AI strategic advisory
with real impact.
Manual work between systems, disconnected locations, rising costs and slow decisions all come out of margin. PrimeInsite finds the operating friction, assesses where AI is economically justified, and guides the change against measures we agree on first. Strategy, build and ongoing management for multi-unit operators and the companies that serve them, at prices we publish.
Everyone has an AI pilot. Almost nobody has an AI P&L line.
Margins are thin, labor is scarce, and the systems that run the business do not talk to each other. AI tools arrive one vendor at a time, each solving a slice. The result is a dozen subscriptions, no owner, and a board asking what it all added up to.
The pilot that never left location three
A voice-ordering or scheduling tool works in a test store, then stalls. Nobody mapped the data, the integration or the manager's workflow before buying it.
Vendors selling tools, nobody selling outcomes
Every POS, payroll and ordering platform now ships an "AI" feature. Each is priced to its own product, none is accountable to your margin.
No one on staff whose job is this
Our own count found that across 420 recent restaurant and foodservice postings, six companies were hiring anyone with "AI" in the title. The other operators are doing it on the side, or not at all.
See the researchOne firm, from the board conversation to the store floor.
Most firms stop at the strategy deck. Most vendors start at the install. PrimeInsite covers the whole arc, so there is one accountable party from the first opportunity list to the monthly results review.
AI Strategy & Roadmap
Where AI pays back in your operation, in what order, and what it will cost. Ranked by P&L impact, not by what is fashionable.
Strategy practiceExecutive Advisory
A fractional Chief AI Officer for the leadership team and the board. Vendor decisions, governance, risk, and a monthly cadence that keeps the program honest.
Advisory practiceBuild & Integration
Agents, automations and integrations that connect the systems you already own. Shipped in six-week sprints with measured results, not a demo.
Build practiceManaged AI Operations
We run what we build. Monitoring, triage, vendor and model changes, and a monthly performance review, priced per location.
Operations practiceYou have three other ways to buy this. Here is how they compare.
We built the firm around the gaps we kept running into as operators: partners who sell and juniors who deliver, vendors whose incentive is their own product, and builders who leave the day the thing goes live.
| Global consultancy | Software vendor | Dev shop | PrimeInsite | |
|---|---|---|---|---|
| Who shows up | Partners sell, analysts deliver | Sales engineers | Developers | Senior operators who have run the P&L, backed by specialists |
| How you pay | Time and materials, rate card undisclosed | License plus "implementation services" | Hourly or sprint, scope creeps | Fixed fees and per-location rates, published on this site |
| Their incentive | More hours | Their product | More features | Your operating result, with a gainshare option |
| After go-live | Gone | Support ticket queue | Gone | Managed operations, monthly review, named owner |
| Knows your industry | Sometimes | Their slice of it | Rarely | Decades in restaurants, payments and franchise operations |
| Minimum to start | Six figures | Annual contract | Statement of work | A half-day briefing or a two-week Quick Start |
A practical path from ambition to a number on the income statement.
Every engagement follows the same arc, so you always know what phase you are in, what it produces, and what it costs. Start anywhere in the sequence. Most clients start with Discover.
Discover
Your operation, your data, your systems, and where the money leaks. Three weeks.
- Current-state systems and data map
- Ranked opportunity list with P&L estimates
- Go / no-go recommendation
Define
A strategy the CFO can sign: sequence, budget, vendors, governance, and the measures that decide success.
- 12 to 24 month roadmap
- Build-buy-partner decisions per use case
- Governance and data policy
Enable
The operating model: who owns what, what the managers need to know, and what the data has to look like before anything is switched on.
- Data readiness fixes
- Training and change plan
- Vendor contracts negotiated
Execute
Six-week build sprints with a measured result at the end of each one. Live in real locations, not a lab.
- Working agents and integrations
- Pilot-to-rollout plan
- Sprint results against baseline
Realize
Measure, tune, expand. We run the operations desk and report the number every month.
- Monthly performance review
- Model and vendor changes handled
- Expansion to the next use case
We don't quote other people's surveys. We count.
Every number in this section is something our research desk counted itself, with the denominator and method written down so your CFO can reproduce it. The counts are updated as the field changes.
Six companies account for every "AI" job title in restaurants and foodservice.
Of 420 recent LinkedIn postings for restaurant and foodservice operators, ten carried "AI" in the title, from six employers. Starbucks alone had four. Everyone else is expected to figure it out on the side.
One restaurant controller posting in 33 mentions AI at all.
Of 33 "restaurant controller" postings scanned, one mentioned AI, eight named a specific finance or POS system, and 16 said "POS" generically. The finance function is being hired for the systems of 2015.
We work where the margins are thin and the locations are many.
Our partners spent their careers in restaurant technology, payments and franchise operations. We start with the industries we know from the inside, and we say so when a problem is outside them.
Hospitality & multi-unit restaurants
Independent groups, regional chains and emerging brands from six to several hundred locations. Labor, inventory, scheduling, guest data and the back office.
How we helpFranchise organizations
Franchisees operating across brands and franchisors supporting a system. Standardizing AI across units without stepping on brand standards or data rights.
How we helpFoodservice distribution
Broadline and specialty distributors and the operators they serve. Order prediction, rep enablement, pricing and the data that flows between the two.
How we helpPayments & fintech
PayFacs, ISOs, acquirers and software companies with embedded payments. Risk, underwriting, support and the economics of serving small merchants.
How we helpPrivate equity operating teams
Operating partners who need a repeatable AI playbook across a portfolio of multi-location businesses, and a diligence lens for the next one.
How we helpHospitality technology vendors
POS, back-office and ordering platforms deciding what to build, what to partner on, and how to price AI without giving it away.
How we helpConsulting firms hide their prices. We think that's the first sign of a bad deal.
Every engagement on this site has a fixed fee or a published rate. You know the cost before the first meeting, and so does your board.
Ideas, counts and field notes for people who run things.
Short, specific and written by the people who do the work. No thought leadership.
Why most restaurant AI pilots stall at location three
It is almost never the model. It is the data, the integration and the general manager's Tuesday.
ReadSeven questions a CFO should ask before buying any AI tool
Including the one about who owns the data, which almost nobody asks until renewal.
ReadAgents need an operator
Why "set and forget" is the most expensive phrase in AI, and what a managed operations desk actually does all month.
ReadBring us the problem. We'll bring the plan and the price.
A 30-minute working session with a senior partner. No deck, no pitch. You leave with a point of view on where AI pays back in your operation and what it would cost to find out.