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Introducing Apollo
Apollo is a family of Foundation Agent Models: Goal-pretrained agents that can be fine-tuned to work on behalf of any company. Our first model, Apollo-Commerce, enables every consumer company to deploy its own conversational commerce agent that outperforms both human and LLM Agents.
About Apollo
Apollo is a family of Foundation Agent Models: Goal-pretrained agents that can be fine-tuned to work on behalf of any company. Developed over the past six years in collaboration with 60,000 human agents, Apollo outclasses traditional LLMs in agentic use-cases. Apollo is trained on a neuro-symbolic language that constitutes both descriptive and procedural ("agentic") data, replacing autoregressive inference with agentic reasoning producing both language and instructions for actions. This method relies on obtaining a structured interaction state, achieved through sensory data collected to produce a symbolic, parameterized representation of each interaction.

Apollo enables companies of any kind to deploy Controllable Agents, versions of Apollo that are fine-tuned on a specific task. Controllable Agents offer fine-grained control, adhere to the deploying company’s policies and provide a white-box view of their decision-making and reasoning. They enjoy superior tool use, steerability and overall performance over GPT Agents.
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