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AI SERVICES

Forward deployed AI engineering

Engineers who analyse, design and build inside your business.

Forward deployed AI engineering puts senior engineers inside your business to analyse the work, design the solution with your business and technology teams, and build AI agents into your real systems, data and processes. Transformativ's forward deployed engineers join from the first week of Catalyst+, so analysis, design and build move together, and they hand over a capability your people own and can extend.

THE PROBLEM

Why AI that works in a demo stalls in your environment

Most AI agents never leave the pilot, for four reasons.

  1. Integration gets deferred.

    The pilot ran beside your systems, and connecting it becomes a project of its own.

  2. The data was prepared for the demo.

    Production data has gaps, permissions and lineage requirements the pilot never met.

  3. Today's model choice becomes a lock-in.

    Agents built around one vendor are expensive to move when a better model arrives.

  4. The capability leaves with the builders.

    When the external team goes, nobody inside can extend what was built.

WHAT CHANGES

What changes

Forward deployed engineers build AI agents into your environment from the first week, and your people own the result.

  1. AI agents are built into your systems from week 1, so the design is tested against real work as it's drawn.

  2. Every agent action is logged, so what's built can be approved for live operation.

  3. The architecture lets you swap models as better ones arrive.

  4. Your engineers build alongside ours, and they own the result.

THE METHOD

The method behind it

One method shapes how we build.

Model-agnostic agent architecture

Built so a better model next year is a plug-in decision, and today's choice never becomes a three-year bet.

HOW IT RUNS

How it runs inside Catalyst+

Forward deployed AI engineering runs through every stage of Catalyst+, our AI transformation product.

See how Catalyst+ works →
  1. 01 · DEFINESIX WEEKS

    Define

    Our engineers secure access and data in the first weeks, and where the scope is focused, build the first AI agents on real work by week 6.

  2. 02 · ACTIVATETYPICALLY 8 TO 12 WEEKS

    Activate

    The agents go into live operation, integrated, monitored and governed.

  3. 03 · SCALE

    Scale

    Your team extends the capability across the business, and we step back.

What happens in the six weeks

WEEK 1WEEK 6: AI DELIVERING VALUE
  1. WEEKS 1 TO 2ALIGN

    WEEKS 1 TO 2 | ALIGN

    Our engineers join from the first week. Work with your business and technology teams to understand the process, systems and data, and agree access and controls with your security and risk teams.

    BY WEEK 2

    The process, systems and data understood, with access and controls agreed.

  2. WEEKS 3 TO 4DISCOVER

    WEEKS 3 TO 4 | DISCOVER

    Analyse the work with the people who do it, and design the solution with your architects, testing it against your systems and data as it's drawn.

    BY WEEK 4

    The design tested against your systems, data and controls.

  3. WEEKS 5 TO 6DESIGN

    WEEKS 5 TO 6 | DESIGN

    Design the agent architecture so you can change models as better ones arrive. Where the scope is focused, the first AI agents go live on real work.

    BY WEEK 6

    The build designed and, where focused, the first AI agents live on real work, built with your engineers.

QUESTIONS

Common questions about forward deployed AI engineering

A forward deployed engineer works inside your business, alongside your operations and technology teams, and takes a problem from analysis through to software running in production. They sit with the people who do the work to understand the process, the data and the exceptions, design the solution with your architects and risk teams, build it on your systems, and stay until it delivers the agreed outcome. The model started at Palantir, and AI companies including OpenAI and Anthropic now use forward deployed engineers to get their models working inside customers' operations.

A systems integrator usually builds to a specification someone else wrote. Our forward deployed engineers do the analysis and design themselves, working directly with your business and technology teams from week 1 of Define, so what they learn about your process, systems and data shapes the solution. They stay through Activate until the agents are running in production, and train your engineers to run and extend them.

Yes. The code, prompts, evaluation tests, agent configuration and documentation are yours, built in your repositories and cloud accounts. Your engineers work alongside ours throughout, so by the end of Activate they can maintain and extend the agents without us.

Whichever fit your environment and risk settings: Claude, OpenAI, Microsoft Copilot and Azure, Google Gemini or AWS Bedrock, and open-weight models where data has to stay on your own infrastructure. The model sits behind an interface you control, so you can switch when pricing or capability changes without rebuilding the agents. We're not tied to any one vendor.

From week 1. Before any agent touches live data, we agree with your security and risk teams which systems and data it can reach, how its own identity and permissions are managed, how it's tested for prompt injection and data leakage, and what it logs. These are the controls APRA expects for agentic workflows, including identity controls for non-human actors.