses Decker to manage the process. They upload data room documents, call notes, and third-party reports. Decker’s agents parse the information, populate a diligence tracker with key findings, flag missing evidence, and generate follow-up question lists. The platform creates a structured review table that the team can use to track progress and identify gaps. This use case improves the efficiency and thoroughness of the diligence process, ensuring that no critical issue is overlooked and that the final IC memo is supported by comprehensive evidence.

What types of deliverables can I create with Decker?

Decker is designed to produce a wide range of high-stakes business documents. This includes board decks, strategy decks, and IC memos for investment committees. It also handles memos such as briefs and board reads, financial models like DCF and sensitivity analyses, consulting proposals with SOWs and pricing, diligence trackers with evidence management, and research reports that are source-backed and executive-ready. All deliverables are produced in editable formats, such as PPTX for decks, ensuring you can make final adjustments.

How is Decker different from using ChatGPT or Claude for my work?

The key difference lies in Decker’s purpose-built design for professional deliverables. While ChatGPT and Claude provide a draft, Decker gives you the agents that ship the complete deliverable, the structured workflows to direct them like a senior operator, and access to expert support when you need a second set of eyes. It is built for the work that happens after the initial prompt, focusing on production, quality, and adherence to professional standards rather than general text generation.

Can I monetize the work I create on Decker?

Yes, monetization is a core pillar of the platform. Every deliverable you build or upload can be redacted to remove client-specific information, labeled for context, and turned into AI-ready training data. Decker facilitates this through partnerships with model providers who compensate you for high-quality data. This allows you to turn one-off project work into a recurring income stream, effectively licensing your expertise for future AI training.

Who is Decker designed for and what level of experience is required?

Decker is explicitly built for mid-senior professionals in private equity, consulting, and financial services. It is used by operators from MBB, Big Four, bulge-bracket banks, middle-market PE, growth equity, and Fortune 500 companies. The platform is designed to enhance the productivity of experienced professionals who understand the structure and standards of their deliverables. It is not a beginner tool; rather, it amplifies the efficiency and quality of seasoned practitioners.