Adaptiv shows how agentic AI is rewriting the integration playbook

Adaptiv is moving beyond RAG pilots and into production-grade automation and reshaping how it delivers value.

Agentic AI is opening new ways to overhaul business processes. Specialist integrators like Adaptiv are eyeing the opportunities of multi-agent systems.

“With the advent of agentic AI, we’re now starting to unlock real business value — moving beyond expensive pilots to solutions that support teams in production,” said Nikolai Blackie, CTO and co-founder, Adaptiv.

Adaptiv started with RAG (retrieval-augmented generation) pilots, where a language model retrieves relevant data from an external knowledge source before generating an answer. But it quickly showed its limitations in terms of useful business applications.

“In many cases, it was data engineering exercises to come up with an advanced kind of search feature,” said Blackie, speaking at last week’s Boomi World event in Sydney.

Adaptiv’s almost 20-year partnership with Boomi has grown from a low code integration and API platform into an enterprise platform that now encompasses data management and AI.

Now agentic AI is enabling the business to scale services without growing its workforce. “It’s changing how we deliver value — and how fast we can do it,” he noted.

However, the speed and efficiency gains pose another challenge for partner businesses — shrinking billable hours that may see margins reduced. Partners will need to think strategically about how else to help customers.

Blackie said Adaptiv quickly realised they weren’t alone — across the industry, SIs large and small were converging on the same ideas at the same time, from code-analysis agents to migration accelerators.

“The argument is, we’ll be faster than the competitors, but if we do it faster, we can repurpose budget for our customers to add further value,” he said.

Blackie has found transitioning from pilots to production agentic AI is a big leap, especially building the governance frameworks and tools to reliably monitor and manage the agents. It’s the beginning of what promises to be an exciting transformation.

“With this agentic revolution, we’re starting at the building blocks: clean, well-governed data and frameworks for productionising agents,” he said.

Partners interested in these opportunities will need to embrace emerging skillsets in orchestration, governance and helping customers clean and structure data for multi-agent workflows.

“Mastering single-agent solutions is just the first stage; the real frontier is orchestrating multiple agents to tackle broader business challenges,” he told CRN Australia.

A recent implementation for a logistics provider involved parsing unstructured data with an AI agent that identifies the customer and calls the APIs to create the shipping information.

“The agent explains how it reached the conclusion and the level of confidence, and if it’s too low, we get a human in the loop to interact with it. But humans no longer have to process every single order,” he explained.

Blackie likens the shift to AI agents to the early days of API programs, where organisations built out their API catalogue and orchestrated more complex business processes.

“We're starting with the building blocks of the agent and operationalising and productionising these agents to move into the orchestration of these agents to add more value,” he explained.

Adaptiv’s focus for the coming year is AI enablement, data quality — to serve data up to AI and traditional processes in a clean and consistent manner — and governance,

“We’re focussed on helping organisations adopt AI in a secure, high-trust manner,” he said.