AI solutions firm Tredence plans 1,700 new hires in 2025, 30% dedicated for Gen AI, Agentic AI

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Data science and artificial intelligence (AI) service provider Tredence plans to hire 1,700 employees in 2025, with 30 percent of the new hires focused on Generative AI and Agentic AI. This is significant because 2025 is when companies are expected to make big bets on Agentic AI to drive the next growth phase in this evolving technology.

Meanwhile, the company is also set to train over 1,000 of its 3,500 employees on Agentic AI in 2025, with an aim to achieve $500 million in revenue by 2027.

“Our ability to not just grow incrementally but growing exponentially in building Agentic AI solutions for our clients, at the end of the day, will be enabled by the quality talent that we'll bring to the table,” Shub Bhowmick, CEO and co-founder, Tredence, told Moneycontrol.

Last year, the company aimed to onboard approximately 1,500 employees and came very close to meeting that target.

Bhowmick added that Gen AI revenue has surged for the San Jose-headquartered firm, now making up about 20-25 percent of its earnings driven by such deals.

Tredence is backed by two institutional investors, Advent International and Chicago Pacific Founders. Founded by Sumit Mehra and Shashank Dubey, along with Bhowmick in 2013, it has so far raised $30 million in 2020 and a Series B funding of $175 million in 2022.

Modus Operandi

Although there’s a lot of hype, the IIT graduate and Kellogg School of Management alumnus says Agentic AI is still in the early stages.

The company has already deployed Agentic AI into production for a client. And at least five are in the proof-of-concept (PoC) stage for various clients.

The one implementation already in production is for a consumer packaged goods (CPG) company, utilizing a cloud-based Reporting-as-a-Service (RaaS) solution where a multi-agent framework enables seamless communication between agents.

Bhowmick explained that in this setup, a human supervisor analyst communicates with a supervisor agent, where the two coordinate as the analyst agent retrieves various results.

“So we're starting to see a very significant innovation in the way these agents are now starting to get used by large corporations,” said Bhowmick, who has worked in various roles at Infosys, American Express, and Mu Sigma.

Nonetheless, he believes that most companies in the enterprise AI space are still in the early testing phase, with limited mainstream adoption. However, growing pressure from boards and investors will lead companies to implement Agentic AI.

What goes behind Agentic AI

Building an Agentic AI system involves two key components: the brain (the model) and the body (the application), he added.

Developing these systems requires advanced data scientists to configure frameworks and engineers to handle orchestration, agent operations, and governance, with the company's growth relying heavily on investing in talent across both areas.

Moreover, the lifecycle of building Agentic AI systems involves three key categories of talent.

First, senior-level consultants with domain expertise create blueprints by designing the agentic architecture and estimating feasibility, timelines, and costs. Second, build consultants, including LLM scientists and engineers, execute these blueprints by developing the system’s brain and body.

And finally, Agent Ops professionals handle ongoing monitoring, ensuring cost efficiency, responsible AI practices, and system performance, as these digital agents.

“But over time, this will keep progressing and these smart agents will get faster and better. And then they will be they will start solving higher order problems,” Bhowmick added.

Future Outlook

Tredence is investing a portion of its revenue in developing advanced capabilities, including small language models (SLM) and reasoning models tailored for specific client contexts.

It is also building its own versions of "smart interns" to serve as copilots for data engineers, business analysts, and insight generation teams, he further said.

Additionally, the company is developing platform capabilities in collaboration with its hyperscalers to co-create solutions.

“The company has allocated 10% of its revenue and workforce to R&D, focusing on Gen AI and developing next-gen AI agents for coding, decision-making, and operations,” he said further.

Tredence has invested $1 million in establishing an AI Innovation Center to drive these advancements.