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.
  • Agentic systems that plan, call tools and finish real work, with guardrails you can trust.
  • Forecasting, recommendation and classification models running in production.
  • Quality benchmarks, safety rails and observability wired into every model you ship.

Capabilities

From prototype to production.

Our AI & ML development services take AI from demo to dependable: LLM application development, retrieval-augmented generation (RAG) over your own data, AI agents development and machine learning models that run in production, not just a notebook.

LLM application development

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

Included with every engagement

  • Use-case audit
  • Production AI pipeline
  • Eval & monitoring suite
  • Team enablement

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

Investment

Average cost of an AI development project.

Every AI & ML development engagement is scoped to the use case, not a fixed package. Here's the real range our projects tend to fall into, so you can gauge where yours sits before the first call.

From $30,000

For a single LLM feature or copilot added to an existing product.

From $90,000

For a RAG system or AI agent wired into your real workflows, with evals attached.

From $220,000

For a production ML pipeline with forecasting or recommendation models at scale.

From $450,000

For a multi-model AI platform with guardrails, observability and team enablement.

Want the exact cost of your AI idea?

Tell a senior engineer what you're building on a free 30-minute call, and you'll walk away with a scoped, itemised quote — not a ballpark.

Trust

No science projects. Evals and guardrails, from day one.

Every model we ship carries an eval harness, guardrails and observability, so quality is measured against real examples, not judged by a demo that only looks convincing.

Free 30-minute call. We'll tell you straight if AI is the right tool.

  • 01Eval harness before production, not after
  • 02Guardrails, PII handling & human-in-the-loop
  • 03Cost and latency budgets set upfront

Our process

From prototype to production, safely.

Six phases with evals and guardrails built in from the start, so quality is measured at every step, not hoped for at the end.

Use-case audit & feasibility

We pressure-test the use case against what LLMs and ML models can reliably do today, and say plainly when AI is not the right tool for the job.

Output

Feasibility brief, success metrics, scope

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: RAG over your own data, AI agents development and machine learning models that run in production with guardrails, evals and monitoring. A prompt in a text box is not a product.

Every model ships with AI 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.

Yes — document intelligence is one of our most common AI automation use cases: extracting, classifying and routing contracts, claims, invoices and forms, with a human review step where the cost of a mistake is high.

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 — Claude and other frontier model integration, plus open-source and custom machine learning models where they're cheaper or more controllable. We're not married to one vendor.

Pairs well with

Built on

Common in

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.