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For sales and BD teams

Keep your sales team on the cutting edge of AI.

We test new AI on your own leads and emails, set up what wins in your CRM and inbox, and train each seller 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

Account research before a call

Today

Websites, filings and LinkedIn, read by hand.

After a round with Orcapo

A research brief from a saved setup, checked by the seller.

02

First emails and follow-ups

Today

Written one at a time from a blank page.

After a round with Orcapo

Drafts from your own best emails, edited and sent by the seller.

03

CRM notes and pipeline updates

Today

Typed in after every call.

After a round with Orcapo

Call notes turned into CRM updates for the seller to check.

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 sales team, 9 people

Tools you pay for

ClaudeChatGPTGmailYour CRM

Your rules

Approved tools only

No customer data in public AI

Roles

Time on repeated tasks

Account executives

First: Account research

SDRs

First: First emails

Sales ops

First: Pipeline updates

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 · Account research before a call

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 sales team, 9 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 Account executives: Account research ClaudeYour CRM
  2. Weeks 3 and 4 SDRs: First emails ChatGPTGmail
  3. Weeks 5 and 6 Sales ops: Pipeline updates ClaudeZapier
  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

Writes a research brief for each new meeting

Runs in your own Claude and calendar

AI agent
2

Turns call notes into CRM updates

Runs in your own CRM and Zapier

Automation
3

Drafts follow-ups for the seller to send

Drafts only, in your own Gmail

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 account: a regional hospital group
  • Sample account: a battery maker
  • Sample account: a city transit agency

Write a one-page brief before the first call.

Paste the account into your research setup.

Done. The brief looks complete.

Check the sources. Which line has no link?

Every claim in a brief needs a source you can open.

Live coach · next to Gmail

On
Draft from your best emails

Step 2 of 3: draft the follow-up

Should I mention the pricing we discussed?

Only if it is in your call notes. Check them first.

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

Account executives 4/4
SDRs 2/3
Sales ops 2/2

Pick up to 3 to test

  • A newer model for account research
  • A new tool for first emails
  • An agent for pipeline updates

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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