Achieve low latency, high throughput and better accuracy to improve user experience.
Use production-ready models. Lower risk, shorten dev time from months to days.
Reduce memory footprint and maximize hardware utilization. Easily deploy at the edge.
Object Detection
Semantic Segmentation
Pose Estimation
Image Classification
Access catalogue of ultra-performant models
Securely train or fine-tune on premise
Custom performance objectives
Deploy to any environment
Go from data to production ready model in days.
Enhance your product with faster, accurate inference.
Gain significant cost savings per model on average.
Decrease cloud instance time & better hardware utilization.
The world's most efficient and cost effective foundation models.
Gain a competitive edge through advanced model customizations.
Self-hosted inference. Ideal for enterprises and handling of sensitive data.
“Using Deci, we swiftly developed a model that enabled us to expand our offering and further scale our solution on existing CPU infrastructure with significant cost-efficiency.”
“Controlling our inference cloud spend without compromising on performance is key for our business success. Deci enabled us to scale our workloads while reducing costs and improving our users’ experience.”
“At Adobe, we deliver excellent AI-based solutions across a wide range of cloud and edge environments. By using Deci, we significantly shortened our time to market and transitioned inference workloads from cloud to edge devices. As a result we improved the user experience and dramatically reduced our spend on cloud inference cost.”
“Our advanced text to videos solution is powered by proprietary and complex generative AI algorithms. Deci allows us to reduce our cloud computing cost and improve our user experience with faster time to video by accelerating our models’ inference performance and maximizing GPU utilization on the cloud.”
“Applied Materials is at the forefront of materials engineering solutions and leverages AI to deliver best-in-class products. We have been working with Deci on optimizing the performance of our AI model, and managed to reduce its GPU inference time by 33%. This was done on an architecture that was already optimized. We will continue using the Deci platform to build more powerful AI models to increase our inspection and production capacity with better accuracy and higher throughput.”
“Deci delivers optimized deep learning inference on Intel processors as highlighted in MLPerf, allowing our customers to meet performance SLAs, reduce cost, decrease time to deployment, and gives them the ability to effectively scale.”
“At RingCentral, we strive to provide our customers with the best AI-based experiences. With Deci’s platform, we were able to exceed our deep learning performance goals while shortening our development cycles. Working with Deci allows us to launch superior products faster.”
“By collaborating with Deci, we aim to help our customers accelerate AI innovation and deploy AI solutions everywhere using our industry-leading platforms, from data centers to edge systems that accelerate high-throughput inference.”
from transformers import AutoFeatureExtractor, AutoModelForImageClassification
extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")
model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")