tech4ze

AI & ML development

Applied AI that earns its keep: LLM products, ML models and automation wired into your real workflows.

In short

AI & ML Development, at a glance

  • RAG, copilots and agent workflows built on Claude and other frontier models.
  • Forecasting, recommendation and classification models in production.
  • Document processing, support triage and back-office automation.
  • Quality benchmarks, safety rails and observability for every model.

Capabilities

From prototype to production.

We take AI from demo to dependable: retrieval-augmented chat over your data, agentic workflows, computer vision and forecasting models that run in production with guardrails and evals.

  1. 01

    LLM applications

    RAG, copilots and agent workflows built on Claude and other frontier models.

  2. 02

    Machine learning

    Forecasting, recommendation and classification models in production.

  3. 03

    AI automation

    Document processing, support triage and back-office automation.

  4. 04

    Evals & guardrails

    Quality benchmarks, safety rails and observability for every model.

How we build it

Architecture built to last.

How we put applied AI into production, so it stays accurate and observable once real users arrive.

01Experience
Product UIAssistant / API
02AI layer
LLM orchestrationRAG pipelineAgents & tools
03Models & data
Foundation modelsVector storeFine-tuned models
04Quality
Eval harnessGuardrails & PIIObservability
05Infra
Serverless / GPUCI/CDMonitoring

Trust

No science projects. Every model we ship carries evals, guardrails and observability, so quality is measured, not hoped for.

RAG over your dataEval harnessGuardrails & PIIHuman-in-the-loopCost & latency budgets

AI & ML Development questions, answered.

Still unsure if AI & ML Development is right for your project? A senior engineer will tell you straight on a free call.

We take AI from demo to dependable: retrieval over your own data, agent workflows and ML models that run in production with guardrails, evals and monitoring. A prompt in a text box is not a product.

Every model ships with evals, guardrails and observability. We benchmark quality before launch and watch it after, so you catch drift instead of hearing about it from a customer.

Usually, yes. A lot of the work is shaping data and picking the right use case, so we start with a use-case audit and spend your budget on AI that pays back, not a science project.

Whatever fits — we build on Claude and other frontier models, plus open-source and custom ML where it's cheaper or more controllable. We're not married to one vendor.

Have an AI idea worth pressure-testing?

Book a free 30-minute consultation. A senior engineer will tell you straight what's feasible, what it takes, and whether AI is even the right tool.