Smart AI Development Services

Create Measurable Impact Using Artificial Intelligence

Holistic Approach that Spurs Business Outcomes

By blending business strategy, UX design, and deep tech expertise we build practical, user-centric AI solutions for a careful, solution-oriented implementation.

Faster Time to Value

With agile workflows and rapid prototyping, you can validate ideas quickly, minimize risk, and accelerate ROI.

Cross-Industry Track Record

We have successful implementations in healthcare, HR, education, or e-commerce — we know how AI can solve the complex, industry-specific pain points of different workflows.

Flexible Engagement Models to Fit Your Needs

We offer adaptable contracting options and simple onboarding processes for rapid project initiation that accommodates your needs and timelines.

Why Choose Nomtek?

We help companies release AI solutions faster and validate ideas sooner. Prioritizing outcomes, we propel your product to success with dedicated, goal-oriented teams of 2-30 specialists.

250+

Mobile native products, cross-platform apps, AI solutions, and AR/VR products shipped.

100+

Senior designers and developers supported by dedicated product managers.

10M+

Active users of a single app over the years.

10+

Average team member experience

AI Development Services

Use AI to cut manual workloads, reduce time-to-market for new features, and identify high-impact use cases before committing to full-scale investment. We can help you with key areas of articficial intelligence implementation.

AI Discovery & Strategy Workshop

Kick-start your AI initiatives with clarity and direction — for organizations seeking a clear vision of how to leverage AI and align stakeholders around a common strategy.

Identify the areas where AI services can bring the highest value to your business.
Audit your infrastructure and data to plan the optimal AI implementation approach.
Develop a strategic roadmap covering an initial proof of concept (POC) and key ROI metrics.

Generative AI PoC

Rapid prototyping for validated potential. Perfect for companies looking to explore the business impact of generative AI quickly and get tangible results without a heavy initial commitment.

Build a basic prototype (e.g., chatbot, content generation, RAG) to quickly test the technical and business viability of your solution.
Through fast iterations, you minimize risk — invest more only after you see real value.

Custom AI Model Development & Integration

From prototype to enterprise-grade product — ideal option for organizations needing scalable AI deployments that integrate with production systems and cloud services.

Design and implement AI solutions that integrate with your existing processes.
Comply with industry-specific standards (healthcare, finance, etc.) while ensuring robust security and data protection.

AI Agents Development

Automate decisions and actions — best suited for organizations aiming to reduce manual workload and accelerate operations with intelligent, autonomous systems.

Build AI agents that can delegate tasks and collaborate across tools and workflows.
Tackle domain-specific logic and complex tasks using single or multi-agent architectures.
Deploy agents that operate in dynamic environments with minimal human supervision.

Computer Vision & AR Solutions

Boost your business with image analysis and immersive experiences. For companies requiring high-precision image analysis, visual search, interactive visualizations, or immersive AR-driven user experiences.

Employ advanced object detection or recognition and augmented reality for better user engagement (e.g., e-commerce, training).
Implement vision-based solutions that increase quality control and refine workflows.

Machine Learning & Predictive Analytics

Predict and optimize to stay ahead of the curve. Recommended for organizations that want data-backed decision-making to have greater operational efficiency and strategic planning.

Design data pipelines and train predictive models for demand forecasting, pricing, user behavior, and more.
Deploy continuous learning cycles (MLOps) so models adapt to changing market conditions.

How we deliver — Our Process

Our process for artificial intelligence development services is built on experience, precision, and a commitment to delivering results at every stage of the project. We've chiseled out a process that is proven with low risk thanks to rapid iteration.

01

Alignment & risk gates

We agree on a single workflow, a hard success metric, and the non-negotiables (privacy, compliance, uptime). Stakeholders sign off. No coding until the goal and guardrails are clear.

02

Data & architecture

We audit data sources and access, set data contracts, and design an architecture that fits your stack. Security controls, observability, and cost profiles are planned upfront—so what we build can live in production.

03

Prototype under real conditions

We deliver a thin, end-to-end slice that ingests data, makes a decision, and exposes an interface or API. It runs against real workloads where possible. If it doesn’t move the metric, we iterate fast or change course.

04

Production launch

We deploy a hardened service with SLOs, dashboards, access controls, and a rollback plan. Documentation, runbooks, and operator training are delivered before handover.

05

Operations & improvement

We monitor drift, bias, latency, and business impact. Retraining happens on a cadence or when metrics shift. Changes are versioned, reviewed, and logged for audits.

Get Custom AI Development Services

Case studies

Go beyond the obvious. Co-create with teams who value impactful experiences and products.

View All Projects

app screens from Friday Harbor AI underwriting analysis

Automating mortgage underwriting with multi-agent AI

Friday Harbor

screens from Monster AI Job Search feature

Helping candidates perform better at job interviews using AI

Monster AI

Helping students learn and understand basic math using artificial intelligence

Fibo — AI Math Tutor

Leveraging AI to build a content summarization app for better knowledge retention

taim

Creating a personalized audio listening experience with content curated by artificial intelligence

Audioburst

"We consider nomtek a partner, not just a vendor. They understand our limitations and problems. Nomtek designed and developed our iOS and Android app. Their deliverables meet our expectations and we are happy with them. We talk nearly every day following an Agile methodology and release on average a version weekly."

Raz Gerstl

Raz Gerstl, VP of R&D at Audioburst

AI Technology Picked to Fit Use Case

We prioritize outcomes over tools — selecting the tech stack that best supports your project’s goals and delivers the highest value to end users. Our custom AI solutions are purposefully designed to meet your objectives efficiently, without unnecessary complexity.

See Case Studies

Taim — Content Sumarization

To streamline content consumption, we created an AI-powered summarization tool that condenses both video and text materials — regardless of length — into clear, digestible summaries. Built on GPT-3.5 and LangChain, the solution uses a custom text-splitting system to manage longer inputs within the model’s context limits. For performance tracking and analysis, we integrated Helicone alongside LangChain and OpenAI. The application was later reimagined and adapted for Apple Vision Pro, bringing immersive AI-driven summarization to spatial computing.

Helicone

Wishes — Holiday Wishes Generator

Wishes is an AI-powered app that creates personalized holiday greetings and cards from user prompts, with an optional feature to donate to charity directly within the experience. Behind the scenes, the app combines OpenAI’s language capabilities, LangChain’s orchestration, and DALL·E for image generation to deliver a seamless, custom greeting experience.

Dall-E

AI-Powered Texas Hold’em

We built a prototype of an AI- and AR-powered application designed to support poker players during Texas Hold’em sessions. Using a Lenovo AR headset, the system identifies cards through YOLO-based computer vision, while an integrated large language model offers real-time decision-making support. Developed strictly for educational use, this project does not promote or encourage gambling. The tech stack included OpenAI, YOLO, and Unity Sentis.

Yolo

Unity Sentis

Tiny Tales — Safe AI Storytelling

For the Gemini Competition, we developed a solution that combines AI-generated storytelling and visual creativity. Using Gemini to craft engaging fairy tales and Stable Diffusion to produce accompanying imagery, the entire experience was seamlessly integrated within the Google Cloud ecosystem.

Gemini

Stable Diffusion

Google Cloud

Fibo — AI Math tutor

We developed a prototype tutoring app designed to support entry-level students in learning mathematics through step-by-step guidance and concept explanations. To enhance the quality of instruction, we implemented reasoning techniques such as Tree of Thought. In testing, the AI tutor successfully solved the basic-level National Math Exam (Matura), achieving an 80% score.

LangChain

Build a Custom AI Solution

What to Consider before Creating a custom AI solution

You’re aiming for operational lift but face real risk: unclear ROI, integration delays, and weak adoption. Treat custom AI as a staged investment with hard gates. Start with one high-impact use case tied to a business metric. Budget beyond build, plan the data path, and launch where people already work.

ROI & Total Cost of Ownership

Model the use case P&L (cost per task, time saved, revenue impact). Ship a narrow MVP to a small cohort in production-like conditions within weeks, then decide go/no-go on hard KPIs. Include ongoing spend for data prep and inference. Budget for MLOps, evaluation, and security. Phase funding so larger spend follows proven value.

Don't let Integration be the Bottleneck

Most delays come from plumbing, not modeling. Map data flow end-to-end with system IDs and permissions. Confirm SSO with role-based access, then add audit logging and data residency controls (GDPR/CCPA). Use a modular stack: API gateway, RAG index, and a replaceable model layer. Set latency targets, failure budgets, and fallbacks before rollout.

Adoption & Operational Readiness

Put AI inside existing tools (CRM, help desk, IDE) so habits don’t have to change. Add human-in-the-loop for edge cases and clear ownership for review. Measure active users, task success, and defect rates; iterate by workflow, not by feature. Stand up observability for prompts and outputs, drift alerts, and incident response. Define SLAs and a rollback plan from day one.

Frequently Asked Questions

What tech stack and security do you use?

Stacks include OpenAI/Anthropic, LangChain, YOLO, Unity/visionOS, Gemini, Stable Diffusion, and Google Cloud—selected per use case. Nomtek operates under ISO 27001 for information security.

How do we start and how fast can we test value?

Begin with the Discovery & Strategy Workshop to map use cases and metrics. Next, run a Generative AI PoC to test a focused idea within weeks before scaling to production systems and cloud integrations.

What AI services do you offer?

AI Discovery & Strategy Workshop, Generative AI PoC, custom AI model development and integration, AI agents, computer vision & AR, and machine learning with predictive analytics.

Can AI replace manual tasks?

Yes, AI can replace a wide range of manual tasks, particularly those that involve data processing, classification, or pattern recognition. This includes tasks like transcribing audio, scanning invoices, and sorting support tickets. By using AItools and custom algorithms, businesses can significantly reduce human input in areas like logistics, HR, and finance. Partnering with an AI development company helps identify which business processes are the best candidates for automation. While AI doesn’t replace every human task, it adds clear value in improving efficiency and supporting business growth.

How much does an AI developer cost?

AI developer rates vary based on experience, location, and the specific technologies required. In the U.S. or Western Europe, a senior AI engineer may cost between $80 to $150 per hour, while offshore developers may charge $30 to $70 per hour. The total cost also depends on whether you’re hiring in-house or working with an AI development company. For project-based work, partnering with a firm that offers AI application development services might be more cost-efficient than building an internal team. It’s also important to consider if your project involves advanced machine learning or pre-built ai tools, which require careful strategy development and experience in AI projects.

What company is leading AI development?

Several major players lead in AI innovation, with OpenAI, Google DeepMind, and Anthropic developing foundational AI models and deep learning tools. However, when it comes to applied AI application development services, specialized firms that develop custom software solutions offer adapted to business needs. The right partner depends on whether you’re seeking research-driven innovation or practical, deployable AI solutions. Working with an AI development company that can deliver results aligned with specific industry challenges is what helps leading companies raise the bar even higher for the competition.

How much does it cost to develop an AI application?

The cost of developing an AI application depends on the complexity of the use case, the amount of data involved, and the technologies required. Projects can range from $30,000 for a basic prototype to over $300,000 for enterprise-grade solutions. Companies offering custom AI app development will typically scope the project based on features, integration needs, long-term goals, including scalability. Factors such as the type of AI models used and the need for ongoing support also impact the total cost. Engaging in AI consulting early can help clarify the budget range before development begins.

What if I already have data, can you build something on top of it?

Yes — leveraging your existing data can shorten development time and improve performance. Our team can handle data engineering, AI model training, data analysis, and deep learning to turn raw information into valuable outcomes. Whether it’s structured data for predictive tools or text for sentiment analysis, we build on what you have to deliver AI powered solutions.

Can your team help us move from PoC to a production-ready product?

Absolutely. We’re not just a prototyping shop — we’re an AI development agency with full-cycle software development services. Once a concept is validated, we scale it with production-grade infrastructure, robust security measures, scalable setup, and integrations. From MVP to deployment, the key for us is to deliver business value.

How can we integrate AI into our existing systems without breaking workflows?

We take a modular approach to AI implementation, focusing on how each component fits into your existing systems. Whether it’s plugging into APIs or deploying AI features alongside current tools, we design with compatibility in mind. The goal is to augment — not disrupt — your operations.

What’s the fastest way to test AI without investing a huge budget upfront?

Start with a proof of concept focused on a single use case. Our AI software development services include rapid prototyping — using pre-trained AI algorithms, fast iteration cycles, and off-the-shelf components to minimize cost and build something highly workable within weeks. We’ll help you prove value before investing further.

Is it possible to build a lightweight prototype before committing to full development?

Yes — this is a core part of our approach. As an AI app development company, we create working prototypes that let you user fit and technical feasibility. We often recommend this path to reduce risk and gather actionable feedback quickly, so you only scale what works.

How do I validate if generative AI will actually work for my use case?

We specialize in building fast, low-risk prototypes to test ideas before you invest in full-scale development. Whether you’re exploring natural language processing, content generation, or recommendation systems, we assess the viability using tools like RAG pipelines and lightweight interfaces. The goal is early results, not overengineered solutions that don't have real life application.

What kind of AI use cases make sense for my industry?

Every industry has its own pain points — whether it’s inventory management, customer service, document processing, or decision support. We work across sectors like healthcare, HR, education, and e-commerce to identify AI use cases with real business potential. Our focus is on solving actual problems, not just experimenting with technology.

How do I know if my company is ready to implement AI?

Readiness isn’t about having everything figured out — it’s about knowing what business outcomes you want to achieve. In our AI Discovery & Strategy Workshop, we help you assess data quality, infrastructure, and existing workflows to determine if adopting an AI system is feasible and how it could benefit your workflow. Together, we map opportunities and limitations so you can make informed decisions with minimal risk.

What is the importance of adaptability to user behavior in AI-powered mobile apps?

Adaptability to user behavior is essential to make a mobile application popular among target audiences in a too often saturated mobile app market. AI lets developers customize in-app features and services according to individual user preferences, thus improving user satisfaction and retention.

What are the main benefits of using AI-integrated mobile apps?

AI-integrated mobile apps let developers simplify often complex processes and deliver personalized experiences that results in enhanced user engagement.

What is the role of AI in mobile applications?

AI plays a crucial role in personalizing the mobile app experience for users, allowing them to enjoy tailored content and custom interfaces that reflect their individual preferences, behavior, and context.

How to integrate AI in mobile app?

To effectively integrate AI into a mobile app, software development teams should design changes to the user interface, gather data sets and training samples, prepare the data for use in AI/ML development projects, and implement an effective security solution. Or you can integrate OpenAI's ChatGPT API to enjoy the benefits of conversational AI at a relatively low price.