Use AI without losing control.We make it work.
We set up approved AI tools, build workflows with human review, and keep confidential work off public AI entirely — with a saved record your compliance team can stand behind. Working solutions, not a consulting deck.
Most teams want AI. Few know how to use it safely.
People are already using AI tools, but on personal accounts with no oversight.
Sensitive files and NDA materials end up in public AI tools that were never built for your compliance rules.
Teams buy too many tools and can't tell which ones actually help.
No one is saving what was asked, what AI said, or who reviewed it.
We fix that. Here's how.
Not one platform. Three lanes, each with a clear purpose.
We help you decide what goes where. Your team approves everything.
Approved AI assistants
Enterprise tools your team can approve, set up for real work.
Give your team ChatGPT Enterprise, Claude Enterprise, or Copilot configured for your workflows. First drafts, summaries, research, formatting. Public information only.
- Configured for your team's work
- Plain-English do's and don'ts
- Reusable prompts and templates
- Training and office hours
Repeatable workflows
Turn recurring tasks into consistent, reviewed processes.
Work your team repeats every week, automated with a human review step before anything is shared. Morning briefs, filing monitors, peer tracking. Same process, same checks, every time.
- Approved sources only
- Human reviews before output
- Warning flags for sensitive topics
- Saved record for every run
Private AI workspace
AI for confidential work, without sending files to public tools.
When work touches NDA materials, private company decks, or internal diligence, we build a private workspace. Your files never leave your environment. Every answer cites its source.
- Private model on your hardware
- Secure document workspace
- Source-cited answers
- Reviewer approval before export
Public information? Lane 1. Same task every week? Lane 2. Confidential or NDA? Lane 3. We help you decide. Your team approves.
We learn how you work. Then we build it with your people.
Workflow teardown & AI strategy
We sit with your team, understand what you do, what's public vs confidential, and where workflow friction and pain points are. Then we recommend where AI can add the greatest value.
Set up the right tools
Configure approved AI assistants for your team. Plain-English rules. No tool sprawl.
Build workflows
Turn recurring tasks into reviewed processes. Human checks before anything ships.
Train and maintain
Train your team. Keep tools current. Save records compliance can reproduce.
Sequenced, not open-ended: strategy first, then approved tools go live, then one workflow is built and piloted, and private AI is scoped when the work calls for it. Every phase ends with a written sign-off before the next begins.
Every AI-assisted task leaves a trail you can show compliance.
When someone asks how a piece of work was done, you answer from a saved package. Not from memory.
What was asked
The request, in the user's own words, with date and person.
Which tool answered
Which approved assistant, workflow, or private workspace handled it.
Sources used
The public links, exports, or private files the answer was based on.
AI's first draft
The model's output before any human edits, saved exactly as produced.
Human changes
What the reviewer changed, removed, or approved. And who did it.
Final record
Where the final version lives, who approved it, how to find it again.
Built, not just advised.
We don't hand you a slide deck and leave. We sit with your team, map the full chain, configure the tools, build the workflows, train your people, and stay current as AI changes.
Operator-led
Built by people who run businesses and ship software. Not career consultants.
Compliance-aware
We work around your compliance, legal, and IT rules. You keep approval authority.
Always current
Quarterly tool reviews. We keep you updated as models and vendors change.
Who we work with
Funds first. Serious teams of every kind.
Three worked examples, step by step.
Illustrative examples with fictional companies — the pattern is real, the names are not. Every engagement is tailored to your coverage, your sources, and your rules.
Model & scenario assistant
An analyst is building a public-company model and wants base, upside, downside, and break-point cases ready for PM review.
Public inputs only — filings, transcript, investor deck — each tagged and dated on a source checklist.
Scenario cases drafted from analyst-approved assumptions, with a clean assumption log.
Formula and workbook QA flags references and hard-coded numbers for review. Never auto-corrected.
Draft, assumptions, QA flags, and analyst edits saved as one package. Judgment stays with the analyst.
Morning portfolio brief
Before market open, the team wants a structured draft brief on overnight filings, headlines, and price action.
A scheduled step pulls from approved sources only — filings, news feeds, internal data.
The draft is written in your format, with passage-level citations and warning flags on weak claims.
An analyst opens the reviewer console, checks cited sources, edits, and approves before anything is shared.
The approved brief goes out, and the full run — sources, draft, edits, approver — is saved as one record.
Private diligence workspace
A confidential deck, diligence notes, and a management Q&A log arrive under NDA. The team wants to ask questions across all of it — without public AI tools.
Documents go into a private workspace with sensitivity labels and access controls.
Questions run only against the architecture your compliance, legal, and IT approved.
Every answer cites its source passages, so each claim is checkable against the file.
Higher-risk outputs route to a reviewer queue before export. The full trail saves with the deal.
Straight answers.
Yes. We build private AI workspaces so confidential files never go to public tools. Your compliance team approves the setup, and we sign NDAs before we see anything.
Tell us what your team does.
We'll show you where AI fits.
A 20-minute call. We'll learn your workflow, map the friction, suggest a lane, and outline a plan from AI strategy to deployment.