Automate multi modal tasks using GenAI, reliably, at scale
V7 Go uses generative AI to automate tasks and document processing reliably and at scale, allowing companies to reduce the strain of back-office work and focus on what really matters. V7 Go turns images and documents into structured data.
Hey Product Hunt 👋
We built V7 Go because multimodal foundation models are good enough to solve most of the tasks we complete at work today, but aren’t easy to run at scale and with reliable results. We believe AI should free us from back-office and administrative tasks to give us time to focus on creative and interpersonal work.
About 40% of the work we’re doing on our laptops can be done just as well by frontier models if configured correctly and with the right context, so we built a product that lets you intuitively configure AI models and run them at scale on any task involving documents, video, or text.
Here’s a few things it can do out of the box:
✅ Extract information from large, complex documents
✅ Qualify and categorize inbound messages, such as contact forms, and perform actions via Zapier.
✅ Classify text, emails, or images in the order of millions.
✅ Compare the performance of different LLMs across the same task.
As an AI-powered database, V7 Go can be used to solve almost anything, and upon launch we’ve focused a lot of its optimizations on document processing, form understanding, and data extraction, as tasks that nobody really likes doing, but are still done in massive quantities worldwide.
💡 The idea came to us when working with a client that analyzes 300,000 scanned pages of paper per day (!) occupying thousands of human hours. We not only needed a way to use LLMs like GPT-4 reliably enough to outperform expert human analysts, but also in a way that scaled past the 1:1 chat UI, so we developed V7 Go to resemble a smart spreadsheet where every cell hosts an LLM.
There is a massive workflow challenge in generative AI, where its ability to succeed relies on being able to source similar examples of a task, and understand a company’s context, so it can be more accurate well-tuned than baseline GPT-4, Claude 3, or Gemini. V7 Go abstracts away a lot of configuration burdens on the user, but has a lot going on under the hood and is built to integrate with your (internal or external) product via the API.
Here’s what makes it special:
🔬 Files are turned into mini repositories where an agent can analyze text, images, tables, and reflect on how to find the right info. We call this Index Knowledge
🔬 You can control the options a model spits out using Select Properties, so it won’t just ramble on with text. This is great for integrations.
🔬 Select Properties allow you to subdivide projects into Workflows, where each stage has an AI perform a unique set of operations.
🔬 Visual grounding (this one is in limited release) lets you see where each piece of info the LLM came up with is found in the source data, even if it’s an image.
🔬 Scales up to 10 million cells per project, that’s a lot of tokens!
There’s more to come, and we’d love to hear your first impressions.
➡️ Special for PH: ScoutHunt10 for 20% off V7 Go Pro.
You can try it for free now, we’d love your feedback and welcome any questions!
