Scale your output.
Keep your team lean.
MindLab installs a private AI company brain around your firm’s research materials, portfolio updates, approval rules, and institutional knowledge, so your team starts with structured, source-aware work instead of rebuilding context from scratch.
Private
Workspace-level separation.
Source-Aware
Evidence-aware outputs.
Approved
Human-controlled records.
Compounding
Memory improves workflows.
Analyst Leverage
Give Every Analyst
More Leverage
The best AI product for private capital will not be another chat window. It will be the workflow layer that remembers what the firm already learned.
01
Create Analyst Leverage
MindLab turns the repetitive first pass into a managed workflow, so associates start with structured briefs, risks, questions, and source context instead of blank pages.
02
Stop Paying for Rework
Every hour spent re-reading PDFs, reformatting notes, and rebuilding the same context is expensive leakage. MindLab captures the work once and makes it reusable.
03
Monitor What Changed
Compare new board materials, KPI files, and updates against prior company memory so watch items surface before the portfolio review starts.
04
Make Memory Compound
Approved work becomes company memory, source history, advisor-accessible context, and institutional knowledge instead of disappearing into folders, prompts, and inboxes.
The Implementation Pilot
Do not test AI in theory. Install one workflow on real materials.
Pick a concrete research or monitoring job your team already needs. MindLab installs the workflow, your team reviews the output, and recurring support only makes sense if the result saves real analyst time.
1. Diagnose
2. Install
3. Calibrate
4. Compound
Installed Workflows
The Workflows Your Team
Should Not Rebuild by Hand
MindLab starts with the outputs investment teams already need to produce again and again: target briefs, memo sections, portfolio updates, company memory, and approved advisor knowledge.
Target Brief Workflow
First-Pass Screening
Move from first look to usable internal brief faster. Upload CIMs, decks, websites, and notes; MindLab organizes the thesis, risks, metrics, sources, and open questions.
Memo Sections
Diligence Question Bank
Turn fragmented findings into memo-ready narrative, risks, diligence questions, and assumptions your team can edit, challenge, and bring to committee.
Portfolio Monitoring
Recurring Update Workflow
Prepare cleaner recurring updates by comparing new board materials, KPI files, and notes against the company context your team already approved.
Company Memory
Reusable Firm Memory
Stop losing context in email threads, folders, and one-off prompts. Approved work becomes living company memory your team can reuse across future decisions.
Radar and House Research
Compare themes, risks, and changes across companies so partners spot patterns earlier and analysts prepare sharper questions from the monitoring layer.
Capacity Model
Capacity-based plans, not workflow slot pricing.
Your team should not be punished for discovering more use cases. MindLab plans are governed by the real operating capacity needed to support your firm: AI usage, document volume, support time, deployment needs, and calibration effort.
If a workflow fits your capacity and improves the system, it should not be blocked by a made-up slot count.
Research
Monitoring
Memory
Advisors
Trust By Design
Private Capital Workflows Need Serious Controls
Investment teams cannot afford black-box automation or casual data handling. MindLab is designed around private workspaces, source-aware outputs, permission boundaries, and human approval.
Private Workspace Separation
Confidential materials stay inside your workspace and are used to operate your service, not to serve other customers.
Human Approval Controls
MindLab prepares drafts, organizes intelligence, and flags missing information. Your team approves final outputs and external communications.
Internal and External Boundaries
Internal advisors work from permissioned internal knowledge. External advisors only answer from knowledge your team has approved for that audience.
Evidence-Aware Outputs
Important claims can be tied to source materials, review flags, and missing-information markers where feasible.
Bring the Messy Materials
Your Team Already Uses
Investment work does not arrive in a clean database. MindLab starts with PDFs, decks, spreadsheets, notes, websites, and recurring updates, then turns that raw context into usable workflow output. We do not ask your team to rebuild the workflow around MindLab; we install MindLab around the materials your team already uses.
Deal Documents
CIMs, decks, PDFs, notes
Financial Models
Excel, CSV, KPI files
Operating Context
Notes, transcripts, updates
Benchmark Evidence
Built around the workflow, not just the model.
In internal benchmark testing on the same source package, MindLab scored 91 versus 70.5 for ChatGPT Deep Research on an 8-factor investment screening memo rubric.
Internal benchmark only. Results depend on source quality, workflow setup, implementation, review process, and evaluation criteria.
MindLab vs ChatGPT Deep Research
Buyer FAQ
Before AI Touches Your Firm's Workflows
Data, accuracy, implementation, pricing, and human approval, answered plainly.
Free Checklist
Find Your First Workflow Worth Installing
A practical checklist for identifying where your team rebuilds context, loses memory, repeats research, and spends expensive staff time on work a private AI workflow should prepare.
By requesting this guide, you agree to receive occasional updates.
Install the workflow
your team keeps rebuilding.
MindLab is accepting a small number of Implementation Pilots for investment and wealth teams. We pick a high-friction workflow, install the system around real materials, and continue only if the result proves useful.
