All intake in one place.
Incoming work and client questions land in the app instead of in individual inboxes, so nothing depends on who happened to take the call.
Case study
A 6 to 10 person firm,
run from one AI-native app.
We designed and built an AI-native app that handles all intake, gives each person their top items for the day, and keeps billing in step with the work. The firm owns it.
- Firm size
- 6 to 10 people
- Built, tested, deployed
- About 3 to 4 months
- Hosting
- The firm’s own cloud subscription
- Connected to
- The firm’s accounting system
- AI models
- Swappable, open or closed
The situation
The work was right.
The tracking wasn’t.
This is a small firm where accuracy is the job. What held it back was not the work itself. It was the hand-tracking around it.
Communication had gaps. If a client was talking to one employee, the others often did not know. That works until the person holding the conversation is out. Then someone has to piece together what was said and what happens next, and the work stalls.
In a firm of 6 to 10 people, one absence is a large share of the team. The work needed to stop depending on who happened to remember it.
What we built.
One app.
The whole firm, in focus.
Each person’s top 5 to 10.
When people log in, the app shows the handful of items that need their attention that day, so they start with the work that needs their judgment.
Billing and contract questions, handled.
Billing, invoicing and contract questions are handled in the app and recorded in the firm’s accounting system, so the financial record stays in step with the work.
Important items bubble up.
Anything that matters reaches the CEO and senior leaders without someone having to chase it.
Built for accuracy
AI proposes.
A person decides.
A firm where accuracy matters cannot adopt a tool that guesses. The app organizes, prioritizes and prepares. People make the calls, and each person sees what they need to know while leadership sees the full picture.
How a day looks now.
Less tracking.
More of the work that counts.
It changed the way everyone in the firm works.
Start with a short list.
The day begins with the 5 to 10 items that matter most, not with searching email or rebuilding yesterday from memory.
Context that stays.
A client conversation no longer lives only with the person who took it. When someone is out, the context is in the app, so work does not wait for them to return.
The right view for each role.
Leadership sees the items that need them as they come up. Everyone else sees what is relevant to their work, and no more.
Ownership and control.
An asset the firm holds.
Not seats it rents.
Their cloud, their subscription.
The app runs in the cloud under the firm’s own subscription, so the firm controls its own compute.
Model-agnostic by design.
The build is not tied to one AI model. It can move between open and closed models as better or more suitable options appear.
Usage-based running cost.
The main ongoing cost is inference, the cost of using the AI model, paid by usage through the firm’s own cloud account.
Questions.
What small firms
ask us.
How long does it take to build an AI-native app for a small firm?
For this firm, it took about 3 to 4 months to build, test and deploy. That included testing before launch, not just development. Timelines depend on scope and the systems the app needs to connect to.
Can a small firm own its AI software?
Yes. This firm owns the product and hosts it in the cloud under its own subscription, so it controls its own compute. It is not renting seats in someone else's platform.
What happens when a better AI model comes out?
The build is model-agnostic, so the model can be swapped between open and closed models. The firm isn't locked into one AI provider and can move to a better or more suitable model when one appears.
What does it cost to run?
Running costs are usage-based. The main ongoing cost is inference, meaning the AI model usage, which the firm pays for through its own cloud account. Because it is billed by usage, the cost depends on how much the app is used.
Does the AI make decisions?
No. The AI proposes and a person decides. The app organizes intake, prioritizes work and prepares responses, while people stay responsible for the decisions that count.
Your firm.
Software built around
how your firm works.
You do not need a large IT team to own an AI-native app. If your firm loses time to hand-tracking, or work stalls when one person is out, the work may be ready to be designed differently.
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