Frontier AI for the part after the demo.
I help founders, CTOs, and engineering teams turn promising AI prototypes into reliable production systems: agents, retrieval, vision, evals, telemetry, and the engineering glue required to make them work outside a controlled demo.
Live now: Analytics Agent in the Shopify App Store ↗
National-scale research infrastructure. Live AI products. Confidential agentic systems. One or two clients at a time.
shipping_since
2005
production_ai_systems
6+
engagements_at_once
one or two
based_in
AU · GMT+10
what invenire is
Invenire is a founder-led AI engineering studio based on the Gold Coast, Australia. I design and ship agentic systems, retrieval and vision pipelines, evaluation infrastructure, analytics products, and AI-native engineering workflows for teams that need AI to work outside the demo.
The models move quickly. I stay close to what is changing, test what matters, and bring clients the parts that hold up under production constraints.
flagship · live · production
Analytics Agent.
Six specialist agents read a Shopify merchant's GA4, Search Console and store data every day and write three to five plain-English findings. No dashboard. It is the live proof point — every architecture pattern, every eval technique, every retrieval choice I recommend on a call has already been pressure-tested here.
ANALYTICS AGENT · MISSION BRIEF · DAILY OUTPUT
mission_briefs
Six agents, one router, daily brief. Rewritten three times before the briefs stopped reading like LLM slop.
anomaly_detection
Fifteen-minute checks against a rolling baseline. Catches the 2am spike before anyone logs in.
ga4_audit
Eight checks, a 0–100 score, one-click fixes. The fixes are the hard half — and the reason this exists.
what I do
Four ways to bring in a senior AI engineer for the work that has to hold up.
01 / ai-strategy
AI strategy and architecture.
Decide what to build, what to buy, and what to ignore. I help teams find the AI opportunities that are technically possible, commercially useful, and worth the operational risk.
02 / production-ai-systems
Production AI systems.
Agents, retrieval, vision, and multi-modal workflows designed to run beyond the demo. Built with evals, telemetry, failure modes, and human review where they belong.
03 / evals-and-observability
Evals and observability.
Golden datasets, regression tests, traces, cost visibility, latency tracking, and quality gates. Trust becomes something you can measure.
04 / ai-native-engineering
AI-native engineering.
Help your team adopt Cursor, Claude Code, agent workflows, eval-first development, and AI-assisted delivery without turning the codebase into an unreviewable mess.
selected work
Production systems. Not slides.
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SHOPIFY · LIVE · 2025–
Six-agent system delivering daily Mission Briefs, fifteen-minute anomaly detection and a GA4 audit with one-click fixes to Shopify merchants. Router over specialists, LLM-as-judge evals wired into CI, full cost and latency telemetry per tool call. Live in the App Store.
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SOLO-BUILT · SELF-HOSTING · 2025–
Seven services, five languages, one operator. An autonomous engineering platform exploring how one senior operator can coordinate AI agents, externalised state, objective verification, and multi-service software delivery. The R&D layer behind the AI-native engineering practice.
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NATIONAL · GRIFFITH · 2020–2023
Australia's national platform for ecological and environmental modelling. Nine partner institutions, a decade of legacy systems re-engineered into one reproducible-by-design modelling platform — designed, architected and shipped to launch.
founder
Arve Sølland.
PRINCIPAL_AI_ENGINEER · FOUNDER
Arve Sølland is a Principal AI Engineer and founder of Invenire. He has spent 20 years shipping production software, including national-scale research infrastructure, climate and geospatial platforms, Shopify AI products, and confidential agentic systems. His work sits where fast-moving AI capability meets the slower, harder world of production engineering.
Invenire takes on a small number of engagements at a time, usually where architecture, implementation, and judgement all matter.
Have a system that has to actually work?
Thirty minutes. Bring the architecture diagram or the screenshot of the bug — whichever is closer to where you are stuck. I will tell you what I would build, what I would not, and whether I am the right person for it. If I am not, I will say so.
Discuss an engagement