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AI ENGINEERING STUDIO

AI that ships.Not AI that demos.

Most AI pilots never reach production. We build the ones that do — agents, retrieval systems, and vision models running against real users and real data.

02 / 06

RAG & Knowledge Systems

03 / 06

Computer Vision

04 / 06

iGaming Platforms

05 / 06

Full-Stack Product

06 / 06

ML Engineering

14

Technologies

8+

Years of Engineering Experience

Expertise

Engineering Intelligence Into Your Business

From AI agents and knowledge systems to full-stack products and cloud infrastructure, we design and build technology around the way your business actually works.

Use cases

AI use cases for every industry

How we work

From idea to production

  1. 01

    Discovery

    We scope the problem, the data you actually have, and what a successful pilot would need to prove — before any code gets written

  2. 02

    Pilot

    We ship a narrow, measurable pilot fast, against real data and real users, so we validate the approach before investing in the full build.

  3. 03

    Build

    We harden the pilot into a production system — the error handling, monitoring, and edge cases a demo can skip but production can't.

  4. 04

    Rollout

    We roll out with a change management plan, so the people using the system day to day are ready for it, not surprised by it.

  5. 05

    Support

    We monitor the system in production, retrain and tune as data drifts, and stay on to support it after launch.

FAQ

Questions, answered

How much does custom AI development cost?
 
The cost of custom AI development depends on the scope, complexity, integrations, data requirements, technology stack and deployment environment. NeuroML.AI first evaluates your requirements and then recommends an appropriate architecture and development approach.
Can you integrate AI into existing software?

Yes. We integrate AI capabilities into existing web applications, mobile apps, enterprise software and internal systems. Depending on the use case, integrations can include LLMs, RAG pipelines, AI agents, APIs, databases, automation workflows and third-party platforms.

Do you build RAG applications?
 
Yes. We build Retrieval-Augmented Generation (RAG) systems that connect AI models with business documents, databases and knowledge sources. Our approach includes document processing, retrieval, context management, evaluation and production deployment.

Get in touch

Tell us what's stuck

Send us the shape of the problem — the pilot that stalled, the retrieval that hallucinates, the model that drifted. We'll tell you honestly whether we're the right people for it.