New project enables enterprises to build, deploy, and manage vision AI pipelines with modular, reusable components
Plainsight, the leader in automated infrastructure for data-centric AI pipelines, announced the launch of OpenFilter, an open source project that simplifies and accelerates the development, deployment, and scaling of production-grade computer vision applications. Available now under the Apache 2.0 license, OpenFilter introduces an innovative “filter” abstraction that combines code and AI models into modular components that allow developers to assemble vision pipelines.
Plainsight will demonstrate OpenFilter at the Embedded Vision Summit, where it will be showcased at booth #518. CEO Kit Merker will present on Thursday, May 22, with a talk titled “Beyond the Demo: Turning Computer Vision Prototypes into Scalable, Cost-Effective Solutions.”
“OpenFilter has revolutionized how we deploy vision AI for our manufacturing and logistics clients,” said Priyanshu Sharma, Senior Data Engineer at BrickRed Systems. “With its modular filter architecture, we can quickly build and customize pipelines for tasks like automated quality inspection and real-time inventory tracking, without having to rewrite core infrastructure. This flexibility has enabled us to deliver robust, scalable solutions that meet our clients’ evolving needs, while dramatically reducing development time and operational complexity.”
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OpenFilter directly addresses the challenges enterprises face when working to deploy AI computer vision in production. Its frame deduplication and priority scheduling reduce GPU inference costs and its advanced abstractions reduce deployment timelines from weeks to days. Its extensible architecture future-proofs investments, making it easy to adapt it to audio, text, and multimodal AI, and positioning OpenFilter as a foundational platform for scalable, agentic computer vision systems.
Bridging the Prototype-to-Production Gap
Traditional computer vision projects often stall due to fragmented tooling and scalability challenges. OpenFilter addresses this with:
- Open Source Core: Apache 2.0-licensed runtime with pre-built filters for common tasks (tracking, cropping, segmentation).
- Filter Runtime: Manage video inputs (RTSP, webcams, image files), processing, and output routing to databases, MQTT, or APIs.
- Modular Pipelines: Assemble filters for tasks like object detection, deduplication, or alerts into reusable workflows.
- Flexible Deployment: Deploy filters across CPUs, GPUs, or edge devices, optimizing resource costs.
- Broad Model Support: Integrate PyTorch, OpenCV, or custom models (e.g., YOLO) while avoiding vendor lock-in.
OpenFilter Use Cases:
- Manufacturing: Automated quality inspection, defect and foreign object detection, and fill level monitoring on production lines.
- Retailers and Food Service: Drive-through analytics, cup and condiment counting, and real-time inventory tracking.
- Logistics and Supply Chain: Vehicle tracking, automated inventory management, and workflow automation.
- Agriculture: Precision farming and livestock monitoring through drone and camera footage analysis.
- Security: People counting, surveillance automation, and safety protocol enforcement
- IoT and Edge: Event detection and alerting.
“Filters are the building blocks for operationalizing vision AI,” said Andrew Smith, CTO of Plainsight. “Instead of wrestling with brittle pipelines and bespoke infrastructure, developers can snap together reusable components that scale from prototypes to production. It’s how we make computer vision feel more like software engineering – and less like science experiments.”
“OpenFilter is a leap forward for open source, giving developers and data scientists a powerful, collaborative platform to build and scale computer vision AI,” said Chris Aniszczyk, CTO, CNCF. “Its modular design and permissive Apache 2.0 license make it easy to adapt solutions for everything from agriculture and manufacturing to retail and logistics, helping organizations of all types and sizes unlock the value of vision-based AI.”
“OpenFilter is the abstraction the AI industry has been waiting for. We’re making it possible for anyone – not just experts – to turn camera data into real business value, faster and at lower cost,” said Plainsight CEO Kit Merker. “By treating vision workloads as modular filters, we give developers the power to build, scale, and update applications with the same ease and flexibility as modern cloud software. This isn’t just about productivity, it’s about democratizing computer vision, unlocking new use cases, and making AI accessible and sustainable for every organization. We believe this is the foundation for the next wave of AI-powered transformation.”
Source: Businesswire