We find the right AI, ready your data, and build it.
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. In your systems and your cloud, building on Claude and Databricks.
Azure
Where Blue Orange creates value.
Start where you are: we work out what is worth building and in what order, build it with your team, and expand only when the case for value is clear. Below, the three ways we work with you, then the four things we build.
Figure out where AI pays
- Start hereFree diagnosticA senior engineer, read-only access. You leave knowing where you are on our five levels of AI maturity and which workflows to build first.
- Two to four weeks · Stage 1 of 3AssessTwo to four weeks with your operating team: where AI pays in your company, ranked, with the savings, the plan and a board-ready readout.
- How we see where you areThe five levelsFive levels we defined to show a company what kind of system it needs, in plain terms.
Build it with you
What we build
- What we buildAgentic automationSoftware that runs a whole workflow, with a person reviewing the exceptions and a full audit trail.
- What we buildData platformOne governed source of data underneath, so the AI is right.
- What we buildAnalytics & MLForecasts and models built on your real data.
- What we buildAI context layerThe AI context layer that dashboards and agents both read.
Run it and repeat it
- Across the portfolio · Stage 3 of 3ScaleTake what worked at the first company to the next ones, with one governance standard across the portfolio.
- A senior AI lead on retainer · Alongside every stageAdvisoryA senior AI lead on retainer: board reporting, governance, and the vendor decisions.
- Half-day, full-day or multi-weekAI trainingHands-on Claude training on Claude Code, Cowork and agents, run on your own repos and workflows, with the controls set before day one.
Inside three portfolio companies. What it pays, and when.
A $200M precision components manufacturer
- Year 1
- $2.1M
- By year 2
- $5.3M
- By year 3
- $8.6M
Spend classification and supplier quotes
Impact$1Ma year · up to $2.5MAddressable spend runs about 25% of revenue. We count 2% saved; the band runs to 5%.
Time to value8 to 16weeksStarts with the spend data in the ERP. Savings arrive as supplier contracts come up for renewal.
Quote margin guidance and discount guardrails
Impact$1.2Ma year · up to $2.4MQuoted work runs about 60% of revenue. We count one point of margin recovered on it.
Time to value8 to 14weeksUses the quote and order history in the ERP and CRM. The first weeks go to the margin rules.
Order intake from emailed purchase orders
Impact$1Ma year · up to $1.4MOrder entry runs about 1.2% of revenue. We count half that effort removed, then 15% off for overlap.
Time to value6 to 10weeksReads the inbox the team already works. No new data foundation needed.
Illustrative companies, sized from the bands in measured engagements. Low end of every band at the company’s revenue; the third use case counted at 85% because it shares data and people with the first two; each one paying from the late end of its window and at full rate a quarter later. Value before the Build investment. Ranges, not promises.
Outcomes we have shipped, not slideware.
- Operations · Level 3500xfaster rewriting of requirements to the INCOSE standardFord rewrites 13,000 engineering requirements in 4 hours instead of 2,170Ford Motor Company
- Case study10xmore data pipeline throughputBooking.com moved pricing and inventory data from batch to under a second
- Operations · Level 220%more accurate package volume forecastsFedEx improved package volume forecast accuracy by 20% with production ML
Three stages and an advisory retainer, with published ranges.
- 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
Common questions.
What does Blue Orange do?
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. The work splits into two groups: the first figures out where AI pays; the second builds it and keeps it running.
What are the three stages?
Three stages with published prices, and advisory alongside: Assess (know where AI creates value), Build (ship the first workflow) and Scale (repeat it across the book), with Advisory (a senior AI lead on retainer). Assess delivers its readout in 2 to 4 weeks, Build embeds forward-deployed engineers to put the first workflow into production, and Scale covers 3 to 15 companies.
How does Blue Orange figure out where AI will pay?
It starts with the diagnostic: a read-only read of your data and AI stack that places you on our five AI maturity levels (L1 to L5) and hands you a ranked list of workflows, complimentary for qualified companies. Assess then delivers an opportunity map, ROI model, 90-day plan and board-ready readout in 2 to 4 weeks, at a fixed $25K to $50K.
What does Blue Orange build?
Four capabilities: agentic automation (production AI agents for operator workflows, with human-in-the-loop controls and production monitoring), a data platform (fragmented systems unified into one governed lakehouse), analytics and ML (forecasts and models built on your real data) and an AI context layer (one meaning for your data, read by dashboards and agents). The Build stage takes one function to Level 3 in production.
What results has Blue Orange delivered?
Three sit on this page. Ford rewrites 13,000 engineering requirements in 4 hours instead of 2,170 with an LLM pipeline on its private Azure tenant. Booking.com moved pricing and inventory data from batch to sub-second with a change data capture pipeline into Snowflake. FedEx improved package volume forecast accuracy by 20% with a machine learning environment on Databricks.
Does Blue Orange work with Databricks and Claude?
Yes. We build on Claude and Databricks, and the work runs in your cloud, on AWS or Azure. FedEx's forecasting environment, on this page, runs on Azure Data Lake and Databricks, and so do Bregal Sagemount's deal sourcing system and TechSmith's data layer.
How much do Build, Scale and Advisory cost?
Build is $75K to $350K, 3 to 6 months. Scale is $250K to $1.5M+, per year, annual agreement. Advisory is $15K to $30K / mo, monthly, 3-month minimum. Milestone billing: you pay for progress, not hours. Assess is $25K to $50K, 2 to 4 weeks.