Mergers and acquisitions (M&A) have always been complex. While large enterprises can rely on bankers and networks to find the right targets, small and mid-sized companies are often left out. They lack access to the right data, face steep advisory fees, and struggle with a process that is slow, opaque, and relationship-driven. Deals can take months, sometimes years, to materialize.
However, there’s an Indian startup named GrowthPal trying to solve this issue. The company has built an AI-powered matchmaking platform where algorithms optimize matches by assessing compatibility & synergies across multiple variables like team composition, product fit, market overlap, and customer base. Along with executing on buyer mandates, the AI also monitors a company’s sector and competitors, surfacing off-market opportunities and even suggesting new growth ideas. This allows businesses to move faster, uncover hidden targets, and approach M&A not as a manual, relationship-driven process, but as an intelligent, scalable, and near real-time growth strategy.
The Problem With Traditional M&A
Traditionally, M&A deals have depended on investment bankers, consultants, and personal networks, which is an expensive and slow process, especially for smaller companies that can’t afford high advisory fees. Even when they can, traditional sourcing methods typically surface only a handful of in-market companies, many of which are already being courted by multiple buyers. For mid-market companies, this often means missed opportunities.
Deals can take months, sometimes even years, to come together. However, GrowthPal believes that its technology can remove much of this friction by making the process more data-driven. Its model identifies off-market opportunities that remain invisible to conventional channels, expanding the pool of viable targets multifold while improving speed, fit, and conversion rates for buyers.
Traditional M&A has long been a reactive and relationship-driven process, often limited by human networks and outdated databases,” “Buyers typically see only what is already on the market, missing out on high-quality off-market opportunities that could be a better strategic fit and faster to close. We saw several inefficiencies in this process, limited visibility into the SMB landscape, reliance on static data, and manual research that slows down decisions. Our aim with GrowthPal is to make deal origination proactive, data-driven, and scalable, so that M&A becomes an intelligent growth lever.
Maneesh Bhandari, co-founder and CEO of GrowthPal
What Does it Offer?
GrowthPal’s platform works a lot like a matchmaking service, but for businesses. It uses AI to scan, analyse, and connect companies with the right counterparties.
- For buyers: The platform identifies precision-fit targets, often off-market, before they appear in banker pipelines.
- For investors: It surfaces companies aligned with their portfolio strategy and growth thesis.
- For corporates: It finds acquisition candidates based on sector, geography, capability, and growth potential.
- For sellers: It allows potential sellers to understand where they stand in the market, get insights on their readiness, explore discreetly, and also get buyer, investor, or partner suggestions when they are ready.
The company’s biggest impact has been in the mid-market, where most opportunities go unseen. Its platform caters to a wide range of buyers, from corporates scouting bolt-on acquisitions, to corporate development teams pursuing tuck-ins, to founders exploring acqui-hires to accelerate talent-led growth.
Clients today include mid-market enterprises, fast-growing startups, PE-backed companies, and corporate development teams across India and the US. Demand has been rising, particularly among IT services firms with $30–$100 million in revenue, which are increasingly looking to acquire capabilities, clients, or expand into new markets. Roughly half of GrowthPal’s clients are US-based, with the rest primarily in India. There is also growing inbound interest from Europe and Southeast Asia.
How It Works: Agentic AI for Deal Discovery
The main component of GrowthPal’s model is an AI stack built for intelligent deal sourcing. It includes proprietary models, sector intelligence, and agentic AI, autonomous systems that can take a strategic input (such as entering a new market or acquiring a new capability) and translate it into a structured acquisition thesis. After that, it scans databases of millions of companies, pulling from public filings, web traffic, job boards, funding history, and other signals. This level of contextual matching would be nearly impossible to do manually at scale.
Instead of relying on static snapshots, the AI looks at live signals, including hiring trends, fundraising activity, or executive moves, to identify companies that might be preparing for a transaction. One of the major game changers, GrowthPal’s Agentic-AI has introduced various deep analysis like business synergies, cultural fit, leadership team analysis, instant similar matches, deep insights on any M&A announcements by potential competitors, etc.
The Bigger Shift in M&A
When it comes to the M&A lifecycle, deal sourcing consumes the majority of time and resources, especially for mid-sized transactions, where lean CorpDev teams must balance multiple mandates. Traditionally, identifying and evaluating targets takes weeks to months. However, the AI agents work alongside their (optional) human analyst team, taking this timeline to just weeks. It allows buyers to evaluate multiple scenarios that would previously have been impractical.
AI-driven platforms like GrowthPal represent a broader shift in M&A. Instead of relying only on networks or static databases, limited pipelines, deal origination is becoming data-driven, intelligent, and global, driven by deep integration of AI.
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