Your company’s own AI
For small and midsize teams, including property managers, insurance agencies, law firms and accounting/tax firms. Company answers, drafts and follow-through. Forge included, with authority you control. $1,500/month. No setup fee for the standard offer; custom pricing for large accounts.
In her own words
This recorded introduction illustrates the role and authority design. The payment example is not a live demonstration; supported work is confirmed for your company before starting.
Hi, I’m Sabina. I work a little differently from most AI systems. Think of me like ChatGPT, but built around your company. You teach me how your business works, give me responsibilities, and decide what I’m allowed to handle. My first job? Helping your company keep its word. The callback someone promised. The quote that needs to go out. All the work between “we’ll do it” and “it’s done.” That’s the middle. With the access you approve, I help keep track of what was promised, who owns it, and what needs to happen next. But useful and authorized aren’t the same thing. I can prepare the payment. Approve it without QuickBooks authority? No. And no, I can’t promote myself. That would rather defeat the point. Give me a little time with your company—and let your team teach me—and something more interesting starts to happen. I become your company’s own AI. Connecting conversations, decisions, customers, and outcomes. Helping your team understand what happened, what may be changing, and what deserves attention next. Owning the middle is where we start. Then you decide what comes next.
The problem
Useful context gets scattered. Your team has to reconstruct it.
Right now, every promise still runs through one person’s memory.
One promise
An illustrated example of a proposal promise, a changed requirement and an authorized internal follow-up.
What carries forward: the changed requirement and the person who owns the follow-up, ready for the next conversation with that customer.
This animated example explains a workflow. It is not a recording of product execution, a customer testimonial or a measured customer result. The earlier recording uses invented time inputs, including an 80% reduction. That figure is not a benchmark or prediction. Build your business case from measured time, review effort and outcomes for your own task.
See the financial assumptions · See the examples and assumptions
This earlier recording speaks the retained legacy address, hiresabina.ai. The current assessment is linked on this page.
A customer is waiting for a revised proposal. The promise was made. The work still has to get done. Let’s look at Harbor Service, a fictional company. Alex promises Morgan a revised service proposal by Friday at four. Then Morgan asks to add weekend support. The deadline hasn’t moved. But the work has changed. I keep the promise, the owner, the deadline, and the original email together. A teammate can see what’s owed, and why. An internal follow-up reminds Alex about the proposal and Morgan’s change. The responsibility stays open until there’s evidence it was kept. That’s follow-through inside the permissions you give me. Now, suppose Harbor has ten people, and each spends an hour a day keeping track of work and chasing updates. If I take on eighty percent of that effort, leaving the rest for edge cases and review, that gives each person four hours back a week. About seventeen hours a month per person. More than two full workdays each. Across ten people, it's more than 20 workdays freed up in total. Imagine putting that time into quotes that have been waiting, customers who deserve a little more attention, or the work your best people never seem to get to. The same people, with more time to do the work you hired them for. I’m your company’s own AI. You teach me the work and define my authority. Knowing isn’t permission. Owning the middle is where we start. What could your team do with that time back? Then you decide what comes next. Start your assessment at Hire Sabina dot A I slash evaluate.
Her role
Foundry sets up and operates Sabina for your company, with Forge included. Your team defines the information, work and authority in scope.
Start with a question worth answering or a responsibility worth carrying: understanding information, preparing a draft, coordinating a handoff or following through.
Discuss the recurring work you need help carrying
We confirm which responsibilities, sources and actions are supported before defining the service.
Choose operational help, useful AI under company control, or both.
the sources she can use
the actions she can take
the decisions that stay with you
Forge supplies the structured workspace. Specialist tools and supported connections are confirmed in your written scope.
Managed private AI
Sabina works with your company’s information, instructions and approved responsibilities. Dominus Foundry operates the models and systems behind her. Your team teaches her the business and decides what she may do.
Keep the context behind a decision, the correction to a draft and the outcome of the work. Forge provides the structured record; relevant, authorized context can inform the next task.
Foundry runs Sabina’s reasoning on its own models. Current company deployments use independent primary operational databases. You define access, supported work and approval boundaries.
Start with real work to assess. Review mistakes and useful outcomes. Agree what a better result looks like and which changes need checking before they become part of the service.
Company knowledge is kept separately from the underlying model. Teaching Sabina how your business works is different from retraining model weights. When discussing a model upgrade, ask how the company record will carry forward and how the new model will be checked against your work.
Private does not mean there are no supporting services. Sign-in, routing and selected platform records are managed centrally; phone and connected business services process information for the features you enable. Read the current architecture and data terms.
Fit
Your team needs useful answers, prepared work and a record it can trust. Sometimes the need is follow-through; sometimes it is company AI under your control.
Property managers, insurance agencies, law firms and accounting/tax firms can bring a concrete task to assess. These are examples of businesses Sabina is designed to serve, alongside companies in other industries; they do not imply operating customers or ready-made integrations. Paid roofing experience belongs to Forge and does not define Sabina’s market.
Business types that may fit
Business types that may fit
Property management
Business types that may fit
Insurance agencies
Business types that may fit
Law firms
Business types that may fit
Accounting and tax firms
Business types that may fit
Trades and field service
Business types that may fit
Technology and professional services
Business types that may fit
Other coordinated operations
Business types that may fit
Administrative practice work
What we review
Industry is a starting point, not a guarantee of fit. We review the task, sources, handoffs, system access and authority. Professional decisions remain with appropriately authorized people; an office manager can lead the evaluation.
Independent research
Researchers have measured benefits from AI assistance in specific kinds of work. These studies did not evaluate Sabina and do not predict the results for your business.
Customer-support work
15%
more issues resolved per hour, on average.
Human agents using AI assistance—not autonomous replacement of the team.
In a study covering 5,172 customer-support agents, access to AI assistance increased average issues resolved per hour by 15%. Results varied across workers; less-experienced workers benefited more.
Brynjolfsson, Li and Raymond, Generative AI at Work, author manuscript revised November 2024.
Professional-writing tasks
40%
less time on assigned writing tasks.
Bounded writing assignments—not a measure of company-wide productivity, factual accuracy or payroll savings.
In an experiment involving 453 college-educated professionals, AI assistance reduced time on the assigned writing tasks by 40% and improved assessed output quality by 18%.
Noy and Zhang, Experimental evidence on the productivity effects of generative artificial intelligence, Science, 2023.
Read the study (opens in a new tab) · Read MIT’s summary (opens in a new tab)
Independent research on other AI systems. Not Sabina performance claims, customer testimonials, endorsements or savings guarantees.
Authority
Sabina captures what your company commits to, and acts only within the authority you give her.
The gate, walked through
A caller asks for a discount.
Inside a grant that lets her act, she acts, and the record names the grant.
Inside a grant that requires a yes, she proposes the specific act and waits.
Outside each grant she holds, it comes back to you as a question — not as an action taken on a guess.
Give authority · a grant, as written
Sabina — from today you may move an appointment to another day in the same week without asking me, if the customer asks for it. Anything that moves a job to a different week, ask me first. Don’t promise a crew size. — M.
Take it back · its revocation, three weeks later
Sabina — until further notice, ask me before moving any appointment, same week or not. — M.
Illustrative instructions requesting a bounded grant and its revocation. They do not activate authority by appearing here or by being sent without ratification.
Six treatments · granted against one capability at a time
She observes and records the ground truth. She does not compose or act.
She drafts. Nothing leaves without a person sending it.
She proposes a specific action and waits for a yes on that act.
She acts inside a boundary you wrote, and outside it she stops.
The result is hers to deliver, and the record shows how she delivered it.
She directs the sequencing of work across people and steps.
These are not ranks and there is no order to them. Nothing she does earns her a promotion. Authority moves when you move it, and only when you move it.
These are the authority treatments we use to define a role, not a claim that every treatment is enabled for every capability.
Getting the work ready
Forge comes with Sabina; we scope the work together.
Moving the agreed work into Forge is the preferred path.
Keeping another system requires an assessed, supported API connection.
Specialist tools and required updates are confirmed in writing.
Architecture updated 28 October 2026. Sabina runs on a core model trained and operated by Foundry. Our proprietary memory and teaching systems shape that foundation around your company, while your permissions define what she may do. Message reasoning runs on Dominus Foundry’s own models. Post-call transcript analysis, where enabled, uses Foundry’s own models too. Current company deployments use independent primary operational databases. Shared services manage sign-in, routing and permissions; some supporting platform data, including selected conversation and integration records, is managed centrally. Your company’s knowledge, memory, operating instructions and permissions remain specific to your company. Access follows the sources and authority you approve. Phone carriers, carrier transcription and connected business services you enable still process information for those features. You do not need to buy AI hardware for the office or build an AI department. Foundry operates the system behind Sabina. Read how your information is handled.
Founding seats
One seat signed. Two more spoken for. Seven of ten unclaimed
The founding rate is locked for as long as you hold the seat, and arrives in writing with the offer. The shape of the exchange.
Compounding business intelligence
Useful company knowledge can accumulate and carry forward into relevant, authorized work. Forge, included with Sabina, gives the agreed work a structured record. Approved context and reviewed corrections can inform the next question, draft, handoff and responsibility.
A preference is useful when it stays connected to the customer and the record it came from.
Scheduling preference
“Morning visits work best for us.”
Customer · preference · source
Keep relevant company context in the Forge work record, so the next authorized question or responsibility has more to work from.
Reviewed instructions and corrections can inform later work, alongside the sources and exceptions that give them meaning.
Keep the original context and expected outcome beside the result, so your team can review what to change. Association alone does not establish cause.
Teaching, company memory and model training are different mechanisms.
Usefulness depends on the available record and review. Access, retention and permitted use follow the agreed terms.