According to McKinsey, a recent study of corporate and investment banks shows that productivity growth at many pure-play investment banking franchises has been stalling, and they conclude that artificial intelligence-enabled, end-to-end operating models will be crucial to regaining momentum.

Navatar CEO Alok Misra said, “As deal markets reset, advisors no longer win mandates just by showing up in the data room – they win by consistently being first with the right idea, backed by credible insight.”

“Leading banks are already using AI to enhance prospecting, lead prioritisation, and frontline effectiveness, and the next step is to let AI agents run end-to-end workflows. Our AI Deal Engine is built to sit at the centre of the M&A franchise, so bankers spend less time updating systems and more time in front of clients.”

Navatar’s operating model introduces a single AI Deal Engine that spans deal origination, client and sponsor coverage, opportunity screening, marketing, execution, and post-close relationship management. The AI runs continuously, capturing intelligence as it is created, preserving institutional context, and moving work forward automatically across the mandate lifecycle.

Navatar’s AI is intended to be a firm-wide intelligence and execution layer for sector teams, sponsor coverage, and senior rainmakers. The artificial intelligence constantly collects signals from emails, meetings, call notes, pitch materials, and market activity, tying them to sectors, themes, buyers, sellers, and capital providers. It spots whitespace and under-covered relationships within each banker’s universe, surfaces next-best actions, and flags where follow-through is at risk.

This firmwide mapping of relationships provides senior bankers with a real-time, dynamic view of coverage health, replacing static lists with a clear view of client coverage, idea flow, and mandate pipeline across regions and sectors.

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