Custom AI
development services

Building a tailored AI solution takes time. If speed is your main priority, an off-the-shelf tool may seem like the best option. It takes a few hours (sometimes, minutes) to buy. Installing and integration may take a few days. And you often only need to invest in basic training for everyone to start using it.

Custom AI development for business solutions can be time-consuming. The development team must first understand your requirements. Designing and planning the product takes time. Once built, it must be tested and debugged before it can be deployed.

Then, you will need to train your team on how to use it because there will not be any training manuals available online.

Of course, with our rapid prototyping, you do not have to wait months to see results. We can deliver a working MVP in just two weeks. This way, you have something tangible to validate and refine while the full solution is being built. We also provide tailored onboarding and training, so your team can start using the AI tool confidently from day one, maximizing the benefits of our consulting services.

AI needs data to power it. These systems use machine learning to understand the relationships between various data points. That is how they can analyze fresh inputs to make predictions.

AI-ready data needs to be:

Clean: Free from duplicate entries, errors, typos, inconsistent formatting, and irrelevant noise.

Complete: Sufficiently comprehensive, with minimal missing values or large gaps that reduce model accuracy and reliability.

Consistent: Standardized across systems and sources, with values in the same formats and units.

Accurate: Matches the real-world truth, or the model will make flawed predictions.

Relevant: Directly tied to the problem you’re solving, as unrelated data points only add to the clutter.

Timely: Up to date, with the right frequency of refresh, because outdated data can make models less useful.

Sufficiently large and diverse: Enough volume and variety to capture the full range of scenarios to prevent creating an unreliable or unfair model.

Well-labeled: If you’re training AI models that require labels (e.g., “spam” vs “not spam”), the labels must be accurate and consistently applied.

Accessible and structured: Stored in a way that’s easy to retrieve, query, and process, not buried in PDFs or inconsistent spreadsheets.

Compliant: Collected and stored in line with privacy and regulatory requirements (GDPR, HIPAA, etc.), so you can use it without legal risk.

If your business data is not AI-ready, it might seem easier (and more efficient) to buy an already-trained solution and plug your data into it.

If that’s your only concern, though, Infinum can help. Our enterprise-grade data engineering services transform fragmented, messy, or incomplete datasets into structured, compliant, and AI-ready pipelines. 

We clean and prepare your information, ensure it is properly labeled, and set up ongoing processes to keep it accurate and current. That way, you can build a strong foundation for your ML model without having to compromise on quality or compliance.

Generic tools are designed for simple applications. If your challenge is basic, rule-based automation, one of these tools might be enough in the short term.

But business needs rarely stay simple. What starts as simple automation might need to grow in scope as you expand your business. With an off-the-shelf solution, you end up buying more features that are not quite ideal for you, unlike custom software that is tailored to your needs. Or you have to switch to another product that offers the additional functionalities you want.

That is where using Infinum’s custom AI development services can be helpful. We scope projects so you get what you need today. At the same time, we design for the option to expand into more advanced AI tomorrow.

Custom AI requires upfront investment, which can feel risky compared to subscription-based tools. Comparatively, it is much cheaper to buy a product in the market. The development cost for such a solution is distributed among all its buyers. 

A custom AI product, on the other hand, is more expensive initially. You pay for all its costs, including design, development, deployment, and maintenance.

Infinum reduces that risk with an iterative approach—starting with prototypes and proofs of concept before scaling to full deployment. That way, you invest gradually and let the product “pay for itself.” You can use analytics and feedback to determine which features should be prioritized. That makes the solution even more valuable to users.

Artificial intelligence can seem overwhelming if your team does not have deep technical expertise. Off-the-shelf tools come with predefined dashboards and manuals. That makes them seem easier to manage.

Building custom AI solutions often involves advanced concepts like data engineering, model training, and continuous monitoring. They require onboarding and governance processes that may feel intimidating for a team that has never worked with AI before.

At Infinum, we make complexity manageable. Our engineers design solutions that are intuitive, well-documented, and supported by training tailored to your team. 

We handle the heavy lifting—from architecture to monitoring. You get the power of custom AI without being burdened by the technical details. Your team gains the confidence to use and scale AI, while we stay by your side to ensure it performs as expected.

AI is not a one-and-done project. Once deployed, models can lose accuracy as new data is introduced and user behavior shifts. Or, your business goals evolve. Off-the-shelf solutions take the burden of maintenance off your shoulders.

However, while they may update the product, you have little control over when or how they adapt. Without proper monitoring and retraining, your AI risks becoming less reliable, less compliant, and ultimately less useful to your business.

With Infinum, maintenance is built in from the start. We provide continuous monitoring, performance tracking, and proactive retraining to ensure your AI stays aligned with your goals as part of our AI integration services.

Our team also helps you adapt the system as your business changes—whether that means integrating new data sources, scaling to more users, or extending features. This way, your AI solution remains accurate, compliant, and valuable for the long term.

AI systems often deal with sensitive data—from customer information to financial records and healthcare details. Mass market solutions are usually black boxes, meaning you cannot see how they process or store data.

This lack of transparency makes it difficult to guarantee compliance with regulations like GDPR or HIPAA. Even when the vendor is reputable, improper integrations or misconfigurations can still introduce security risks.

At Infinum, compliance and security are never afterthoughts; they are integral to our AI services. As an ISO-certified company, we design AI systems with governance, privacy, and security baked in from day one.

We also conduct cybersecurity testing on both solutions we build and third-party applications to uncover vulnerabilities and strengthen defenses. The insights gained from this work feed back into our development process. We ensure your AI solution is both secure and compliant, now and in the future.