AI Agents Development & Integration

Why Choose Nomtek?

We help teams ship and improve products with focused senior delivery. We run pilots that prove value quickly, then scale what works.

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

Why AI Agents?

Legacy code doesn’t fail because teams don’t care. It fails because modernization competes with roadmap work, and the backlog never gets smaller. AI agents help when you treat them as a delivery system, not a coding trick.

Parallel Execution

The biggest speed multiplier. One engineer can supervise multiple agents working at the same time on 30-minute to 3-hour tasks.

Developer Time First

Tokens cost money, but developer hours cost more. The workflow is designed to reduce supervision overhead and keep review manageable.

Proof Over Promises

We start with a scoped pilot, measure output, then decide how to scale across the codebase.

Built for Enterprise Environments

Agents can move fast. Enterprise codebases demand control. We design modernization work so agents help where they’re strong, and pause where judgment is needed.

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Human Oversight

Architecture, risk calls, and final merges stay with your engineers. Agents surface context and wait for approval when the change impacts core behavior.

Isolated Workstreams

We run one task per isolated workstream to avoid conflicts and keep agents productive while other work continues.

Feedback Loop Through Tests

Agents don’t just “finish.” They validate. CI checks and functional tests are part of the loop so output is verifiable, not just plausible.

Task-Sized Delivery

Work is decomposed into agent-sized units (30m–3h). That keeps context under control and improves consistency across a long run.

Task Routing

When input is ambiguous or risk is high, the agent stops, explains what it found, and routes the decision to the right person.

Access Boundaries

We define what the agent can see and touch: code, docs, or designs. Sensitive data paths are handled through restrictions, anonymization, or local workflows.

What AI Agents Can Do in a Modernization Pilot

Agents support modernization across product engineering work, not by replacing developers, but by taking on execution-heavy tasks under supervision.

Refactoring & Cleanup

Reduce legacy drag with structured refactors, targeted cleanup, and consistency work that usually stalls behind feature delivery.

Migration Support

Handle framework/library upgrades and repetitive conversions with a proven pattern that can be scaled across many similar components.

Test Coverage Lift

Add or adjust tests where they unlock safer change. Agents can draft tests and iterate based on failures, with engineers reviewing intent and gaps.

UI Consistency Work

Where design access is approved, agents can iterate toward UI parity. Engineers keep control of architecture and edge-case behavior.

Content Operations

Draft, review, and publish content across platforms. AI agents maintain consistency and accelerate publishing cycles with minimal oversight.

Knowledge Capture from Code

For large codebases, we prioritize “research first.” Agents explore the code, write findings to a file, and then work from that shared context.

What sets Nomtek apart is their cross-functional approach: they assembled a diverse team with expertise spanning UX, development, and product strategy to ensure that the solution would be practical, scalable, and aligned with our long-term goals. Their collaborative mindset and ability to explain complex topics in an accessible way made the entire process feel like a true partnership.

We’re excited to continue this journey together and can confidently recommend Nomtek as a reliable, proactive, and thoughtful partner for any AI-driven product development.