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AI Engineering

Most AI projects don't fail at the model. They fail around it - messy inputs, no route to production, no way to tell whether it worked.

Arocom is an AI engineering partner that builds systems designed to run in production from day one. We develop custom machine learning models, generative AI applications, and autonomous agents that plug into the tools your teams already use, and we stay accountable for accuracy, latency and cost once they’re live.

Our Expertise Across the AI Spectrum:

Agentic AI & Intelligent Automation

  • Autonomous and multi-agent system design
  • Tool and API orchestration
  • Workflow automation across business systems
  • Human-in-the-loop approval flows
  • Agent observability and tracing
01

Generative AI & LLM Applications

  • RAG and knowledge search systems
  • LLM fine-tuning and instruction tuning
  • Document intelligence and extraction
  • Conversational assistants and copilots
  • Prompt engineering and evaluation harnesses
  • Guardrails, safety and output validation
02

Computer Vision

  • Object detection and classification
  • OCR and document digitisation
  • Visual quality inspection
  • Video analytics and activity recognition
  • Edge deployment and model optimisation
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Custom Machine Learning Development

  • Model design, training and tuning
  • Feature engineering
  • Classification, regression and clustering
  • Recommendation engines
  • Anomaly and fraud detection
  • Model evaluation and benchmarking
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Why Arocom for AI Engineering

We start with the decision, not the algorithm

We map the business decision the model is meant to improve before selecting an approach - which is often why a simpler, cheaper model wins.

Engineering rigour on non-deterministic systems

Evaluation suites, guardrails, prompt versioning and human-in-the-loop review are standard on every generative AI engagement.

Production-first, not proof-of-concept

Every model we build ships with monitoring, retraining triggers and a rollback path. MLOps is part of the build, not a later phase.

Domain-fluent teams

Deep experience across healthcare, finance, logistics, manufacturing, retail and aviation means less time spent explaining your business to us.

Technologies We Work With

Frameworks

  • PyTorch
  • TensorFlow
  • scikit-learn
  • Hugging Face
  • LangChain
  • LlamaIndex

Models & platforms

  • Amazon Bedrock
  • Azure OpenAI
  • Google Vertex AI
  • Open-weight models

MLOps

  • MLflow
  • Kubeflow
  • SageMaker
  • Airflow
  • Weights & Biases

Serving & data

  • Docker
  • Kubernetes
  • Ray
  • Pinecone
  • Weaviate
  • pgvector

Building on data pipelines and warehouses? See our Data Engineering services – the foundation most AI programmes depend on.

How We Engage

01

Discover
We assess your data, systems and the decision you're trying to improve, then define wh at success looks like in measurable terms.

02

Prototype
A working proof of value against your real data, typically within weeks, with a clear go/no-go.

03

Engineer
Production build with testing, security review, MLOps and integration into your existing stack.

04

Operate
Monitoring, retraining, cost optimisation and iteration as your data and business shift.

Have an AI problem worth solving?

Tell us what you’re trying to improve. We’ll tell you honestly whether
AI is the right tool – and what it would take to build.

Questions about service

We provide AI strategy, machine learning model development, predictive analytics, NLP, computer vision, generative AI, recommendation systems, and AI-powered automation solutions.

Yes. We develop tailored AI and machine learning solutions aligned with your business goals, workflows, and industry-specific requirements.

Yes. We work with structured, semi-structured, and unstructured datasets including text, images, videos, sensor data, and enterprise data sources.

Absolutely. We integrate AI and ML models into web applications, enterprise platforms, mobile apps, APIs, and cloud environments.

We support healthcare, retail, finance, logistics, manufacturing, education, aviation, energy, and various other industries.

Yes. We build predictive models for forecasting, demand planning, fraud detection, risk analysis, customer insights, and operational optimization.

Yes. We develop Generative AI applications including chatbots, AI assistants, document intelligence, knowledge search systems, and workflow automation.

We use data validation, feature engineering, model evaluation, continuous monitoring, and retraining strategies to maintain model performance and reliability.