According to reports from Moneycontrol, Prabhudas Lilladher has issued a 'BUY' rating on Latent View Analytics with a target price of ₹490. The broker's research report dated March 04, 2026, recommends the stock following interactions with the company's management. The recommendation comes after a recent market correction that has made valuations more attractive from a target perspective.
As reported by Moneycontrol, the stock is currently trading at 26x/21x of FY27E/FY28E earnings after the recent correction. The broker has reduced USD revenue estimates by 60bps/90bps for FY27E/FY28E respectively due to continued weakness in Hi-Tech and higher concentration mix of Diagnostics. However, margin estimates remain unchanged. The company maintains a cash-rich balance sheet with approximately 9% market cap.
According to the broker's analysis reported by Moneycontrol, the FS, Retail and Industrial verticals should continue their growth momentum in FY27E with 25–30% YoY growth. This growth is supported by underlying demand and scaling efforts to graduate the first potential FS accounts into the USD 10mn+ band. The company is focused on driving revenue through advanced AI horizontal capabilities, which currently represent approximately 20% of revenue.
As reported by Moneycontrol, the changing AI landscape is likely to put pressure on the Diagnostics segment (60% of revenue), especially in technical areas, while the Domain and Consulting segments should maintain steady state. Margins are likely to remain within the guided band of 23–25%, supported by improved utilization, selective hiring, and a higher fixed-price mix of 80–85%. The company is exploring opportunities in the Healthcare & Life Sciences segment and Databricks capabilities.
According to the broker's report, the revised target price of ₹490 is based on a PE multiple of 32x (reduced from 40x earlier) to FY28E earnings. The previous target price of ₹630 has been revised downward. The company's traction in Data Engineering remains strong, aided by the Databricks partnership and expanding avenues around Snowflake and GCP, which are expected to accelerate further as enterprises receive boardroom mandates to make their data AI-ready.
