Automate multi-modal tasks at scale using Gen AI, with V7 Go.
We label terabytes of data and from the operations perspective, the scale of the projects requires a reliable training data platform like V7 to succeed.Read case study ->
After conducting an extensive research of annotation tools, we chose V7 as it fits our needs best due to its customizable workflows and automated QA.Read case study ->
We use V7 to make our annotation and model training workflows more efficient. It's much easier to use than other software thanks to its intuitive UI.Read case study ->
How switching to a dedicated platform can double your ML team's output.
The Pro plan is limited on fields (what you would call ‘cells’ in a spreadsheet) and Go tokens, which are consumed when you use AI models. The field limit does not refresh, while your token allowance resets on the same cadence as your billing cycle, either monthly of yearly. While both fields and tokens are a hard limit, they can be increased by expanding your plan.
V7 Darwin is a data labeling platform for annotating videos and medical imaging to train your own model, while V7 Go specializes in applying foundation models to multimodal data, starting with intelligent document processing. In time they will be natively connected.
Go is more accurate and robust than calling a model provider directly. By breaking down complex tasks into reasoning steps with Index Knowledge, Go enables LLMs to query your data more accurately than an out of the box API call. Combining this with conditional logic, which can route high sensitivity data to a human review, Go builds robustness into your AI powered workflows.
V7 Go will support external models via API, allowing for a flexible approach to document processing by incorporating both in-house and third-party AI models.
Go tokens are standardized units obtained by converting tokens from various model providers into a single measure. More expensive models consume Go tokens at a faster rate than cheaper models. While Go tokens are metered and limited as part of a billing plan, the primary limit is on fields.
V7 Go is capable of recognizing both printed and handwritten text, leveraging advanced optical character recognition (OCR) technologies, as well as charts, diagrams and logos.
V7 can process various types of data, including images, medical imaging files, videos, volumetric series, and documents. The exact types of data that can be processed may depend on the specific use case and requirements. However, V7 supports the majority of visual data formats.
Yes, V7 provides a complimentary free tier that lets you explore some of its basic features and capabilities. However, to access the full suite of advanced functionalities and harness the platform’s complete potential, it is worth considering one of the paid plans. You can see the full feature breakdown and pricing of V7 here.
V7 is a subscription-based service. The pricing of our paid plans depends on your organizations use case, data requirements, and any add-on options, such as our managed labeling services. Please contact our sales team for more information.
Yes your data is secure with V7. We take data security very seriously. Go to V7 Data Processing & Security to learn more about how we keep your data safe.
The Pro plan is limited on fields (what you would call ‘cells’ in a spreadsheet) and Go tokens, which are consumed when you use AI models. The field limit does not refresh, while your token allowance resets on the same cadence as your billing cycle, either monthly of yearly. While both fields and tokens are a hard limit, they can be increased by expanding your plan.
V7 Darwin is a data labeling platform for annotating videos and medical imaging to train your own model, while V7 Go specializes in applying foundation models to multimodal data, starting with intelligent document processing. In time they will be natively connected.
Go is more accurate and robust than calling a model provider directly. By breaking down complex tasks into reasoning steps with Index Knowledge, Go enables LLMs to query your data more accurately than an out of the box API call. Combining this with conditional logic, which can route high sensitivity data to a human review, Go builds robustness into your AI powered workflows.
V7 Go will support external models via API, allowing for a flexible approach to document processing by incorporating both in-house and third-party AI models.
Go tokens are standardized units obtained by converting tokens from various model providers into a single measure. More expensive models consume Go tokens at a faster rate than cheaper models. While Go tokens are metered and limited as part of a billing plan, the primary limit is on fields.
V7 Go is capable of recognizing both printed and handwritten text, leveraging advanced optical character recognition (OCR) technologies, as well as charts, diagrams and logos.