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Artrilogic
Proof

What we are shipping and what we have shipped.

We are deliberate about case studies. Customer permission first, then anonymised, then named. Below is what is currently in flight and what has recently been delivered.

Currently shipping

In flight today, described without naming the customer.

Phase 1 visibility per our case study release process: the shape of the work, no identifying detail until customer sign-off.

  • Currently shipping

    MCP server estate for an Australian SaaS platform

    Australian SaaS platform

    Surfacing core platform capabilities to agentic AI consumers through Model Context Protocol servers. Built on open foundations, governed end to end. Architecture, identity flow, audit story and agentic workflows. Customer name pending written sign-off for a joint announcement.

    Outcomes

    • Agentic AI consumers can use platform capabilities through governed MCP interfaces
    • Zero rewrite of the existing platform code
    • Auth, schema, rate limiting and audit handled at the integration layer
    MCP serversAgentic AIWSO2Open integration
  • Currently shipping

    CalibratedCV: an Artrilogic product, in active build

    In-house product · CV intelligence

    Our own product. CV intelligence for engineering hiring, built on the same Next.js, Docker and Caddy stack we recommend to customers. We are deliberately writing about this lightly while the product takes shape.

    Outcomes

    • Multi-model Agentic AI service in practical use
    • Live engineering surface that informs how we advise customers
    • Demonstrable product with high-volume user load, built on the same stack we recommend to customers
    Next.jsDockerCaddyVPS
    Visit CalibratedCV.com
  • Currently shipping

    Microsoft Dynamics 365 Customer Insights for a Queensland customer

    Queensland-based enterprise

    Standing up Dynamics 365 Customer Insights for a Queensland-based customer. Data unification across the existing Dynamics estate, segment and journey design, and the integration plumbing into the broader Microsoft stack. Customer name held while the work is in flight.

    Outcomes

    • Unified customer view across previously siloed Dynamics data
    • Phase 1 segments and journeys live, scoped to the smallest useful uplift
    • Integration patterns extend cleanly into the customer's existing Azure estate
    Microsoft Dynamics 365Customer InsightsAzureMicrosoft Fabric
Recently delivered

Engagements that have shipped to production.

Anonymised summaries. We can broker a referee call where the customer has agreed.

  • Delivered

    Health app delivered for a Sydney startup, scaled into a California Series A

    Health technology startup

    Co-developed a consumer-facing health app on Google Cloud infrastructure for an Australian startup. The architecture was designed from day one for a high-volume user base, so the platform did not need to be rebuilt as growth arrived. Shortly after delivery the company relocated its HQ to California and closed a Series A funding round.

    Outcomes

    • Production-ready platform engineered for scale on day one
    • Survived the user-load curve that came with Series A traction
    • Architecture supported the company's relocation and capital-raise narrative
    Google CloudHigh-volume architectureMobile + web frontendsScalable backend
  • Delivered

    AWS environment optimisation and Java upgrade for a marketing gamification platform

    Marketing technology

    A platform originally built in the early 2010s to deliver gamification for marketing campaigns and user engagement had grown beyond its original AWS footprint. We delivered a combined AWS environment optimisation and a Java platform upgrade, lifting throughput substantially and bringing operating cost back into a defensible range. No big-bang cutover.

    Outcomes

    • Higher platform throughput sustained under campaign-driven load spikes
    • AWS spend brought back inside the original commercial envelope
    • Codebase modernised in slices, original platform stayed live throughout
    AWSJava platform upgradeThroughput optimisationCost remediation
  • Delivered

    .NET Framework to .NET Core microservices on Azure for a high-data-volume platform

    Enterprise data platform

    A .NET Framework solution originally built in 2011 to handle high data volumes was modernised to .NET Core with a controlled microservices architecture on Microsoft Azure. The work was phased so the original platform stayed in service throughout, and the customer's feedback on the engagement is reflected publicly in our Google reviews.

    Outcomes

    • Modernised codebase on a current, supported runtime
    • Microservices architecture sized for the workload, not for vanity
    • Customer engagement reflected publicly in Google reviews
    .NET Framework to .NET CoreAzureControlled microservicesPhased migration
    See it in our Google reviews
Why we work this way

Customer trust precedes marketing copy.

We do not write case studies before customers are ready for them. The work is real. The decision about when (or whether) to publish a customer's name is theirs, not ours.

If you want context on how we engage before signing, our views page is the long version. The AI readiness assessment is the short one.

Want to talk to a referenceable customer?

Some of the engagements above have referees willing to take a call. We can broker the conversation when the fit is real.

Request a reference callGeneral contact