Managed AI for small & mid-sized business

In a year, the best AI ideas in your company should come from your people, not from us.

ScaleSight AI is a managed AI service. Our team runs one secure AI workspace for your whole company under a ceiling you set, and ships new templates, agents and workflows into it every month, out of a library we build once and give to every client. Anything built on your own documents stays yours. We also build scoped AI projects on their own, each with a start date and an end date.

That ceiling and written rules about who checks what aren’t what you are buying. They are what make it safe for your people to start building their own quotes, summaries, and reports.

Book a readiness review What good looks like
  • Everything built before you arrived
  • Budget split by team, capped
  • A record of what AI is used for
  • Your work stays yours

What we are building toward

A few automations is where this usually stops.

Four workflows, a renewal, and nobody inside the company able to build the fifth. We’re working toward people who keep finding the next one without being asked.

You will know it is working before any report tells you

  • The person who closes your books sets up something that drafts the month-end summary, and mentions it to you after it is already working.
  • The question in a meeting stops being “could AI do this?” and becomes “has anyone already?”
  • Somebody asks us to check something they built, instead of asking us to build it.
  • A new hire’s first week starts from what your team already worked out, not a blank page.

The test we hold ourselves to

After a year, who found your last three AI use cases? If the answer is us, you bought automations. If the answer is your own people, you have something that compounds.

We can’t sell you a culture, and neither can anyone else. What we can do is run the conditions that make one possible: spend bounded so experimenting is safe, one place where good method is visible instead of private, and something new landing every month. At the quarterly review, our team tells you whether it’s happening.

The library

Somebody else already paid to build half of your AI workflows.

The work that is the same in every business gets built once. Every ScaleSight AI client gets all of it, including everything built before they arrived.

Built once, delivered to everyone

Proposals, quotes, meeting summaries, job postings, onboarding packets, customer replies. Close to identical in every business, so we build each one properly once instead of charging every client to solve it again.

Your own work never leaves your workspace

Anything built on your documents, your data, or the specific way your company does a job stays in your workspace and is never shared with another client. The library is the generic half only, and we write down which half a thing belongs to before we build it.

It compounds while you aren’t looking

The more companies we run this for, the larger the library is on the day a new client starts. A company joining in month twenty opens nineteen months of generic work, and none of another client’s private work.

Maintained, not just piled up

A workflow that worked in January is weaker by September, because models and prices change. We re-point the library to better or cheaper models and re-test it. An unmaintained library stops earning its place.

A software license can’t do this for you. An hourly consultant won’t: they are paid to build your thing once, then start from zero on the next client.

Two ways to work with us

A managed service that runs your AI, and a team that builds with it

Managed AI is ongoing: we run the workspace, set the allowances and ship new work every month. An AI Build Project has a scope, a start and an end. You can take either one on its own.

Ongoing managed service

Managed AI

Your people are already using AI, on accounts you can’t see and a bill nobody has added up. ScaleSight AI puts all of it in one workspace under a ceiling you set, and puts a team on making sure it gets used.

  • Control: every seat carries a monthly usage allowance. We set it by team and department rather than per person, review it against real use every month, and bring you the changes worth approving. Pricing is per seat plus usage, under a ceiling you set.
  • Collaboration: one workspace the company owns instead of forty personal accounts. Shared prompts, projects, and templates are visible to colleagues and reusable by them, and what a person keeps private stays private.
  • Governance: a report on the kinds of work going through the workspace, by department, plus written review points for anything with money or a customer on the other end. That record is where next month’s build list comes from.
  • Acceleration: new templates, agents, and workflows handed over every month, with short recorded training at each handover so somebody has shown your team how to use them.
  • Model agnostic: nothing we build is tied to one AI company. Routine work runs on whichever model does it well for the least money, which helps keep a month’s work inside its allowance.
See Managed AI
Project work

AI Build Projects

The AI work that is too specific to come out of a box. Scoped in writing, built, tested against your real past cases, and handed over with the people trained to run it.

  • Scoped in writing before anything is built: the work it replaces, the steps, what a person still checks, and what finished looks like.
  • The hours we need from your team are in the scope before you sign, not discovered afterwards.
  • One accountable owner, and written status against milestones.
  • Everything built is model agnostic, so a model change means re-pointing, not rebuilding.
  • Handed over working: documentation, trained users, and the workflow already running in the business.
See AI Build Projects

By industry

Written around the paperwork your industry produces

One page for each of six kinds of Columbus and Central Ohio business, covering the documents AI can draft and the work that should stay away from it.

Manufacturers

RFQ replies, quotes built off your own job history, work instructions and audit paperwork.

Accounting and law firms

Proposals, engagement letters, long documents summarized and meeting notes turned into actions.

Insurance agencies

Renewal summaries, carrier proposal comparisons, certificate language and claims correspondence.

Contractors

Bid documents, scope letters, RFIs, change order narratives and daily logs.

Nonprofits

Grant proposals, funder reports, appeal drafts and board packets.

Credit unions

Adverse action notices, policy drafts, fee change notices and board minutes.

See all industries

What we do

Contain the risk. Compound the return.

Four jobs, in two halves. Most providers sell one half: either the upside or the restraint. ScaleSight AI is one team doing both, on one invoice.

Contain the risk

The money and the judgment, bounded before any of this scales.

Set the budget, then split it across the teams.

We set each team’s monthly allowance, watch it while the month is running, and hold total spend under a ceiling you set.

Know what AI is being used for, and who checks it.

We report the kinds of work your company hands to AI, by department, and write down where a person signs off before anything leaves the building.

Compound the return

Method that accumulates instead of resetting every time somebody starts over.

One place to work, so good method spreads.

We set up the shared spaces and show your people how to publish the jobs worth keeping, so the next person opens a method instead of inventing one.

The library grows every month.

We ship new templates, agents and workflows into your workspace every month, most of them built for another company first, which is why they cost you nothing extra. Nothing built on your data leaves your workspace.

See what each one involves

Why ScaleSight AI

The software is the easy part

There is no shortage of places to buy AI seats. What’s scarce is somebody doing the work afterward: reading the usage report with you and building the next thing from what it says.

  • Our team sets the allowances, not just the software. Team-level quotas exist in more than one product. What you’re buying here is somebody doing the work: setting each team’s allowance at setup, reviewing it against real use every month, flagging which team is close to a limit while the month is still running, and bringing you one decision to approve.
  • A price rise somewhere else isn’t your rebuild. No single AI company leads at everything: one is ahead on generating an image, another on live web research, another on reasoning across a long contract, and another is just the cheapest way to draft a follow-up email. We send each job to the model that does it well, and your people never have to know which one they’re using. Nothing we build sits inside one company’s model, so when a price moves or a model is retired, our team re-points it and re-tests it against the cases it was accepted on. You never see that cost, which is the point of paying for it.
  • We state the pricing model, including the part that varies. Managed AI is priced per seat plus usage. It isn’t flat and it isn’t unlimited, and we say so before the contract, not on the first heavy invoice. The variable part is visible in real time, attributed by team and department, and capped where you set it.
  • You keep the work if you leave. The prompts, templates and documents your people create in the workspace belong to your company. Ask for the term, the notice period and the export terms before you sign, and we’ll send them in writing. An exit answer belongs in an agreement, not in a marketing claim, so read it there.

Data and security

“Where does our data go when someone types it into that box?”

On a free consumer account you can’t answer that. ScaleSight AI runs on a SOC 2 Type II audited platform, sends you the written terms before you sign, and says plainly which company the audit belongs to.

See how your data is handled
  • SOC 2 Type II audited platform
  • Tenant-isolated
  • No training on your data
  • US-hosted

Questions

The questions we get asked most

What is managed AI, and what does ScaleSight AI actually do?

Managed AI means an outside team runs a company’s AI workspace for it. ScaleSight AI does that for US companies of roughly 20 to 500 people where nobody owns AI as a job title. You get one secure workspace, allowances set by team under a ceiling you control, a report on what work is going to AI, and new workflows every month.

What should we budget for managed AI?

ScaleSight AI engagements start at $250 a month, and above that the budget follows the seat count. Plan on these monthly ranges: up to 10 seats, $250 to $500; 10 to 25 seats, $500 to $1,175; 25 to 100 seats, $1,175 to $3,800. The $250 minimum is where a team of five or fewer lands. Seats above the first ten are budgeted at lower rates, so the budget grows more slowly than the team does. These are seats rather than headcount, because you seat the people whose work happens on a screen: a 60-person manufacturer commonly seats 20 to 30 and plans against the middle range rather than the top one. Where a company lands inside its range depends on how large the allowances need to be and how much setup the first month carries. These are planning figures, not a quote, and AI Build Projects are budgeted separately.

Our AI bill keeps climbing. How do we get control of it?

ScaleSight AI puts three things in place: one company account instead of scattered personal subscriptions, a usage allowance on every seat, and a total ceiling the company sets. We also route routine work to lower-cost models so each allowance goes further. Spend still varies with use, but it varies inside a limit you chose, and you can see it by team and department while the month is still running.

How is this different from Microsoft 365 Copilot, and what do I tell my IT provider?

Copilot, ChatGPT and Claude are products a company licenses and then owns the job of driving. ScaleSight AI is a team that runs the program: allowances set by team and department, a report on what kinds of work AI is being used for, review points for anything with money on the other end, and new workflows built and delivered every month. We’re also not tied to any one of those products, so a price rise or a retired model doesn’t become your rebuild, and each job goes to whichever model does it best. We work alongside an existing IT provider rather than replacing them. The two questions worth asking your provider are who sets the team budgets and who builds the workflows after launch.

Employees are pasting client data into ChatGPT. What do I do about it?

We move the activity into a workspace the company controls, then write the policy around what people are doing. Blocking AI outright pushes the same behavior onto personal phones, where nothing is logged. Once the work is in one place, we report what’s being handled, set rules for who can reach which sources, and define where a person signs off.

We gave everyone ChatGPT and nothing changed. Why?

A blank chat box gives an employee no starting point and no reason to break an existing habit, so the licenses sit unused. We deliver ready-made templates, agents and workflows for jobs people already do every week, keep delivering them every month instead of only at go-live, and run short recorded training at each handover.

Can someone build AI workflows for us? We do not have time to do it ourselves.

Yes. AI Build Projects is our project work, available on its own or alongside the Managed AI service. We scope the work in writing, build it, test it against your real past cases, and hand it over documented, with your users trained. It has a start date and an end date. If you want it maintained afterwards, put it on the managed service. If you don’t, you own it as it stands.

You build workflows once and give them to every client. Does our work end up at another company?

No. Anything built on your documents, your data or the specific way your company does a job stays inside your workspace and is never shared with another client. What’s shared is the generic half: drafting a proposal, summarizing a meeting, writing a job posting. Before anything is built, we write down which side of that line the work falls on. If a workflow needs your data to work at all, it’s yours alone.

You have no client names or case studies. Why should we believe you?

We don’t publish client names, logos or case studies. What you can check instead is method: the pricing model stated before the contract, our written security terms, a project scope that names the hours and the review points before anything is built, and a walkthrough on a call using one of your own recurring jobs. Judge the parts you can check now, not a story you can’t verify.

All questions

Find out what AI is already costing you.

A readiness review shows where AI is already in use, what data it touches, and what it adds up to on the expense reports. You keep the findings whether or not you go further.

Tell us what you’re working on See how it works