AI deployment for mid-market operators
We put AI where the work actually is.
Operent deploys AI inside $25M–$500M operators, in industries such as healthcare, construction and property services. Then we prove what it did to the P&L: cost per unit of work down, capacity up, revenue that used to slip away captured. We stay until it is in production.
Interviews cannot find these, because the people being interviewed do not know they are doing them.
01 · Who we are
Operators, not advisors
We have sat inside the operations teams we now build for, at the firms and institutions below.
02 · The offer
The diagnostic is guaranteed
If it does not surface validated opportunities worth five times the fee, you do not pay it. No track record required for that to be true.
03 · The method
We bring our own instrument
Proprietary workflow tracking that shows how work actually moves, not how the process map says it does.
Educated and trained at
The gap
They have already bought the tools. They cannot make them work.
The failure is not technical. Nobody instrumented the baseline, nobody owned the system after the vendor left, and the pilot was chosen because it was interesting rather than because it was expensive.
of AI pilots never reach production.
Iris.ai, 2026
of companies abandoned most AI initiatives, up from 17% a year earlier.
S&P Global
Success rate with a specialist implementer, against the same work built in-house.
MIT NANDA
Baseline first
We instrument the “before” as paid phase one. Most failures trace to nobody measuring it.
Reviewable by design
We only automate work where a human catches the error cheaply, before it ships.
Kill criteria up front
Every pilot ships with a defined number that ends it, agreed before we start.
What we do
Three phases. You can stop after any of them.
Every engagement starts small and expands on proof. The first purchase is a fixed fee a COO can approve alone, and the value lands on both sides of the P&L rather than only the cost line.
Diagnose
Four to six weeks. We find where the work actually is, then price what AI does to it.
- Workflow census produced by our own instrumentation, not interviews alone
- Volume audit: documents by type, call minutes by disposition, spreadsheet dependencies
- An opportunity register of scored items, each tied to a cost line
- An EBITDA bridge, and three pilot candidates with defined kill criteria
Deploy
Vendor-led where a good product exists, custom-built where none fits. Most failures at this size are selection and adoption failures, not model failures.
- Selection, negotiation and integration into the system of record
- Custom extraction for non-standard, handwritten and faxed documents
- Agents that operate legacy systems and portals with no API
- An evaluation harness, so quality is measured rather than felt
Embed
A fractional AI leader for companies that will never hire one, plus quarterly proof the money showed up.
- Owns the roadmap, the vendor portfolio and the benefit case
- Governance pack: review thresholds by risk tier, audit logging, model risk register
- Realised versus modelled benefit, at a level of detail a CFO will accept
- Builds the internal capability that eventually replaces us
The half everyone expects.
- Hours per document, call and file
- Rework, error correction and rekeying
- Overtime and agency cover at peak
- Headcount needed to absorb the next 20% of volume
The half that usually pays for the programme.
- Contacts answered instead of abandoned
- Quotes out the same day instead of next week
- Bids and proposals pursued that used to be declined
- Work taken on without adding people to do it
What we build
The industry changes. The shape of the work does not.
Almost everything we deploy is one of six things. If your people spend their day reading documents, answering phones, or moving data between systems that do not talk to each other, you are already looking at your own work below.
Voice agents
Inbound calls, scheduling, status enquiries, after-hours cover and call-out recovery, handled end to end with escalation rules you set.
Document extraction
Invoices, forms, faxes, scanned PDFs and handwritten notes turned into structured data your systems can actually use.
Retrieval and answer
Grounded answers over policy libraries, contracts, plan documents and governing documents, each answer carrying a citation back to the source line.
Drafting
Appeals, proposals, reports and correspondence drafted for a person to finish. The economics hold whenever editing beats writing from blank.
Reconciliation and matching
Invoice against contract, three-way match, duplicate detection, billing accuracy. Tedious enough that nobody defends doing it by hand.
Monitoring and flagging
Compliance drift, obligation dates, exceptions and quality review, at full coverage rather than the sample you can afford today.
Example use cases
What this looks like in practice.
Two worked examples, in industries such as healthcare services and the built environment. They are illustrations rather than limits. The same capabilities apply anywhere the cost base is people handling documents and calls.
A multi-site clinical group
Outside the hospital, payers impose the document burden, so the paperwork is non-negotiable, standardised, and almost entirely administrative rather than clinical.
- Outpatient rehabilitationMulti-site
- Behavioral health & ABAHigh doc
- Home health & hospicePhone-led
- Dental & veterinary groupsRoll-up
- Revenue cycle & billingPure play
Where we would start
Front-desk phone capture and fax referral intake. Measurable in thirty days, and it never touches the clinical record, which keeps the first project out of the compliance queue.
A contractor or property manager
Two different buyers running on one document set: specs, work orders, technician notes, certificates of insurance. That is why a single playbook serves both.
Construction
- Mid-market general contractorsGC
- Specialty trade contractorsSub
Property & building operations
- Community association mgmtHOA
- Multifamily property mgmtPM
- MEP and fire/life-safetyService
Where we would start
Submittal and RFI processing on the construction side; resident enquiry handling with governing-document retrieval underneath on the property side.
The same shape shows up in
Don’t see yourself here? If your cost base is people reading documents, answering phones and rekeying data between systems, the shape is the same, and the diagnostic will tell us in four weeks whether it is worth doing.
How we work
Measure first. Everything else follows from that.
01
Instrument the baseline
We measure the “before” before touching anything. Our discovery tool shows how work actually moves, not how the process map says it does: the rework loops, the shadow spreadsheets, the task consuming a third of a team's week that appears on no org chart.
02
Diagnose and size
A register of scored opportunities, each tied to a cost line, with three pilot candidates and the number that would kill each one. If it does not surface opportunities worth five times the fee, you do not pay it.
03
Pilot against kill criteria
One workflow, narrow scope, measured against the baseline we captured. We only automate work where a human catches the error cheaply, before it ships. If it does not clear the bar, we say so.
04
Scale and prove it
Roll out site by site with a repeatable deployment kit, then report realised versus modelled benefit at a level of detail your CFO will accept.
Why us
We stay until it is in production.
A consultancy bills hours against recommendations. We write and ship the system, and we are measured on whether the deployed thing delivers. That distinction is the whole job. The technology has not been the constraint for a while now.
Roughly $9B has been committed by OpenAI, Microsoft, Anthropic and AWS to the same proposition: deployment, not models, is the bottleneck. But a $450k forward-deployed engineer never gets sent to a 40-person home health agency or a 12-partner contracting firm. Everything below that line is structurally unreachable for them. That is the ground we work.
The guarantee
If the diagnostic does not surface validated, client-agreed opportunities worth at least five times the fee, the fee is waived. We would rather carry that risk than ask you to take our word for it.
Educated at
Experience across