EyePop.ai makes it easy for any team to add computer vision—no machine learning background required. With a simple call, our SDKs let you analyze images, video, or livestreams. Choose from a library of ready-to-use models for people, text, devices, and more—or train and deploy your own in just a few clicks. Whether you’re running in the cloud, on-premise, or directly on a phone, EyePop.ai brings powerful computer vision to your product in hours, not months.

EyePop.ai is built for startups, SMBs, and product teams that want to add visual automation and image analysis to their workflows without hiring a machine learning team.

The platform is designed for users without machine learning experience, with an intuitive interface for uploading, labeling images and training a model. For developers and engineers, APIs and SDKs are available to integrate models into apps or products. Explore developer docs or sign up free to test without writing a line of code.

Our Visual Intelligence Reports tool is designed to generate insights from a batch of images with no code necessary.

Yes, we offer a library of pre‑built models for common use cases like object counting, product detection, and measurement tasks. These can be used as‑is or fine‑tuned with your own data. Browse available models here.

These include advanced capabilities such as dense image captioning, zero-shot detection, and visual language models (VLMs).

Yes, at EyePop.ai your data is your own. We do not use it for any purpose beyond what you explicitly authorize. We never repurpose, share, or analyze your data outside your specified use case.

EyePop.ai is also HIPAA certified, ensuring the highest standards of data privacy and security for sensitive information.

EyePop.ai’s Self‑Service Training lets you train a custom AI vision model in a few hours. No ML expertise needed.

Most users can end-to-end train a custom AI-powered vision model in just a few hours. The platform automates model optimization, training, and deployment so you can move quickly from testing to production.

Our Self-Service Training platform includes auto-labeling, which uses AI to automatically generate high-confidence annotations on your dataset, accelerating the labeling process and reducing manual effort.

To train a custom AI‑powered vision model on EyePop.ai, you’ll need a set of images or video frames that represent the objects or scenarios you want the model to detect. These images should be clear, high‑quality, and relevant to your use case.

Many users successfully train a model with as few as 200 labeled images. More images generally lead to higher accuracy, but you can always start small and add more data later to improve performance.

You can upload JPEG, PNG, or MP4 video files. For video, the platform will extract frames automatically for labeling and training.

No. EyePop.ai provides a built‑in labeling interface so you can tag objects after upload. You can also upload pre‑labeled datasets through our SDK if you already have annotations.

Initial accuracy depends on the quality and quantity of your dataset. Many users achieve strong results with as few as 200 images, but you can always add more data and retrain to improve performance over time.

Yes. Models can be retrained or fine‑tuned at any time. As you collect more data, simply upload new images, label them, and start a new training run.

Our Self-Service Training platform supports an iterative approach—train, deploy, test—powered by a continuous learning system that helps you identify edge cases and retrain to make your model smarter with every cycle.

You retain full ownership and control of your models, datasets, and outputs as long as your account is active. Unlike some platforms, we don’t claim rights to your trained models.

Our API is REST‑based, meaning it works with virtually any language or framework, including Python, Node.js, Java, C#, and more.

We offer dedicated SDKs for Python, Node, and React, along with code examples to accelerate your development. Explore developer resources.

Yes. Trained models can be deployed locally with our On-Premise AI Application Runtime. This eliminates the need to run your data through a cloud service ensuring more privacy, lower latency, and near zero bandwidth.

Yes. Once trained, your models can be accessed via API or SDKs, or integrated into your app, dashboard, or workflow with our easy to use JSON response. See developer documentation.

No. EyePop.ai handles all compute, scaling, and infrastructure for you. The Production Plan offers faster inference, dedicated compute resources, and team support for production deployments.

Visual Intelligence Reports transform raw images or video footage into structured data and actionable insights. They allow startups and SMBs to automate inspections, assessments, and inventory tracking without manually reviewing visual data. Generate your first report here.

Reports convert any raw imagery you may have into a detailed report CSV or PDF based on your unique output needs. Detects defects, categorizes, tags assets and more to generate a summary of insights in minutes. No coding necessary.

Once your model is trained, Visual Intelligence Reports are generated in about 30 minutes for up to 500 images.

Yes. Reports can be scheduled or generated automatically through EyePop.ai’s API, making it easy to integrate into recurring workflows such as inspections, assessments, or inventory checks.

Yes. Visual Intelligence Reports can be exported as CSV, PDF, or accessed through API to integrate directly into your existing software or workflow. You can also use reports for compliance documentation, audits, or dashboard visualizations.

Yes. EyePop.ai hosts hands‑on workshops where you can build, train, and deploy your first AI‑powered vision model with guidance from our team. See upcoming workshops.

All plans include access to documentation, guides, and community resources. Production & Enterprise Plan users receive priority support and live training sessions.

Yes. We work with partners and clients to build custom features or integrations for specific workflows.