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DevWayz
AI & Automation

AI Agents & Process Automation

Most agent demos fall over the moment they meet a real business. The model is rarely the hard part — the hard part is the system around it: retrieval that returns the right context, tools that fail safely, evaluations that catch regressions before your customers do, and a human gate on anything expensive or irreversible. That is what we build.

Scope this projectTalk to an engineer

What we do

  • Tool-using LLM agents & MCP servers
  • Document & RAG pipelines
  • Human-in-the-loop review workflows
  • Evaluation, guardrails and observability

What you end up with

  • One agent live in production behind a human approval gate
  • An evaluation harness that runs on every change
  • Full tracing — every step, tool call and cost per run
  • A documented rollback path and failure playbook

How an engagement runs

  1. 01

    Discovery & scope

    A working session to map the problem, the constraints and the smallest thing worth building first.

  2. 02

    Architecture & design

    System design, data model and interface work — reviewed with you before a line of production code exists.

  3. 03

    Build in two-week slices

    Shippable increments every sprint, deployed to a staging environment you can click through.

  4. 04

    Launch & operate

    Hardening, observability and an agreed support model. We stay on after go-live.

Proof

Glaukus — Glaukus — Fishing Pond Automation

Glaukus

An IoT and automation platform that continuously monitors water chemistry across fishing ponds, predicts unsafe conditions and triggers aeration and feeding cycles before marine stock is at risk.

Questions we get asked

How long before an agent is doing real work?
Six to eight weeks for a first agent in production. Weeks one and two are discovery and a scored shortlist of candidate processes; the rest is building, evaluating and shipping the highest-value one behind a human gate.
Where does our data go?
Wherever you need it to. We default to EU regions and can run entirely within your cloud account. For regulated work we scope model choice and data residency before writing any code.

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