Centific Brings Last-Mile Physical AI to Production with NVIDIA Cosmos 3

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Press release

Centific Brings Last-Mile Physical AI to Production with NVIDIA Cosmos 3

Centific integrates NVIDIA Cosmos 3 in its Physical AI portfolio to deliver richer pre-annotation, higher-fidelity synthetic data, and faster training cycles for robotics, AV, and vision-agent customers.

Published on Jun 1, 2026

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4 min read time

Table of contents

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NVIDIA Cosmos 3

Vision AI

VerityAI 2.0

Agentic AI

NVIDIA Cosmos 3

Vision AI

VerityAI 2.0

Agentic AI

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Centific

Redmond, Washington — June 1, 2026 — Centific today announced that it is integrating NVIDIA Cosmos 3, the new open world foundation model, across its Physical AI portfolio. By building on Cosmos 3 Super and Cosmos 3 Nano inside Centific's Verity AI platform, as well as data collection, annotation, and simulation pipelines, the company will accelerate how cities and enterprises move from limited real-world data to production-ready Physical AI systems.

Cosmos 3 is a fully open omnimodel that unifies what have historically been three fragmented capabilities, physical reasoning, action transfer, and world transformation, into a single Mixture-of-Transformers architecture. For Centific's customers in public spaces, robotics, and industrial vision, this convergence collapses the prototype-to-production gap that has slowed Physical AI deployment for years.

Why One Omnimodel Beats Three Fragmented Pipelines

The traditional Physical AI development stack forces developers to stitch together separate systems: vision language models for understanding, world generation models for simulating new states, and policy models for predicting agent actions. Every handoff introduces loss - in fidelity, in temporal coherence, in physics accuracy, and in iteration speed.

Cosmos 3 replaces those handoffs with a single open foundation model that natively handles all three:

Reason: understanding what an agent, robot or drone, is physically doing, resolving spatial, temporal, and object-interaction relationships in context.
Simulate: Predicts plausible futures, converges on optimal behaviors, and continuously improves through reinforcement learning in simulation, reducing real-world risk.
Generate: Leading open-world generation, creating large-scale out-of-distribution scenarios that are difficult or costly to capture.

For Centific, this unification matters because its customers operate in the messy real-world tail of Physical AI, egocentric capture, dexterous manipulation, dark-scene observation, city-wide vision, and industrial inspection; where every fragmented pipeline handoff has historically been a place where projects stall.

The Cosmos 3 Nano is particularly well suited to the high-volume, real-time reasoning workloads that Centific runs across its annotation, pre-labeling and inference pipelines. Three capabilities stand out:

Embodied reasoning leadership. Cosmos 3 Nano is the strongest of the three Cosmos models at understanding what an agent, drone or robot is physically doing: 72.7% on Pai-Bench Embodied Reasoning (best in class) and 95.5% on a custom 465-video action set, with category wins on Hand & Manipulation, Service, Driving, Nature Dynamics, HoloAssist, Agibot, and RoboFail. For Centific's customers working with dexterous manipulation and egocentric datasets, this translates directly into faster pre-annotation cycles with higher first-pass accuracy. For cities, reasoning helps accelerate comprehension of behaviors and attributes to elevate public safety.
Broad multimodal reasoning gains. Cosmos 3 Nano is the new generalist for image and academic multimodal reasoning, taking the top score on MM-Vet (63.18%) and MMMU (50.26% strict, 52.78% multiple-choice, 23.76% Groq-lenient). The biggest jumps over predecessors are in recognition, knowledge reasoning, and open-ended generation; the exact qualities Centific's customers need for vision-agent applications spanning industrial AI and smart-space deployments.
Captioning and narrative coherence. On scene captioning judged by GPT-4o, Nano averages 5.83/10 versus 4.83 for Reason 2 and 4.00 for Reason 1, with clear gains on temporal accuracy, completeness, and role identification. Richer, better-ordered video descriptions accelerate the downstream work Centific automates, from training-data curation to model evaluation.

How Centific Is Putting Cosmos 3 to Work

Centific is integrating Cosmos 3 Super and Cosmos 3 Nano across its Physical AI portfolio:

Synthetic data generation and video editing pipelines. Cosmos 3 super powers synthetic video generation and video editing workflows where physics accuracy and temporal consistency are non-negotiable.
Dark-scene and low-light event detection. For city observation and industrial vision customers, Centific is using Cosmos 3's reasoning capability to strengthen detection of events in low-light, dark-scene, and visually degraded conditions.
Physical AI annotation for egocentric and dexterous manipulation. Cosmos 3 Nano Reasoner accelerates annotation for the datasets where action understanding, hand-object interaction, and fine-grained state-change reasoning are critical. This improves the confidence across inferencing pipelines.

With Cosmos 3 Super's Mixture-of-Transformers architecture and its leading physics accuracy, combined with Cosmos 3 Nano Reasoner for real-time reasoning, Centific can deliver richer pre-annotation, higher-fidelity synthetic data, and faster training-and-evaluation cycles for its robotics, city, and vision-agent customers.

Centific is also working with the NVIDIA Physical AI Factory Blueprint to scale these pipelines end-to-end. By pairing Centific's Verity AI platform, along with their data-collection and annotation expertise, including its OneForma 2M+ global expert network, with the open Cosmos foundation, Centific is helping customers compress the path from limited real-world data to production-ready Physical AI from months to weeks.

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