Slow, manual processes are the tax you pay on every deal, every decision, every report.
We build collaborative AI that saves you from the drag: the reporting and analysis that eats your finance and ops team's week, and the signal that tells your sales team exactly who to call and why now. The leverage to do more and grow faster, run by your team.
Every cycle, the same drag repeats. Reports get built by hand. Analysis waits in a queue behind one busy person. The best accounts go cold because no one had time to spot the trigger. The work is slow, manual and fragile, and it quietly taxes every report, every decision and every deal.
What firms keep telling us:
One way of working. Two ways it pays off.
We build AI on your data and hand it over so your team owns it. We do that for the work that drags (reporting, analysis, documents) and for the work that finds revenue (who to call, why now). Start with whichever is costing you most right now.
Operations Studio.
Your reporting, analysis, finance, document and knowledge work, done by AI your team owns. The by-hand month-end close, the analysis that waits on one overloaded person, the document review done line-by-line: built into systems and handed back to you.
Revenue Intelligence.
Find, win and keep your next customer, sourced from the public institutional record. Spot the buying signals your competitors are missing, in the same week they land, so your team works leads with a verifiable, current trigger instead of the same bought list everyone else has.
Custom-built for the way you work. Owned by your team.
No two firms run the same way, so nothing we build is off the shelf. We embed with your team, learn your strategy, systems and data, and surface the opportunities where AI pays back fastest. Then we build it on your data and hand it over, so your team owns the leverage.
Our processWe start with your situation, not a tool. We map your processes, systems, data and the work that drags, so we target the few places worth building first instead of a long wish list.
OutcomesWe blueprint the system before we build it: the workflow, the data, the guardrails and how your team will run it. Adoption is built in from day one, so nothing surprises you later.
OutcomesWe turn the blueprint into a working system: built, integrated, tested and validated on your data. What ships is production-grade and proven against real work, not a demo.
OutcomesWe hand it over so your team owns it: deployed, your people trained, the runbook documented. The system runs without us. You own the machine, not the dependency.
OutcomesYou own the machine, not the dependency.
We build it and hand it over, so the asset and the IP stay in-house, run by your own team.
No training on your data.
We work on enterprise and API tiers where your prompts and outputs are never fed into model training. Your firm's data stays out of anyone's training corpus.
Upskilled to own it, not just handed it.
Hands-on training around your team's real work. Your people run and improve the system themselves, with the option to keep us on as partner when you need further refinements.
Delivered in production. Across both applications.
Hands-on delivery in professional-services environments. Tap any card to expand.Operations reporting From a monthly cycle to a daily decision dashboard +
Context
A financial-services lender ran customer-service reporting on a slow monthly cycle. Every decision about customer experience sat weeks behind the data.
Business challenge
A heavily manual, month-end process left the service team unable to steer experience in real time or react to issues as they emerged.
Solution
The cadence was re-engineered from monthly to daily: automating data extraction, building the back-end ETL to aggregate a daily pipeline, and rebuilding the front-end dashboards to surface granular KPIs the team owns and runs.
Outcome
Reporting moved from a monthly cycle to a daily decision dashboard, owned and run by the in-house team, directly contributing to a 30% uplift in Net Promoter Score.
Data migration An AI-assisted engine for legacy-code migration +
Context
Complex legacy SQL reporting jobs needed to migrate onto a modern cloud data platform, with backend table structures changing underneath them at the same time.
Business challenge
Hand-refactoring each job the traditional way took days to weeks, throttling delivery of critical reporting infrastructure.
Solution
An AI-assisted migration workflow was built: feeding a comprehensive old-to-new database mapping as context to an agentic coding assistant that translated dense legacy SQL into optimised, production-ready Python jobs.
Outcome
Migration and development time fell by 60-70%, accelerating delivery of critical reporting infrastructure, in a repeatable workflow the in-house engineers run themselves.
Knowledge work An internal knowledge agent that arms customer-service officers mid-call +
Context
Customer-service officers needed fast, accurate answers across finance products, policy and procedure while live on calls with customers. The agent assists the officer, never the customer directly.
Business challenge
Officers had to put customers on hold to search documents by hand or escalate to senior staff, breaking call flow and slowing new-starter onboarding.
Solution
A knowledge-graph-powered agent was built over the organisation's own documentation, used by the service officer, with a wiki-style index of structured summaries and section references so the AI retrieves accurate, contextual answers rather than guessing from raw chunks.
Outcome
Officers get instant, sourced answers mid-call without holds, deployed and run daily by the in-house team; escalations to senior staff dropped and new-starter onboarding sped up.
Win-back & retention An outreach agent that briefs every call with a reason and an offer +
Context
End-of-term finance customers who slipped through frontline follow-up were worked by a central retention manager using generic scripts and one-size-fits-all offers.
Business challenge
Generic outreach converted poorly. The manager had no fast way to understand each business customer or match the right offer to the right account.
Solution
An agent was built that researches each B2B customer from public web sources, combines that with their vehicle, finance product and contract terms plus live campaign offers, and produces a personalised call brief: talking points and the single best offer to lead with.
Outcome
Retention improved with the shift to personalised, context-rich outreach; generic scripts were retired, the manager now opens every call with full business context and a tailored offer, and prep time per call fell sharply.
Segmentation modelling Machine-learning segmentation that reshaped retention offers +
Context
Retention and marketing teams needed to understand how different customer segments behave at end-of-term to personalise campaigns and offers.
Business challenge
A single, undifferentiated approach ignored real behavioural differences. A retiring customer, a young professional and a business owner were all treated alike, leaving conversion on the table.
Solution
A segmentation model was built across age, income, profession and business type, then retention behaviour was analysed within each segment to recommend how outreach and offers should differ by profile.
Outcome
Behaviour-based segments changed how the product team structured offers and how outreach was targeted across retention, marketing and product pricing, for example surfacing high-credit professionals eligible for a rate-based retention incentive.
Pipeline visibility End-to-end retention-funnel visibility for a CRM rollout +
Context
A CRM was rolled out to manage customer retention at finance end-of-term, and reliable outputs, funnel visibility and insight were needed to drive outcomes.
Business challenge
Without end-to-end funnel data, leadership couldn't see where retention leads were lost, which frontline managers were working the tool, or why cases were won or lost.
Solution
A funnel dashboard was built tracking every stage from first contact (by channel) through appointment, deal and conversion, layered with won/lost reason analysis and operational tracking of frontline tool adoption, surfaced to an executive steering committee.
Outcome
Full-funnel retention visibility enabled a data-driven strategy; segment-level insight changed how offers were structured, and activity tracking drove tool adoption across the network.
One path, two applications.
AI Opportunity Audit +
A scoped, prioritised map of where AI earns its keep in your firm, with a costed recommendation for what to build first. Fixed-scope, run in days, not open-ended consulting.
- Operations StudioWe map your reporting, analysis, finance and document work and rank the highest-value agent to build first.
- Revenue IntelligenceWe pressure-test how you find, win and keep customers and pinpoint the signal play worth building first.
AI Enablement & Training +
Hands-on training that makes your team genuinely capable with AI, not just dabbling with it, so the skill stays in-house.
- Operations StudioUpskill your people to build and run their own agents across reporting, analysis and knowledge work.
- Revenue IntelligenceTrain your revenue team to read the signals and run AI-assisted prospecting and outreach themselves.
Build-and-Hand-off +
We build the system on your own data and hand it over, documented and tested, so your team owns and runs it. No black box, no on-going dependence on us.
- Operations StudioA production agent across your reporting, analysis, finance or document work.
- Revenue IntelligenceThe signal engine that finds your next best customer from public institutional data.
Fractional AI Partner +
A single monthly retainer across both applications, scaling as far as fully bespoke engagements. Your team always owns and runs what we build.
- Operations StudioThe next agents, refreshes and team enablement as your needs grow.
- Revenue IntelligenceQuarterly playbooks, data refresh and advisory while your team runs the sends.
Common questions.
Who do you typically work with?+
Australian professional services firms that have their own way of working and a team lean enough that handing people back a few hours a week genuinely changes what gets done. We don’t service firms seeking generic AI consulting, or anyone after a black box that’s run off-site.
What does an engagement actually look like?+
It starts with a scoping conversation, usually a short Opportunity Audit to find where AI actually earns its keep in your firm. From there we build: agentic systems across your reporting, analysis and knowledge work, or the revenue intelligence behind how you find, win and keep customers. Each build is shaped around your team and your requirements, then handed off for your people to run.
Will this work with our existing tools?+
Yes. We build on top of what you already run, your CRM, data warehouse and Microsoft or Google stack, rather than bolting something on beside it. No rip-and-replace, no new platform to adopt; the build slots into your systems.
Who owns what you build?+
You do. The system, the data and the day-to-day running of it all stay in-house with your team once we hand off. Your workflow and your firm's data remain yours; the only thing we carry forward is the general method, never your edge.
Where does our data sit, and who has access?+
On your own infrastructure. Everything is deployed into your cloud and run by your team, so your data never leaves your environment. We only reach in when you explicitly invite us, and NDAs and DPAs are standard on every engagement.
Will LLMs train on our data?+
No. We work on enterprise and API tiers where your prompts and outputs are never fed into model training, not by the model provider and not by us. Your firm's data stays out of anyone's training corpus.
Experience you can trust.
15+ years inside enterprise teams, building the operations, data engineering, analytics and AI behind how they run: automated reporting and decision dashboards, ask-your-data and document agents in daily production use, and the revenue intelligence behind how teams find, win and keep customers.
10+ years as a legal professional across law firms, government and regulated environments, and the data inside them. Hands-on with data, analysis and AI. Monash JD candidate. The reason your data never leaves your environment isn't a marketing line: it's how we build.
Let's start the conversation.
Have an idea for a project? Or maybe you're just looking for some advice.
Reserve a spot for a free consultation. Bring one workflow that eats your team's week. We'll build a prototype and hand it over.