This is the full picture. Throttle Neural develops across language, vision, audio, reasoning, and autonomy. Each line of work feeds a single destination: general intelligence that can learn and do what humans can.
Our flagship. A general intelligence architecture built to learn new tasks, carry knowledge forward, plan over long horizons, and adapt when conditions change — memory, reasoning, and environment interaction as first-class concerns, not bolt-ons on a chatbot.
Foundation models for analysis, reasoning, retrieval, multi-step problem solving, and tool use — built to work inside real systems with constraints and oversight, not just generate convincing text.
Specialized text systems beyond general chat: summarization, classification, extraction, translation, document understanding, and structured output for workflows that need precision over personality.
Developer tools that understand project context, navigate unfamiliar codebases, debug edge cases, and help engineers ship — a daily proving ground for reasoning, tool use, and long-context memory.
Scene understanding, depth estimation, tracking, and spatial reasoning — the perceptual layer that connects cameras and sensors to decisions in driving, robotics, and agent systems.
Controllable image synthesis for creative tools, synthetic training data, and simulation environments. Generation and perception developed together — one produces worlds, the other navigates them.
Temporal media models for editing, generation, and scene consistency across frames — extending visual intelligence from still images into motion, narrative, and time.
Detection, classification, and instance recognition across images and video streams — locating and labeling what matters in a scene, from road users to inventory to security feeds.
Speech-to-text, speaker identification, audio classification, and sound understanding — giving agents and interfaces a hearing layer, and opening another modality general intelligence must master.
Forecasting, pattern detection, anomaly identification, and decision support over structured and unstructured data — systems that don't just describe the past but help reason about what comes next.
Sentiment analysis, tone detection, empathy modeling, and affect-aware responses — because intelligence that interacts with humans needs to read context beyond literal words, in text, speech, and face.
Systems that turn goals into monitored execution — planning steps, using tools, recovering from errors, and operating with human oversight. The bridge between "can answer" and "can follow through."
Perception fusion, behavior prediction, motion planning, and closed-loop simulation for autonomous mobility. Our hardest real-time test of machine judgment. Try the simulator →
