GrowthPal raises USD $2.6m for AI M&A deal sourcing

GrowthPal has raised USD $2.6 million in funding for its software product that uses artificial intelligence for M&A deal sourcing and early-stage execution work.

The company said Ideaspring Capital led the round, with participation from angel investors. GrowthPal said it will use the funding for product development and to expand its presence in the US and other international markets.

GrowthPal operates from Singapore and targets corporate development teams, private equity-backed firms and other buyers that pursue small to mid-market acquisitions. It positions its product as a way to identify off-market acquisition targets and to narrow down long lists into a smaller set of companies that match a defined acquisition thesis.

Deal sourcing

M&A sourcing often relies on investment banking networks and established databases, with buyers competing for deals already in market. GrowthPal said it focuses on earlier identification of companies that may fit a buyer's strategy, including targets that are not actively running a sale process.

It said its product works from a buyer's growth objective, such as acquiring a specific capability or entering a new geography. GrowthPal said the system translates that objective into a structured acquisition thesis. The company said its AI agents then scan an enriched database of more than four million technology companies.

GrowthPal said it draws on signals including public filings, web activity, hiring trends and funding history. It then produces a shortlist of targets that match the buyer's mandate.

"M&A sourcing is where most time and effort is wasted, especially for smaller and mid-market deals," said Maneesh Bhandari, Co-Founder and CEO, GrowthPal. "Teams spend weeks researching, filtering, and chasing opportunities that never go anywhere. We built GrowthPal to help buyers focus only on high-intent, high-fit targets and move from mandate to meaningful conversations far faster."

Smaller transactions

GrowthPal said it focuses on transactions under USD $70 million. It framed that segment as one where buyers often operate with limited internal resources and where traditional advisory coverage can be uneven.

The company also placed its pitch in the context of corporate development teams facing tighter timelines and a need to prioritise work. It pointed to the growth of data products used in dealmaking, including company information platforms and deal workflow tools. GrowthPal said those tools tend to focus on data aggregation rather than decision-making on target fit.

"GrowthPal is solving one of the most under-optimised parts of the M&A lifecycle," said Naganand Doraswamy, Managing Partner, Ideaspring Capital. "By focusing on qualified deal discovery and using AI to compress timelines, the team is enabling a more systematic approach to inorganic growth that traditional tools cannot offer."

Traction claims

GrowthPal said it has supported more than 42 completed M&A transactions. It also said it has facilitated over 210 LOI-stage conversations across North America, Europe, Asia and Latin America.

The company said its clients include large and mid-market enterprises, fast-growing startups, private equity-backed firms and corporate development teams. It said those clients operate across sectors including IT services, SaaS, fintech and vertical software. GrowthPal also cited one client that it said closed seven acquisitions within 18 months using the platform.

The founders are Maneesh Bhandari, Shalu Mitruka and Amaresh Shirsat. GrowthPal described its approach as a mix of software and internal support. It said its team facilitates introductions after outreach to potential sellers and initial interest checks.

Product roadmap

GrowthPal said it plans to expand product coverage beyond sourcing. It said it intends to add work on valuation reasoning, deal structuring and preparation for negotiations.

The company said it wants its product to sit earlier in the decision process for M&A teams, starting with discovery and then continuing into later stages of transaction execution.