A TriEdge Investments company
Build forward from within.
Someone in your operation is still keying in orders and chasing what's missing by hand. We work inside operations-intensive businesses to see how that work is actually getting done, find where technology can create value, build it, and see it through to adoption.
How we work
We start with your business, not with the technology.
Models can already reason. What companies lack is the people, and the knowledge of what the technology can now do, to get it running inside real work.
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01
Observe
We work alongside the team and see how the work actually happens. That is how we find every opportunity, including the ones no one would have thought to ask for.
Outcome Every opportunity, with a value on it
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02
Prioritize
We put a value on each opportunity and work with the leadership team to agree what is worth building, in what order, and who owns it.
Outcome A plan the leadership team has agreed to
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03
Build
We build to the need: extending existing systems, building new, or configuring our platform. Each workflow can flag, recommend or act, with the level of autonomy set by the business.
Outcome A system in production, run by us
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04
Adopt
We stay through rollout, working with the teams doing the work to change how it is done, until the system is delivering the value that was agreed.
Outcome A result visible in the P&L
We look for three kinds of value.
- Lower cost
- Remove work that does not need a person.
- More capacity
- Free the team to support more customers, locations or revenue.
- New capability
- Do things the business could not do before.
What we take on
Every dollar figure is calculated, never generated.
Order entry, finance, revenue cycle, client operations, supply chain: work a business runs on, still done by hand. A wrong number here costs real money. The exact parts run on rules; models handle the messy parts.
- A model reads
- what arrives: the request, who it came from, and what is missing from it.
- Rules calculate
- every quantity, rate and dollar amount.
How it runs
Nothing runs until a person says so.
Mongoose works inside the systems and permissions you already run, and learns the rules nobody wrote down. Each workflow can flag, recommend or act; your team sets which. When a system isn't worth building on, we say so.
Why Mongoose
Most AI projects do not fail because the technology cannot work.
They fail because nobody owns everything between the idea and the operation. We do.
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One team, from problem to production.
The people learning the operation work directly with the people building the solution. Nothing is handed between firms, and nothing is lost on the way.
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Built first for our own portfolio.
Mongoose was created inside TriEdge to solve these problems in its operating companies before the capability was offered to anyone else.
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Built for the real world.
We design around exceptions, human judgment, controls and the systems already in place, because our work runs inside live, regulated operations.
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Judged on what actually changes.
We put a value on the opportunity before we build, measure what changes afterward, and can tie our fees to it.
Who runs what
Your system, our watch.
You control your data, your workflows, your team's screens, and the right to walk away. We run everything underneath.
If you leave, you keep your data and workflow definitions, with the documentation and handover to take them with you, agreed in writing before the first workflow goes live.
The people
Leadership that has taken AI into production inside large, regulated institutions.
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Shimon Senderowitz
Head of Technology Value Creation & Product
Previously at ADP, BlackRock and Goldman Sachs.
Established and leads TriEdge's Technology Value Creation function, finding where AI and automation can grow EBITDA and enterprise value across its portfolio companies. Chief Product Officer of ADP's Lyric HCM platform. At Goldman Sachs, nearly a decade finding manual, inefficient work and building the systems to automate it.
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David Huang
Vice President of Technology
Previously at Harrison.ai, NEOS Life, Macquarie, Atlassian and Allianz.
Leads engineering at Mongoose, and the standard that turns an opportunity into a production system holding up under healthcare-grade compliance. At Harrison.ai he built the team behind the world's first multi-finding AI platform for radiology and took it through FDA, TGA and EU clearance. Three times from the ground up as CTO or head of engineering.
20+ consultants, product managers, engineers and data scientists behind them.
Fair questions
What people ask before they call us.
- We tried automation and it failed.
- Usually because nobody owned everything between the idea and the operation. Here one team does all of it, and stays until the agreed value is showing.
- How long does it take?
- We would rather not guess. What is built first, and in what order, is agreed with your leadership team once we have seen the operation.
Start here
Show us the work your people still do by hand.
Operating principle Technology is the means; enterprise value is the outcome.