Platform Unifies AI Model Responses

CollectivIQ was developed internally at Buyers Edge Platform, a digital procurement company, to address the challenges its 1,250 employees faced with generative AI, including inaccurate answers and data security risks. The project was initiated by CEO John Davie, who was dissatisfied with the prospect of vendor lock-in and the "per-head" licensing costs of mandating a single AI provider for the enterprise. The platform's core technology is a form of "ensembling," a machine learning technique where multiple models are used to produce a more robust outcome. By simultaneously querying up to 10+ large language models, including ChatGPT, Claude, Gemini, and Grok, CollectivIQ cross-validates the outputs to reduce hallucinations and expose biases. The system presents a single, annotated response that highlights areas of agreement and disagreement among the various AI models. This approach provides a "defensible source of truth" for enterprise users, moving beyond the unverified, probabilistic answers of a single model. For enterprise clients, a key feature is data privacy and security. CollectivIQ operates through stateless enterprise APIs, meaning it does not retain any of the data processed. All requests are handled ephemerally and wiped after the answer is generated, which prevents proprietary information from being used to train third-party models. CollectivIQ is launching with a usage-based, pay-per-query pricing model after an initial 30-day free trial, a strategy aimed at eliminating expensive per-seat subscription costs. This model is intended to cut costs for businesses by over 50% compared to licensing multiple AI platforms individually.