{"company":{"slug":"cresta","name":"Cresta","legal_name":null,"aliases":[],"primary_layer":"L8","primary_topic_id":"customer-service-agents","secondary_topics":null,"hq_country":null,"hq_city":null,"founded_year":null,"is_public":false,"ticker":null,"description":"Generative AI for contact centers — real-time agent assist + automation."},"profile":null,"recent_business_signals":[{"signal_type":"product_launch","signal_date":"2026-05-28","signal_data":{"query":"Cresta","title":"Cresta launched Cresta Synthetic Customers on May 28, 2026, providing realistic AI customer personas based on real conversations.","source":"funding-research"},"source":"funding-research"},{"signal_type":"partnership","signal_date":"2026-05-07","signal_data":{"query":"Cresta","title":"Cresta announced a strategic partnership with Atento on May 7, 2026 to deliver hybrid human-AI customer experience solutions.","source":"funding-research"},"source":"funding-research"},{"signal_type":"funding","signal_date":"2024-11-19","signal_data":{"query":"Cresta","title":"Cresta closed a $125 million Series D on November 19, 2024 at a post-money valuation of approximately $747 million, co-led by World Innovation Lab and Qatar Investment Authority with participation from Accenture, EnvisionX Capital, LG Technology Ventures, Qualcomm Ventures, Workday Ventures, Andreessen Horowitz, Greylock Partners, J.P. Morgan, Sequoia Capital, and Tiger Global, bringing total funding to over $270 million.","source":"funding-research"},"source":"funding-research"},{"signal_type":"funding","signal_date":"2024-11-19","signal_data":{"query":"Cresta","title":"Cresta closed a $125 million Series D round co-led by World Innovation Lab and Qatar Investment Authority at a post-money valuation of $746.97 million, bringing total funding to over $270 million.","source":"funding-research"},"source":"funding-research"}],"recent_talent_signals":[],"citation_url":"/companies/cresta","last_updated":"2026-06-25T02:40:16.467+00:00","generated_at":"2026-06-25T06:28:49.722Z","avg_fit_score":null,"fit_scores":[]}