Fastino, a startup from Palo Alto, has introduced a novel AI model architecture that is smaller and task-specific, requiring far less investment in resources compared to traditional trillion-parameter models. The company has attracted $17.5 million in seed funding, bringing its total to nearly $25 million. Fastino targets enterprise customers with its suite of small models designed for specific tasks, promising faster responses, enhanced accuracy, and lower training costs. While competition in the enterprise AI space is intense, Fastino's innovative approach is gaining traction among early adopters, with positive feedback on performance so far.
Fastino's models are faster, more accurate, and cost a fraction to train while outperforming flagship models on specific tasks.
It has built a suite of small models that it sells to enterprise customers, each focusing on a specific task a company might need.
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