Tamarack Capital Partners

Operational AI Integration

Build an AI operating system that makes your team faster at the work that actually matters.

Prepared for

Tamarack Capital Partners

Primary Contact

Heather Turner

Chief Executive Officer

Prepared by

Fractional Venture Partners

Deployment Timeline

6–10 Weeks

01

Overview

Investment firms run on information. That part is obvious.

What’s less obvious is how much of that information never gets used. CIMs sit in email threads. Meeting notes disappear into notebooks. Financial models live in spreadsheets that only one person understands. The intelligence exists, but it’s fragmented across too many places.

Most firms know AI can help with this. The challenge is figuring out where to start and how to make it stick.

This engagement builds an AI operating system designed around how Tamarack actually works. The goal is simple: make the team faster at deal analysis, reporting, and internal coordination without adding complexity.

When it works, the firm operates with more speed, better visibility, and less wasted effort.
02

Deployment Scope

The system we’re building connects directly to how Tamarack handles acquisitions and asset management. It’s not a generic AI rollout. It’s infrastructure built around your actual workflows.

Architecture

AI Operating System

1

Inputs

broker emailsCIMs / investment materialsfinancial reportsoperator updatesmeeting transcripts (PLAUD)investor communications
2

AI Processing Layer

ChatGPT Team / Business

writing, analysis, and custom GPT development

Claude for Business

long-form document analysis and reasoning

3

Custom GPT / AI Agent Layer

custom GPT assistants defined during the AI workflow audit

4

Workflow Outputs

deal summariesinvestment memosasset performance reportsinvestor updatesmeeting intelligenceaction items
5

Automation Layer

workflow integrations

deal intake pipelines

reporting automation

meeting intelligence workflows

03

Phase 1 — AI Workflow Audit

We start with an audit. Not a theoretical exercise — a practical one.

Process documentation is useful, but it rarely captures how work actually gets done. To build AI systems that fit, we need to understand how information moves through the firm, where things get stuck, and what takes more time than it should.

This means looking at how deals get analyzed, how reports get built, where documents live, and how decisions get made. The details matter.

By the end of this phase, we have a clear blueprint for what to build and in what order.

What We Do

  • map acquisitions workflows end to end
  • map asset management workflows
  • review real materials — CIMs, financial reports, memos
  • identify repetitive tasks and bottlenecks
  • find the highest-value AI opportunities
  • design the architecture for Tamarack’s system

Setting Up the Tools

We also get the AI environment configured during this phase. Most teams are using a mix of tools already, often inconsistently. We clean that up and make sure everything is set up properly before we start building.

ChatGPT Team / Business

The main workspace for writing, analysis, and building custom GPT agents.

Claude for Business

Better for long documents. We use it for CIM analysis and financial reporting.

PLAUD Meeting Intelligence

Captures meetings and turns them into searchable, analyzable transcripts.

Note: These tools have their own subscription costs, paid directly to each provider. Our pricing covers the audit, configuration, training, and custom development work — not the underlying tool subscriptions.

What You Get

At the end of the audit, Tamarack receives:

  • workflow maps for acquisitions and asset management
  • recommended tool stack and configuration
  • prioritized list of custom GPT opportunities
  • prioritized list of automation opportunities
  • a roadmap showing what to build before the workshop and what comes after
The roadmap is the key deliverable. It tells you exactly what to build first and why.

AI Workflow Audit

$7,500

04

Phase 2 — AI School Implementation Workshop

Most AI training is generic. It teaches you how the tools work, but not how to apply them to what you actually do every day.

This workshop is different. It’s built around Tamarack’s real workflows and systems. The examples are yours. The exercises are based on work you already do. By the end, the team knows how to use AI on the things that matter most to them.

What We Cover

  • how to use ChatGPT and Claude effectively
  • working with custom GPT assistants
  • analyzing CIMs and investment materials
  • writing investment memos with AI assistance
  • getting value from meeting transcripts
  • spotting automation opportunities as you work

Training Interface

We deploy a companion interface during the workshop. Participants use it alongside the session to follow exercises, test prompts, and ask questions in real time.

It stays available after the workshop, so the team can reference it as they start applying what they learned.

AI School Workshop

$10,000

05

Custom GPT Assistants

Generic AI tools are useful, but they only get you so far. The real leverage comes from building agents that understand your business.

Custom GPTs are trained on Tamarack’s processes, documents, and reporting formats. They work like digital analysts who already know how you do things.

The specific agents we build get defined during the audit. That’s intentional. We want to build what actually matters, not what sounds good on paper.

Most firms end up with three to five agents forming the core of their AI operating layer. Common areas include:

  • deal analysis and CIM review
  • investment memo drafting
  • asset management reporting
  • investor communications
  • document and agreement review

These are illustrative. What gets built depends on what the audit uncovers.

Pricing

Starting at:

$4,000 per GPT

3 agents

good starting point for most teams

5 agents

full coverage across acquisitions and asset management

Bundle pricing applies when multiple agents are deployed together.

06

Workflow Automation

Some workflows make sense to automate fully. AI outputs trigger downstream processes without anyone needing to copy-paste or reformat anything.

Common examples: meeting transcripts automatically feeding into action item trackers, broker emails routing into deal intake systems, or asset data populating investor reports.

That said, we usually recommend teams get comfortable with AI-assisted workflows before jumping straight to automation. There’s a calibration period where you refine the outputs and make sure the system is actually doing what you need.

Automation opportunities get identified during the audit. We implement them selectively as the team gets comfortable.

Typical builds range from:

$8,000 – $12,000

depending on complexity

07

Ongoing AI Operating Support

AI systems evolve. The team finds new use cases, runs into edge cases, and wants to improve what’s already built. That’s normal.

Some organizations keep us on as an ongoing operating partner to support that evolution. We help optimize GPT assistants, identify new automation opportunities, refine workflows, and answer questions as they come up.

Support runs through a custom interface where the team can submit questions and get help as they continue integrating AI into daily operations.

Monthly retainers range from:

$6,000 – $11,000 per month

depending on support level and system complexity

08

Engagement Summary

Phase 1 — AI Workflow Audit

$7,500

Phase 2 — AI School Workshop

$10,000

Optional Builds

Custom GPT assistants

starting at $4,000

Workflow automations

typically $8,000–$12,000

Getting Started

We start with the audit. That’s where we figure out what makes sense to build and in what order.

If you’re ready to move forward, reach out and we’ll get it scheduled.