Our AI integration services put assistants, automation, and smart routing inside the app your team already uses, in screens they already know. Nothing gets replaced or migrated, and a person approves anything that matters.
Rebuild the system, or leave it alone and let people paste your data into a chatbot in another tab. Neither puts intelligence where the work happens, and the app your business runs on keeps answering nothing about its own data.
Replacing a working app means paying again for everything it already does right: the workflows, the edge cases, and the small fixes nobody wrote down. That is a big bill for what is really a missing capability.
Your team already uses AI tools, just not inside the system they work in. What the tool knows depends on what someone remembered to paste in, and the result still gets typed back into the app by hand.
If the vendor roadmap says next year, your team fills the gap by hand until then: exporting, re-keying, checking, reminding. The data is already in the app. Nothing is using it.
We build alongside your existing app rather than through it. Nothing is removed to make room.
An assistant that lives where your team already works, answers from the records already in the app, and follows the roles and permissions you already maintain. If it prepares something consequential, it waits for a person to approve it.
Intake, checks, updates, notifications, and follow-ups move to software that runs them the same way each time and flags the cases that don't go through. When you want an agent that goes further and acts on your data, that is the AI agents service.
New work is read, categorized, prioritized, and sent to the right person using the fields already in your system. Nobody gets a new form to fill in.
We sit with the people doing the work and follow one real task end to end, including the spreadsheet or group chat that never comes up in meetings. That task is where we start.
Every app has a safe place to attach: an API, a read-only view of the data, a scheduled export, an embed point in the screen. We take the one that adds the most and risks the least.
It goes live with a small group first while everything else runs as before. When the answers are trusted, we turn on the actions your team asked for, with an approval step where the stakes call for one.
When the first workflow holds up, we add the next one, in steps your team can absorb.
| What matters | Rewrite or separate chatbot | AI integrated into your app |
|---|---|---|
| What happens to today's app | It gets replaced, or it is ignored while people work around it. | It keeps running. Nothing is taken out. |
| Where the AI is | In a new system, or in a tab next to your app. | In the screens your team already has open. |
| What it knows | With a chatbot: whatever someone remembered to paste in. | The records already in your app. |
| Permissions | With a chatbot: none. Everyone gets the same answer. | The roles and permissions you already set. |
| Who approves | With a chatbot: nobody, unless the user thinks to check. | A person approves anything consequential. |
| What your team has to learn | A new system, or a new tool. | The same screens, with more in them. |
Both get called adding AI. Only one leaves your app running and puts the AI inside it.
They are the work of adding AI to software you already run. We put an assistant, automation, or smart routing inside your existing app, in the screens your team knows, using the data already there. Your app stays in place. There is no rewrite and no migration, and a person approves anything consequential.
Yes, that is the whole approach. We attach at a safe seam, such as an API, a read-only view, or an embed point, and ship one workflow to a small group first. The rest of the app keeps running as it does today, and what we add can be switched off without taking the app with it. Older .NET and PHP applications, vendor systems with a thin API, and databases carrying years of history are all things we work with. If we can't read your data safely and put something in front of your users, you'll hear that on the mapping call.
It reads through your existing permission model, not around it: if a person can't open a record, the AI won't use it to answer them. It can answer, draft, update records, and route work. Consequential actions are prepared, not executed. The AI stages the work and a person approves it before anything leaves your system.
Cost depends on the workflow, which is why the mapping call comes first. We scope the first workflow and agree the scope and timeline in writing before work starts. You own the code and designs we make for you, and we document them so you can run, change and hand them to someone else. Your team or your vendor keeps the app, and we take responsibility for the layer we add. If part of it runs on the shared foundation behind Attain OS, AttainSoft keeps that foundation and licenses it to you while we host it. You can cancel with 30 days' notice; within 30 days we export your code and data, and after the export we delete the hosted copy. These terms are written into your quote before work starts.
Agents that answer, draft and act inside the software your team already uses.
Explore →Modernize legacy software without a rewrite, one workflow at a time.
Explore →Monitored automations that end the copy-paste and the manual reconciling.
Explore →Tell us which workflow eats the most time. We'll map how AI fits into the app you already run.
