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For the whole company

Keep your team on the cutting edge of AI.

We test new AI on your team’s own past work, set up what wins in the tools you already use, and train each person on it. When better AI ships, we do it again.

See it in 2 minutes

How Orcapo works, start to finish.

Why teams fall behind

AI gets better every month. Your team’s tools stay the same.

01

Switching is a project.

Every new tool means rebuilding automations and changing how people work.

02

Everyone has to relearn.

Each switch means training people again, so most teams never make it.

03

Hype is hard to spot.

New AI ships every week. Nobody has time to test what is real on your own work.

Where we start

The work we test first on teams like yours.

We confirm yours in the first round.

01

Sales

Today

Research, emails and CRM updates by hand.

After a round with Orcapo

Saved setups for each seller, on your real accounts.

02

Support and operations

Today

Replies, reports and intake by hand.

After a round with Orcapo

Drafts from your own docs and data, checked by your team.

03

Everyone else

Today

AI seats that few people use.

After a round with Orcapo

The right tool for each role.

How it works

We work in rounds. Each one keeps your team on the best AI.

  1. 01Map
  2. 02Test
  3. 03Roadmap
  4. 04Set up
  5. 05Train
  6. 06Next round

01 · Map

We learn how your team works today.

It starts with one email. You connect your tools as read-only, and each person fills out a 5-minute form. We map every role and find where the time goes.

Company

An example company, 30 people

Tools you pay for

ClaudeChatGPTCopilotZapier

Your rules

Approved tools only

No customer data in public AI

Roles

Time on repeated tasks

Sales

First: Account research

Support

First: First replies

Operations

First: The weekly report

People

AI experience, person by person

AK

Account executive

New to AI · 18 calls a week

MT

Account executive

Uses ChatGPT daily · 6 calls a week

From a 5-minute form each person fills out.

Example

02 · Test

We test new AI on your own past work.

Every week we go through new AI tools, models and research. We run the best options on your past work, in a safe copy of your tools. An option passes only if it beats how you work today, and your team picks the better result without knowing which tool made it.

Test · Sales

50 past examples
  • Today’s way

    How your team does it now

    Baseline
  • Option A

    A new AI agent

    Not better
  • Option B

    A newer model, set up for you

    Beat today
  • Option C

    A startup’s new tool

    Too many errors

Blind vote

Your team picked Option B 9 times out of 12, without knowing which tool made each result.

Example

03 · Roadmap

You approve every change first.

The winners go into a roadmap. Each change shows the test it won. Nothing goes live until you say yes.

Roadmap · An example company, 30 people

Waiting for your approval

The main idea: each change won its test on your own past work. Nothing starts until you approve it.

  1. Weeks 1 and 2 Sales: Account research ClaudeYour CRM
  2. Weeks 3 and 4 Support: First replies ClaudeYour help desk
  3. Weeks 5 and 6 Operations: The weekly report CopilotZapier
  4. Weeks 7 and 8Automations you approve

Needs your OK

Which tools may see customer data.

Which AI seats to add, and which nobody uses.

Approved
Example

04 · Set up

We set it up in the tools you already use.

The automations and agents run in your own accounts. A person checks the work before it reaches a customer.

Set up from what won

1

Drafts replies for your team to send

Drafts only, in your own email

AI agent
2

Updates your CRM from call notes

Runs in your own CRM

Automation
3

Drafts the weekly report

Runs in your own sheets

Automation

Approvals

Before anything runs

EEmployee Approved
MManager Approved
OOwner Approved

The owner approves anything that touches customer data.

Example

05 · Train

Each person learns on their own work.

Each person gets a short guide made from their own work. Then they practice on a safe copy of their tools, with an AI coach that answers questions. It is not a generic course.

Practice lab

Sample data
  • Sample task: a customer email
  • Sample task: an email with two requests
  • Sample task: a weekly report

Draft the reply with your saved setup.

Paste the email into your saved setup.

Done. The reply looks right.

Read the email again. How many things does the customer ask for?

Two requests means two answers, every time.

Live coach · next to Gmail

On
Draft with your setup

Step 2 of 3: draft the reply

Does the attachment matter?

Yes. Open it first, then draft.

Show me onceor do it yourself

Example

06 · Next round

When better AI ships, the next round starts.

Every month we flag new AI worth testing, and you pick up to three. If one wins its test on your work, it replaces the old tool. If nothing wins, nothing changes.

Monthly check-in

New AI worth testing for your team

Using this round’s change

Sales 9/9
Support 9/10
Operations 8/8

Pick up to 3 to test

  • A newer model for account research
  • A new tool for first replies
  • An agent for the weekly report

If one wins its test, it replaces the old tool. Nothing changes until you say yes.

Example

Before and after

What changes for your team.

Before

Tools picked years ago, and never revisited

AI seats that few people use

Guessing which new tools are real

Training that is not about their work

After

The tool that won on your own work, for each task

Set up in the tools you already use

Each person trained on their own work

A new round whenever better AI ships

Who we are

Two Berkeley founders who build with AI every day.

Google and MIT

Our CTO is first author on AI research with both.

Databricks

Our CEO was an AI and machine learning consultant there.

Berkeley SkyDeck

Supported by Berkeley SkyDeck, Founders Inc. and UC LAUNCH.

Abhiraam Eranti

Abhiraam Eranti

Co-founder and CTO

First author on AI research with Google and MIT. Technical lead on a U.S. Treasury app for 100,000+ blind and low-vision Americans.

Waleed Chaudhry

Waleed Chaudhry

Co-founder and CEO

AI and machine learning consultant at Databricks. UC Berkeley Haas School of Business.

We also built LessonOrca, an AI tutoring company that writes a plan for each student and rewrites it after every session. Orcapo uses the same system for teams at work.

Questions

Questions

Is this a course?

No. We find, test and set up the tools, then train each person on their own work, in the tools they already use. There is no course library.

Why not just buy ChatGPT or Claude seats?

Seats give your team a tool. Nobody picks the tasks, tests the results or checks that people use it. An AI vendor will also recommend its own tools. We recommend whatever wins on your own work, even when that is a rival’s tool.

How often do our tools change?

Only when something wins its test on your work and you approve it. Most months, little changes. We keep the screens your team knows wherever we can.

What happens to our data?

You connect your tools as read-only, and we test new AI in a safe copy, so nothing real can break. Automations run in your own accounts, and you keep everything we set up.

Who approves changes?

You do. Every change shows the test it won, and nothing goes live until you say yes.

How much time does it take each person?

A 5-minute form at the start, a short vote on test results, and about 15 minutes of training for each new tool.

What happens on the audit call?

A short video call. We ask how your team works today and show you where better AI would save the most time. There is nothing to sign.

Our promise

We only recommend a tool if it beats your current one on your own work.

Nothing changes until you say yes.

Book a free AI audit.

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