13:00 – 17:00
Every bank, insurer, and wealth platform on earth will run AI agents inside their core operations within the next three years. Not as experiments. Not as chatbots on a website. As workers. Making decisions. Touching customer data. Moving money. Filing regulatory reports.
Models from one vendor. Infrastructure from another. Copilots embedded in the productivity suite. Custom builds from consultancies who hand over a binder and leave.
None of those pieces talk to each other. None share a governance layer. None produce an audit trail a regulator would accept.
Governance built into the runtime. Compliance inherited by every initiative that follows. Integration native to the systems already in production.
A platform the institution owns, not a vendor stack the institution rents.
When something goes wrong, and it will, the institution owns the liability. Not the model vendor. Not the cloud provider. Not the integrator who left six months ago.
Imagine the institution that does not have to choose between speed and safety. Between innovation and compliance. Between the future and the regulator. This is what we built Chameleon to make real.
Governed. Auditable. Compliant. Connected to core banking, payments, KYC, and CRM without a single line of custom code.
Not because someone remembered to configure a rule. Because the architecture makes it impossible by design.
Every decision, every action, every data access already recorded, explained, and queryable the moment they need it.
The governance layer does not care which model you use. It governs what the model does. The platform absorbs the change.
Not a tool. Not a feature. The execution layer that makes AI safe to run at the centre of a regulated enterprise.
Long before AI agents became mainstream, regulated institutions faced the same problem on repeat. Every new initiative required new integrations, new compliance reviews, new governance controls, new security assessments, and a new delivery programme to wrap it all in.
Nothing compounded. Nothing was inherited. Everything was rebuilt. The result was complexity, cost, and technical debt accumulating across every department that tried to move.
We built Chameleon to solve that. A governed execution layer that made enterprise change faster, safer, and reusable from the first deployment forward.
We did not start with AI and add governance. We started with governance and became the platform AI needed.
The institutions that will define the next decade are not the ones that adopt AI fastest. They are the ones that make AI safe enough to trust with their most important operations. That is the race worth winning.
Ritesh did not study regulated finance from the outside. He spent twenty eight years inside it. Oracle. Temenos. Tata. Tier one banks across Australia, New Zealand, and global markets.
He has led full core banking migrations where the deadline was real and the regulator was watching. He has rescued programmes that were failing. He has sat in board rooms where the question was not whether to adopt AI, but how to stop it from becoming the next regulatory incident.
Chameleon is not his first company. It is the distillation of every migration, every production failure, and every regulatory conversation that came before it.
Chameleon is in production across Australia and New Zealand. Integrated with Temenos, Finacle, payment rails, open banking, KYC, and CRM platforms.
Trusted by institutions that do not have the luxury of getting governance wrong, in the markets where regulators have the sharpest eyes in the world.
Every bank, insurer, wealth platform, hospital network, and infrastructure operator will need the layer we have already built.
The governed execution layer between AI and the systems that run the world's money, health, and infrastructure.
Gen-AI for Lead Generation
Wed, Thu, Fri, Mon, Tue: 13:00 – 17:00