Adptiv is the applied AI consultancy of Lachlan Gill, a Melbourne-based consultant who designs and ships production AI systems, agentic workflows and internal platforms for founders, ops leaders and scaling teams.
Applied AI consultant who ships production systems, not slide decks. Five years across RevOps, marketing operations and applied AI — now focused on private LLMs, agentic workflows, and the unglamorous data plumbing underneath.
I work across the full AI delivery stack: designing private LLM solutions, building agentic workflows in n8n, Zapier and Python, standing up sovereign deployments on AWS Bedrock, and shipping the internal platforms that make the whole system usable. Currently building Capability Astra — a private LLM and knowledge assistant — end-to-end from requirements and ingestion through access controls, testing and deployment.
My background is marketing ops and RevOps — HubSpot, Salesforce and SugarCRM migrations and the unglamorous data hygiene work in between. That history means I obsess about the messy seams where AI meets a real business: data quality, adoption, governance, and the workflows people already trust.
Multi-step automations and agentic systems that handle real work end-to-end — from outbound and reporting to internal ops. Built in n8n, Python, OpenAI, Anthropic, Zapier and Make with proper monitoring, fallbacks and clear ownership.
Full-stack platforms for internal teams or external users — knowledge assistants, copilots, customer-facing tools and admin dashboards. Built on React, TypeScript, Supabase, AWS Bedrock and Tailwind.
For teams that know they need AI but aren't sure where to start. Discovery workshops, opportunity mapping, prototype build and a roadmap to production delivery — ending with a shipped first project, not a strategy document.
Lachlan Gill — Adptiv. Based in Melbourne, VIC, Australia. LinkedIn: linkedin.com/company/adptivai. Get in touch via the contact form on the site. Open to projects, typical reply within 24 hours.
Production AI systems: agentic workflows in n8n and Python, retrieval-augmented assistants on Supabase and pgvector, private LLM deployments on AWS Bedrock, and the internal platforms that wrap them. Every engagement ends with something live in your stack — not a slide deck.
Lachlan Gill, an applied AI consultant based in Melbourne, Australia. Five years across RevOps, marketing operations and applied AI, now focused on private LLMs, agentic workflows and the data plumbing underneath.
Three core offerings: Automation & Agent Workflows, Platform Creation, and AI Discovery & Delivery — each ending in a shipped, owned system rather than a strategy document.
n8n, Zapier and Make for orchestration. Python, TypeScript and React for custom builds. OpenAI, Anthropic and AWS Bedrock for models. Supabase, pgvector and Postgres for data and retrieval.
Yes. Based in Melbourne, working with founders, ops leaders and scaling teams globally. Typical reply within 24 hours.
End-to-end delivery by one practitioner who owns the system in production — from discovery and data wiring through model selection, access controls, testing and deployment. No hand-offs, no junior teams, no theoretical roadmaps.
Discovery sprints run one to two weeks. Most automation builds ship in three to six weeks. Larger platform engagements run six to twelve weeks with incremental releases — you see something working inside the first fortnight, not at the end.
Yes. Retainers cover monitoring, prompt and model tuning, integration changes and feature iteration. You can also take full ownership at handover — every system ships with documentation, tests and the credentials in your accounts.
Send a short note via the contact section. First reply usually within 24 hours, followed by a 30-minute call to scope the problem. From there, a short written proposal with timeline, deliverables and a fixed price before any work begins.
Last updated: June 2026.