AI Readiness Assessment for Your Software and Data

An AI readiness assessment tells you whether your software and data can support AI today. If they can't, it tells you what to fix first. It answers one practical question before you spend money on AI: can it work with what you already run?

Arc AI is two engineers, Bozhidar Ivanov and Ivaylo Valchev. We build AI integrations, and we modernize old systems. So we look at your readiness from both sides.

What we check

• The job for AI. We look at the work your team does by hand and what it costs you. Sometimes the answer is that you don't need AI.
• Your data. We check where it lives, how complete it is and who may use it. AI-ready data is tidy, in one place and allowed for this use.
• Your systems. We look for an API, a database or webhooks that an AI model can work through.
• Security and rules. We list what an AI may see and what it may change. We also note what GDPR and your contracts require.
• Running cost. We estimate what the model would cost each month at your volume.

A quick self-check

Answer these five questions. Each "no" is a point the assessment looks at closely.

1. Can you name one task your team does by hand every day?
2. Does your software have an API, or could a developer add one?
3. Is the data for that task in one place?
4. Is that data mostly complete?
5. Is someone on your side ready to own the AI once it runs?

What you get

You get a written plan. It puts your system in one of three groups:

• Ready now. We start with a small AI version and test it on your data. Our AI integration services page shows how that works.
• Ready after small fixes. We close the gaps first. These are often data or permission problems.
• Modernize first. The system can't support AI safely yet. Our legacy system modernization page explains the next step.

The plan also lists the risks, the cost to build and run, and the first steps. The written plan is yours, and your own team can follow it.

We run AI in production

We don't only assess. We build AI systems and keep them running, for our clients and for our own products. We don't name our clients.

Customer support

• Chat agent. For a home-services company, our chat agent answers customers inside the company's support chat. It confirms who the customer is, checks and cancels bookings, and explains fees and policies from the company's knowledge base. It files other requests as tasks for the team. It handles about 6,000 conversations a month. Our AI chatbot development page walks through one real conversation.
• Voice agent. The same agent has answered the company's support calls by phone since July 2026. A speech-to-speech model holds the conversation, and our code checks who the caller is and records requests for staff. It takes more than 100 calls on busy days, and we review each day's calls to improve it.
• Helper for support staff. Support staff ask an AI helper to change what the agent says or knows. It drafts the change, and a person approves it.
• Listing support agent. Support staff of a real estate platform type a request in plain English. An AI agent finds the listing and the action, and our code checks ownership before anything changes.

Calls, email and photos

• Call transcription. For several contact centres, we turn each recorded call into a timed transcript that separates the customer from the agent. The service also answers set questions about a call. It runs speech recognition on dedicated GPU servers.
• Email sorting. A fine-tuned language model sorts incoming customer emails by intent and filters out spam.
• Photo background removal. For a membership website, new profile photos get their background removed automatically for the profile page and for videos.

Fraud detection

A risk-analysis platform we built checks recent rounds from online card game tables while play goes on. It looks for unusual betting and for chips that move between players who work together. In one week in October 2026, it handled more than 208,000 analysis requests, close to 30,000 a day. In September 2026, half of its answers took about 70 milliseconds or less.

Our own products

• SEO operator. An AI agent does the search work for our own sites, teamarcai.com and ritm.bg. It reads the search data, plans the work and drafts articles and pages. Nothing goes live until a person approves it.
• Medical articles. For ritm.bg, our software for medical practices, AI agents research and write articles in Bulgarian. Separate AI reviewers check them for clarity and facts, and a doctor reviews them.

How the assessment runs

1. A free first call. It takes about 30 minutes, by video or phone, in your working hours, in Europe or the US.
2. Access. You give us read access to the code, the servers and a sample of the data. We sign an NDA if you want one.
3. The review. We read the code and the data. We also talk to the people who would use the AI.
4. The written plan. You get the result, the risks, the costs and the first steps.

The assessment is a small paid step, and we agree the cost before it starts.

Your data and your code

• We work under GDPR and sign a data processing agreement when you need one.
• We don't use your data to train AI models.
• You own all the code we write for you.

Questions people ask

What is an AI readiness assessment?

It is a review of your software, data and rules. It shows whether AI can work with them now, or what has to change first.

How is this different from an online quiz?

A quiz scores your own answers. We read your actual code and data, so the plan rests on what is really there.

What does it cost?

It depends on the size of the system. We agree the cost before the assessment starts.

What if we are not ready?

Then the plan says what to fix first, and in what order. Sometimes that means small data fixes. Sometimes it means modernizing the system.

If you want to know whether AI fits your software, tell us which task you want to hand over. You will hear from a person within one business day.