Value-added services best way to boost margins in data-obsessed era, says Confluent’s APAC SVP

“The ability to get a margin off of the vendor’s product has changed dramatically — that margin has gone to a consulting margin.”

As enterprises navigate data problems — fragmented systems or weak data infrastructure — to maximize the value of AI, channel partners have the opportunity to create repeatable margins by delivering on a clear solutions framework.

“Resellers or channel partners need to stop thinking about how do I get a margin off of this solution — the unit economics are not strong enough because it’s consumption based,” Greg Taylor, Confluent’s senior vice president and general manager, APAC, told CRN Asia.

“What they need to be thinking about is how do I provide a solutions framework? And that framework is repeatable, customer after customer.”

Taylor shared that he has seen a ‘mindset shift’ across partners, be it GSIs or local RSIs, in the region and particularly in Singapore, figuring out the best way to offer value-added services to customers in the age of AI.

“What we’ve seen is the actual resale market or the ability to get a margin off of the vendor's product has changed dramatically — that margin has gone to a consulting margin,” said Taylor. “What that means is resellers need to have a services component for their portfolio.”

This can include having ‘deep skills’ in Confluent’s solutions, as well as how to deal with applications like Kafka and Flink. Also, partners need to understand data streaming pipelines and the interoperability of systems with other players in the market.

“The folks who are doing really well in this space have someone at the solution architecture level that’s building the solution for the customer,” he said. “Then they have an ability to either do it themselves or have a network of partners where they’re actually providing [the service].

“They’re extracting most of the economic value from the customer because they’re providing an end-to-end solution, which doesn’t always just have Confluent in the architecture. It might have Databricks, Snowflake [or] AWS, because customers are asking for choice.”

Increasing investments in data streaming tech

Besides choice, enterprises also typically have multiple solutions run by multiple providers, and they just want everything ‘working in harmony’, added Taylor, so that they can access the right data to operationalize AI.

Enterprises are increasingly recognizing that access to trusted, real-time data is the best way to properly push AI pilots into production instead of having them stall due to ‘dirty data’. Some found that data streaming platforms may be the answer to their problems.

“The companies that we see successful are the ones that started sort of attacking this problem even before AI became a thing,” Sean Falconer, vice president, Product Management - AI Strategy, Global at Confluent told CRN Asia.

“They invested in data streaming technology and they shifted a lot, essentially the notion of defining data earlier in the lifecycle — so shifting it left, cleaning it earlier.”

The team found that as AI investments increase, investments in data streaming has also increased. About 86% of Singapore leaders rank data streaming as an investment priority, alongside AI and machine learning solutions (85%), according to a recent Confluent report.

Additionally, Taylor has found that enterprises are inquiring more about Confluent’s application of model context protocol (MCP) to manage the streaming infrastructure.

“We're definitely seeing MCP being an incredibly important thing, which is basically giving context to every model, because the challenge is you have these really powerful models, but they're only as good as the data that they’re trained on,” said Taylor.