A readout to a client's leadership team
AI consulting and implementation

Production AI
you can trust.

We go beyond the forward-deployed engineer. We find where AI pays in your business, embed engineers with your team to build it, and stay until it runs in production, governed and owned by your people.

250+ production systems since 2016  ·  SOC 2 Type II  ·  New York

Two ways to start

For portfolio companies

We find the right AI, ready your data, and build it

Discovery first, to find where AI pays. Then the data infrastructure that makes AI accurate and trusted. Then forward-deployed engineers embed with your team to build it, and your team owns it.

For operating partners

Find the best AI returns in your portfolio

We assess every portfolio company and rank where AI will return the most, so you know where to invest first. What ships at one company carries to the next.

We build on
ClaudeDatabricks
Runs in your cloud
AWS
Azure
SOC 2 Type II
Investment firms we work with
Operators we have built for
Where you are

Five levels of AI. Each one is built differently.

A chatbot, an agent that runs a workflow and a system that runs an operation are different builds: different data, different guardrails, different cost. We name the level first, then build for it, so each workflow gets the system it needs and what you spend matches what you get back.

  1. Level 1Chat & Copilot
  2. Level 2Connected Intelligence
  3. Level 3Workflow Agents
  4. Level 4Orchestrated Systems
  5. Level 5Autonomous Operations

Level 3 is where cost per seat becomes cost per task.

Level 1Chat & Copilot
Level 2Connected Intelligence
Level 3Workflow Agents
Level 4Orchestrated Systems
Level 5Autonomous Operations
How we work

Three stages. Start where you are.

We learn your business and your data. We tell you what is worth building. We build it with your team and stay until it runs. Every stage is priced up front.

  1. Stage 1 of 3

    Assess

    We look at your data and how work gets done today, read-only. You get a ranked list of what to build, with the savings and the time to value. Two to four weeks.

  2. Stage 2 of 3

    Build

    Forward-deployed engineers embed with your team and build the first workflow in your cloud, on your systems, into production.

  3. Stage 3 of 3

    Scale

    We stay until it runs on its own. Then we take it to the next function or the next company.

Alongside every stage

Advisory. A senior AI lead on retainer for board reporting, governance and vendors.

Your data stays in your tenant. You get a readout every week. We are SOC 2 Type II.

What AI changes

Real workflows, before and after.

Real workflows from client engagements. Software now does the steps a team did by hand. A person reviews the exceptions.

Cost savingLevel 3
Private equity firmConsumer-focused fund · deal team

CIM review cycles 4x faster

Reviewing a confidential information memorandum

BeforeBy hand
After4x faster
Analysts read each CIM end to end
Agent extracts terms, financials and risks
Key terms re-keyed into the model
Populates the model and flags gaps
The whole deal team works the queue
The deal team reviews the exceptions
People do every step
Agent runs it, a person reviews
Deal teams open each review with the company, market and comparable data already assembled, so review time goes to judgment.
Reads fromPitchBookIntapp DealCloudDatasiteMicrosoft 365
Runs onClaudeDatabricks
Read the case study

Level 3 means an agent runs the workflow and a person reviews. See the five levels

Client story

Hours of reporting, now minutes.

DentalXChange, backed by Bregal Sagemount, built its reports by hand. Now they run in minutes, and the team sees operations in real time. Hear it from them.

Minutesreporting, down from hours
Real timeoperational visibility
See it in one workflow

Five levels. We start from yours.

Follow one workflow up the five levels. At Level 3, software runs the work and a person reviews the exceptions. We take each workflow only as far as its P&L justifies.

One workflow, five levels · the month-end close

Level 3: Workflow Agents

An agent runs the close end to end. People review the exceptions it flags and approve.

Peoplereview two steps
Agentsrun four steps
Pull actualsAgent pulls and reconcilesAn agent does this step.
Compare to budgetAgent computes and ranksAn agent does this step.
Draft commentaryAgent drafts the commentaryAn agent does this step.
Investigate exceptionsAgent flags 4; a person digs inAn agent does this step and a person reviews it.
Review and approveController approvesAn agent does this step and a person reviews it.
Send the board packAgent assembles and sendsAn agent does this step.
Who does the work67% agents · 33% people
Impact at level 3Compared with Level 1
Time to close
Before: 14 days2 days
People hours per close
Before: 12024mostly review
Est. savings per year$98K
Hours saved at $85/hr loaded cost, 12 closes a year. One workflow of many.
You pay pertask

Cost per seat becomes cost per task. This is the line between a faster headcount and a cheaper function.

The marker climbs on its own, or click a level. Level 3 is where cost per seat becomes cost per task.

A working session around a conference table
A whiteboard session with a client team
An engineer at a keyboard with a colleague
Who shows up

Forward-deployed engineers, embedded in your team.

Our engineers don't hand you a deck. They join your team, work in your systems, and build next to your people until the workflow runs. The people who design it ship it. No hand-off to a junior team after the sale.

production systems since 2016
250+
weeks to know where AI pays
2 to 4
Pricing and timelines

What it costs and how long it takes.

Three stages and an advisory retainer. Every price is published.

  • Find where AI paysStage 1 of 3

    Assess

    Know where AI creates value.

    Time
    2 to 4 weeks
    Price
    $25K to $50K

    A free diagnostic first, then the full readout: opportunity map, ROI model, 90-day plan, board-ready.

    Explore Assess
  • Build the first workflowStage 2 of 3

    Build

    Ship the first workflow.

    Time
    3 to 6 months
    Price
    $75K to $350K

    A senior pod takes one function to Level 3 (software runs the workflow, people review the exceptions) in production. First workflow live by day 100.

    Explore Build
  • Repeat it across the portfolioStage 3 of 3

    Scale

    Repeat it across the book.

    Time
    Per year, annual agreement
    Price
    $250K to $1.5M+

    What ships at company one is the starting point at company two. 3 to 15 companies.

    Explore Scale
  • A senior AI lead on retainerAlongside every stage

    Advisory

    Fractional AI leadership.

    Time
    Monthly, 3-month minimum
    Price
    $15K to $30K / mo

    A Portfolio Success Partner for board reporting, governance, and vendor management.

    Explore Advisory
Client results

What we built, and what it did.

I've worked with at least a dozen technology teams, and without question the Blue Orange team stands above them all. Most valuable is the transparency they provide about progress and deadlines.
Lauren B. · Point72 Asset Management
Their input and influence has gone directly to improving our bottom line.
Shawn Massie · CTO, Quext
Who we work with

The sectors we work in.

Operationally complex, data-heavy businesses, and the PE firms that own them.

FAQ

Frequently asked questions

Blue Orange builds trusted production AI for PE-backed companies: we find where AI pays, ready the data, and embed forward-deployed engineers to build it. We build on Claude and Databricks, with senior engineers embedded wherever the portfolio is.

Financial services, healthcare, manufacturing, CPG and retail, and technology and SaaS. Most of our clients are PE firms and their portfolio companies: operationally complex businesses that need AI running in production, not in a demo.

Assess takes 2 to 4 weeks. Build runs 3 to 6 months, with the first workflow live in 100 days. Scale is an annual program across the portfolio. Advisory is a monthly retainer for a senior AI lead.

Forward-deployed engineers, not a pyramid of junior staff. Our engineers embed with your team, work in your systems, and build next to your people. The people who scope the work build it, and we tie our fees to results in production.

Three stages, with advisory alongside. Stage 1, Assess, finds where AI pays in two to four weeks. Stage 2, Build, embeds forward-deployed engineers with your team to put the first workflow into production. Stage 3, Scale, repeats it across functions and portfolio companies. Advisory is a senior AI lead on retainer. Every stage is priced up front, and you start at the stage you are at.

Five levels of AI maturity. L1, people use a chatbot. L2, the chatbot knows your data. L3, software runs a whole workflow and a person reviews the exceptions. L4, several agents coordinate. L5, the system starts its own work under policy. Most companies are at L1. We move them up one workflow at a time, as far as the workflow is worth taking.

Next step

Let's find where AI pays.

A read-only look with an engineer who has built this before. You leave knowing your level and what is worth funding.