Smart, efficient, anonymous People Counters & Analytics to the real world.
Our solution allows for easy deployment, capture, analysis, and reporting of the number people who enter a physical place. Optionally, we can also capture and report occupancy in real time.
We assist Retailers, Universities, Casinos, Places of Worship, Office Buildings, and other industries in analyzing and taking action on their people traffic trends.
We offer a special package for retailers to measure performance on traffic, including conversion rate and service levels. Our direct integrations make it easy to combine POS data with staff data. The Retail Equation simulator lets users run simulations to improve sales. It can also be used as a learning tool to understand how traffic, staffing, conversion rates, and quality service relate.
Learn more
Most AI video tools hand you a black box: closed weights, a subscription, and no way to see what is happening under the hood. LTX takes the opposite approach. Built by Lightricks, LTX is an open foundation model that generates and simulates across video, audio, and the physical world, and it puts the weights, the code, and the control in your hands.
At the center of the model is LTX-2.5, a 22B-parameter dual-stream diffusion transformer that produces native 4K video at up to 50 frames per second, with audio and video generated together in a single pass rather than stitched together afterward. Artificial Analysis, an independent benchmarking group, currently ranks LTX among the top three AI video models in the world.
You choose how you want to use it. Download the open weights and run LTX-2.5 on your own hardware. License the model for on-premise deployment backed by enterprise support. Or build directly on LTX Studio, the production suite that turns the model into a full creative workflow. Companies like ElevenLabs, Asteria Film Co., Magnopus, and NVIDIA already rely on LTX for their own work.
LTX is not built for one-off social clips. It is infrastructure for teams that generate motion, audio, and physical environments as part of their own products and pipelines.
Learn more
GWM-1
GWM-1 is Runway’s first family of General World Models created to interact dynamically with simulated reality. Built on Gen-4.5, the model produces real-time, action-conditioned video rather than static imagery alone. GWM-1 allows users to control environments through camera motion, robotics commands, events, and speech inputs. It generates coherent visual scenes that persist across movement and time. The model supports synchronized video, image, and audio generation for immersive simulation. GWM-1 is designed to learn from interaction and trial-and-error rather than passive data consumption. It enables realistic exploration of both physical and imagined worlds. Runway positions GWM-1 as foundational technology for robotics, training, and creative systems. The model scales across multiple domains without manual environment design. GWM-1 marks a shift toward experiential AI systems.
Learn more
Inkling
Inkling is Thinking Machines’ open-weights foundation model built for customization, multimodal reasoning, and agentic AI workflows. The model uses a Mixture-of-Experts architecture with 975 billion total parameters and 41 billion active parameters, making it large in capacity while activating only a subset of experts per token. Inkling supports up to a 1 million token context window and was pretrained on 45 trillion tokens spanning text, images, audio, and video. It is designed as a broad generalist model with strengths across coding, reasoning, instruction following, factuality, tool use, vision, audio understanding, forecasting, and safety. Developers can tune its thinking effort to trade off latency, cost, and performance, which is useful for production systems that need efficient reasoning at scale. Inkling can be fine-tuned on Tinker, tested in the Inkling Playground, and deployed through partners such as TogetherAI, Fireworks, Modal, Databricks, Baseten, vLLM, SGLang, llama.cpp, and Hugging Face transformers. The model can generate applications, operate tools, create styled artifacts, reason over visual and audio inputs, and support long refinement loops for collaborative work. Thinking Machines also previewed Inkling-Small, a lighter Mixture-of-Experts model with 276 billion total parameters and 12 billion active parameters for lower-cost and lower-latency workloads. By combining open weights, multimodal training, agentic capabilities, efficient reasoning, and fine-tuning support, Inkling gives builders a flexible AI foundation for specialized products and workflows.
Learn more
