Coforge announced that all regulatory approvals and statutory clearances in multiple jurisdictions for the acquisition of Encora have been secured without conditions, clearing the path for the transaction to close. The combined entity is expected to operate at US$2.5 billion (US$2.5 bn) on a run-rate basis, with a US$2 billion (US$2 bn) core focused on data, AI-led engineering and cloud services. The company indicated that these approvals align with the strategic rationale for the acquisition and underpin its AI-native engineering ambitions. Integration planning and execution are progressing in line with the established schedule, with the integration management office tracking workstreams across all functional areas. The company said it is on course to meet stated integration milestones and that leadership continuity remains a critical priority. All the senior leaders who were asked to stay have accepted the offer. The cost optimisation programme targeting General and Administrative (G&A) functions is advancing with detailed workplans and governance structures in place, and the company remains confident of achieving its margin guidance. The programme is expected to deliver a 20 per cent to 25 per cent reduction in G&A costs for the combined business within the projected timelines. Front-end commercial and sales teams of both organisations are ready to commence collaborative operations immediately after closing, which the company regards as an early realisation of commercial synergies. Executives indicated the transaction has proceeded as planned and that anticipated synergies are on course to be realised, with the firms expected to merge by the end of April 2026 and subsequently operate as a US$2.5 bn firm on a run-rate basis. The company framed the deal as a step to accelerate its scale in AI-led engineering, data and cloud services and to set a benchmark for deploying applied AI at enterprise scale. The release included a standard caution that forward-looking statements involve risks and uncertainties and that actual results could differ materially from expectations.