Cruzata

AI that solves a business problem, not a demo

Many AI projects stall because they start with a technology instead of a problem. We begin with the process, decision or data that matters most, then choose the simplest approach that works, whether that is a rules engine, a classic machine learning model or a large language model.

Our engineers design, build and deploy AI features into your existing products and workflows, with the monitoring, security and governance that production use demands.

  • Use-case discovery and feasibility
  • Data pipelines and model engineering
  • Secure deployment and monitoring
  • Responsible AI and human-in-the-loop design

Capabilities

LLMs
Chat, search, summarise
ML
Prediction, scoring
Vision
Detect, read, classify
NLP
Extract and analyse

Where AI delivers value

Examples of problems we help teams solve.

Answer questions instantly and personalise interactions.

  • AI chat and voice assistants
  • Recommendations
  • Sentiment analysis
  • Smart search

Automate repetitive work and reduce manual errors.

  • Document processing
  • Demand forecasting
  • Quality inspection
  • Anomaly detection

Prioritise leads and create content faster.

  • Lead scoring
  • Content generation
  • Churn prediction
  • Campaign analytics

Find answers in company data and flag issues early.

  • Enterprise search with RAG
  • Contract analysis
  • Fraud signals
  • Compliance checks

Our AI delivery approach

  1. 1

    Opportunity workshop

    Rank use cases by value and feasibility.

  2. 2

    Data readiness

    Assess data quality, access and privacy.

  3. 3

    Proof of value

    Small, time-boxed build to test the idea.

  4. 4

    Productionise

    Integrate, secure and scale.

  5. 5

    Monitor & improve

    Track quality, drift, cost and feedback.

AI technology stack

Models & APIs

  • OpenAI GPT
  • Anthropic Claude
  • Google Gemini
  • Llama / Mistral
  • Hugging Face
  • Whisper

Frameworks

  • Python
  • PyTorch
  • TensorFlow
  • scikit-learn
  • LangChain
  • LlamaIndex

Data & infra

  • pgvector / Pinecone
  • Weaviate
  • Airflow
  • MLflow
  • AWS SageMaker
  • Azure AI
  • Docker
FAQ

AI Solutions: frequently asked questions

We provide AI strategy and use-case discovery, machine learning and LLM application development, chatbots and agents, document and vision AI, data pipelines, and deployment with monitoring.

Not always. Modern language models can deliver value with little training data, using your documents through retrieval. Predictive models need historical data, and we assess readiness first.

We design for privacy: data minimisation, access controls, encryption and, where required, private or self-hosted models so sensitive data does not leave your environment.

A focused proof of value typically takes two to six weeks. Production deployment depends on integration and governance needs.

Yes. Most of our AI work is adding intelligent features to existing products, through APIs and services that fit your stack.

Start your ai solutions project

Tell us what you are planning. We will reply within one working day with questions or a clear next step.