We build your AI future.

Two pillars: AI-native apps, and custom agents with MCP. Both grounded in what we've shipped ourselves. Both focused on production — not demos.

FIG. 01 — SERVICE · AI-NATIVE APPS

AI-native app development.

Full-stack mobile and web apps where AI isn't a bolted-on feature — it's the foundation. We design for latency, cost, evaluation, and failure modes from day one.

#full-stack#mobile#web#edge-AI#agriculture#industrial#offline

DELIVERABLES · AI-NATIVE APPS

01
Architecture + spec
Edge vs. cloud split, model selection, evaluation harness, cost model. Before line one of code.
02
Full-stack build
Mobile (iOS/Android), web, backend, infra. One team, one codebase, shipped to production.
03
Edge-AI pipelines
On-device inference, proactive notifications, sync-on-reconnect. Built for the field, not the office.
04
Eval + ops
LLM evals, tracing, regression suite, on-call handoff. The stuff that keeps it alive post-launch.

FIG. 02 — SERVICE · AGENTS & MCP

Custom AI agents & MCP integration.

We build autonomous agents that actually work in production. Using Model Context Protocol, we securely connect your proprietary data and tools to LLMs — so AI can act on your business, not just talk about it.

#MCP#agents#B2A#tool-use#evals#secure#observability

DELIVERABLES · AGENTS & MCP

01
MCP server(s)
Custom Model Context Protocol servers exposing your data & tools securely to any LLM client.
02
Purpose-built agents
Scoped autonomous agents with guardrails, human-in-the-loop gates, and per-action audit trails.
03
B2A workflows
Business-to-AI workflows that replace internal ticket-chains and repetitive ops with reliable automation.
04
Evals + monitoring
Golden sets, drift alarms, tool-call auditing. You always know what the agent did, and why.

FIG. 03 — ENGAGEMENT MODELS

Three ways to work together.

MODEL · 01

Sprint

2–4 weeks

Architecture audit, AI feasibility study, or a pointed prototype. Fixed scope.

from A$12k

MODEL · 02

Build

6–16 weeks

Full product build — design, engineering, deployment. Weekly demos, live repo from day one.

from A$60k

MODEL · 03

Embedded

ongoing

We join your team for a quarter or more. MCP infra, agent tuning, on-call coverage.

monthly retainer

FIG. 04 — PROCESS

Product-first, always.

STEP 01

Map

Align on outcomes, constraints, existing systems. No slide-deck theatre.

STEP 02

Architect

Model selection, data flow, eval harness, cost model — written down before code.

STEP 03

Prototype

A working slice in week 1–2. Real models, real data, real users where possible.

STEP 04

Harden

Evals, observability, failure-mode handling. AI that doesn't just pass demos.

STEP 05

Ship

Production deploy, on-call handoff, runbook. You own it afterwards.

FIG. ∞ — START

Bring us your hardest problem.

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