Rediza, LLC — AI & Infrastructure

We build the intelligence, and the ground it runs on.

An engineering firm for teams putting AI into production — the models, the platform underneath, and the on-call rota that keeps both standing.

Applied AI Cloud Architecture Retrieval Systems Kubernetes Agent Platforms Observability Trip Planning FinOps

Three practices

One firm, three things we are genuinely good at.

Most of our work sits at the seam between a model that works in a notebook and a system a business can depend on. We take responsibility for both sides of that seam — and we run a product of our own so we stay honest about it.

01

AI Services

Retrieval systems, agent workflows, evaluation harnesses and fine-tuning. We start from the decision the model is meant to support, not the demo.

  • RAG & retrieval
  • Agents & tools
  • Evals
  • Inference serving
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02

Infrastructure Services

Cloud architecture, Kubernetes, infrastructure as code, CI/CD and the observability that turns an incident into a five-minute question.

  • AWS / Azure / GCP
  • Terraform
  • Kubernetes
  • Cost engineering
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03

AI Trip Planning

Itinerary intelligence as a service — for travel brands who want planning inside their own product, and for travellers who want it directly.

  • Itinerary engine
  • Live pricing
  • White-label API
  • Concierge
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Anyone can demo a model. Far fewer can keep one answering at three in the morning, under load, with someone's money on the line. That gap is the entire job.

Infrastructure

Built to be woken up at 3 a.m.

Production AI is an infrastructure problem wearing a research hat. GPUs are scarce, context windows are expensive, and latency budgets are unforgiving. We design for that reality from day one.

  1. Architecture Multi-region, multi-account landing zones with blast radius drawn on purpose.
  2. Delivery Everything in code. Reproducible environments, gated deploys, instant rollback.
  3. Observability Traces through the model call. Token spend and p95 on the same dashboard.
  4. Cost Unit economics per request, per tenant, per feature — visible before the invoice.

Flagship service

AI Trip Planning that survives contact with a real trip.

A planner that reasons about opening hours, travel time between two points, budget, and the fact that nobody wants three museums in one afternoon.

  • Constraint-aware. Budget, pace, dietary needs and mobility are inputs, not afterthoughts.
  • Grounded. Live pricing and availability, so the plan is bookable, not imaginary.
  • Embeddable. Ship it inside your own product through one API.

How we operate

Availability target we design and operate managed platforms to.
p95 budget for retrieval on our reference stack, before generation.
24/7 On-call coverage on managed engagements, with a named engineer.
Infrastructure defined in code. No console-clicked production.

Approach

Small team. Short loops. Nothing thrown over a wall.

01

Frame

A week of getting specific: the decision, the data, the constraint that actually binds. You get a written architecture either way.

02

Prove

A thin slice, running on your infrastructure, measured against an eval set we agree on before we start.

03

Harden

Load, failure modes, cost per request, rollback. The unglamorous work that decides whether it ships.

04

Operate

We run it with you, or hand it over with the runbooks and the tests to keep running it without us.

Tell us what you're trying to ship.

We'll tell you honestly whether we're the right firm for it — and what we'd do first if we were.