a16z
Andreessen Horowitz
Unbundling the BPO
AI can take on work companies once outsourced, from invoice reconciliation to customer support. Kimberly Tan explains what it takes to deliver the result.
Read the essay
About
Your software factory.
Built on frontier AI, deployed on your most important work.
Marijn Brussel — Co-founder and CTO
Our mission
Autonomy for every business.
Mulholland manufactures and deploys advanced operational software as a service.
Our mission is to transform work inside companies to accelerate their progress and prosperity.
Now, with millions of workflows and processes suddenly up for grabs, we believe a massive share will metamorphose into something positive and abundant for everyone. We’re so excited to be living in this historic moment, to push the boundaries of what’s possible inside an organization, and to enable people to use technology to the fullest.
Our company
We are designers, engineers, and operators collaborating with domain experts across industries.
Mulholland team members, past and present, have worked or partnered with:
AI-native
services
for
the midmarket
Engineering and data
The data is the work.
We start with an audit of one workflow and the data it depends on. We trace records back to their sources, compare conflicting values, and check who can read or change them.
The result is a plan for what to clean, connect and secure before an agent can use it. Much of that work is traditional software engineering and data science, now with coding agents.
From data to action
A continuous production line in six stations. Inputs: source documents and stored data arrive together. Clean: standing sheets represent fields being organized and checked. Records: linked record blocks retain their source pages. Rules: layered grids represent coded business rules and tests, with an exception left open. Action: an agent works over the belt within a dashed permission boundary. Review: a person reviews the resulting records beside source papers and a change receipt. Pink marks show data moving through the line.
Data
We define the nouns, such as customers and invoices, their properties, and the actions the work allows. We classify and link records, remove duplicates, and flag missing values. Each record keeps its source and access rules.
Logic
We turn business rules into code and test the exceptions. Calculations, permissions, and approval steps give the agent something firmer than a prompt.
Action
The agent works from those records and rules, within the access we give it. People review the steps that need judgment, and each change leaves a record.
Further reading
The case for AI-native services
Two perspectives on building services around the work AI can do.
Bain Capital
Ventures
AI should finish the job
Faster contract review can help a business close deals sooner. Bain Capital Ventures makes the case for charging for completed work.
Learn the work
Start with evidence.
We work alongside the people doing the job. We map the process, the systems, the exceptions, and the hours lost between them. You bring representative documents, one workflow, and the people who know it best.
Build it together
The prototype comes first.
We start with one real workflow and a prototype that works. Your team tries the decisions it makes and changes them, working directly with our designers and engineers. The people who do the job shape it from the first walkthrough to launch.
Put it to work
Measure the whole job.
We connect the systems, agree on who approves what, and roll out the deployment. We take a baseline with your team first, then measure the whole workflow again after launch. Preparation, review, exceptions, and corrections all count.
What we build on
See how MarzyOS works
How we map a business
Read about the ontology