If your product needs to understand images, video or documents alongside text, or if your team already runs on Google Workspace and Google Cloud, Gemini is usually the more practical fit. We, Seven Web Tech, integrate Google's Gemini API into existing products so businesses can add multimodal AI features without switching their whole stack.
Gemini, built by Google, can process text, images, video and documents together in a single request, which makes it useful for tasks a text-only model simply can't handle, reading a photo of a damaged product for a claims workflow, understanding a scanned form, or summarising a video. We integrate the Gemini API into existing products for exactly these kinds of multimodal features.
A good number of the businesses we work with are already on Google Workspace or Google Cloud, and Gemini tends to fit into that setup more naturally than switching to an entirely different provider's tools. We have built image and document understanding features for Indian businesses on that stack, and we're upfront when Gemini isn't the better choice for a purely text-based task. Talk to us about your use case on a free call and we'll tell you honestly what fits.
As your product's use of images, video or documents grows, the same integration can be extended to cover more features without rearchitecting your stack, since it's already built on infrastructure you're likely using. We keep the integration structured so Google's model updates don't mean rebuilding your feature.
We build features that let Gemini read and interpret images, product photos, damage claims, scanned documents, as part of your workflow.
We integrate Gemini to process and summarise video content, useful for training material, reviews or content moderation.
For teams already on Google Workspace or Cloud, we integrate Gemini in a way that fits naturally into that existing infrastructure.
We use Gemini's multimodal ability to read scanned forms, receipts or handwritten notes and extract the information your system needs.
We build search features that combine text and image input, letting users search using a photo alongside a text query.
We connect the Gemini API into your existing product or internal tool, matching your current Google-based or general stack.
We have integrated Gemini for image and document-heavy workflows for Indian businesses, so we know where its multimodal strengths actually add value.
We design each integration around the specific multimodal task at hand, instead of treating Gemini as a plain text chatbot.
Automated image or document understanding keeps saving manual review time daily, so we build integrations to hold up as your usage grows.
We help smaller teams integrate one well-defined multimodal feature first, instead of an expensive, broad AI rollout.
We keep refining prompts and output handling as we see how the integration performs on your real images, documents or video.
Our team members follow a step-by-step process to integrate Gemini AI. Here's the process
We start by understanding what your product needs to understand, images, video, documents, and whether you're already on Google Cloud or Workspace.
We map out the API calls, media handling and output structure needed, and share the plan with you before development starts.
We connect the Gemini API into your product or internal tool and build the media-handling workflow around it.
We test the integration against real images, documents or video samples to check accuracy and output structure hold up.
Once testing is done, we deploy the integration into your live product and monitor it closely for the first few days.
We refine prompts and media-handling logic based on real usage, keeping an eye on accuracy, cost and response time.
We stay available to update the integration as your media types change or as Google updates the Gemini models.
Learn about all the reasons why you should choose Seven Web Tech as your Gemini AI integration company in India
We use Gemini where image, video or document understanding is actually needed, not just for plain text chat.
For teams already on Google Workspace or Cloud, we integrate Gemini in a way that works naturally alongside your existing tools.
We build features that combine text with images, documents or video in a single request instead of separate disconnected steps.
We test integrations against real images, scanned documents and video samples before launch, not just clean sample data.
Images, documents and data sent to the Gemini API are handled carefully, and we explain exactly what leaves your system.
We remain available after launch to refine the integration, add new media types or handle updates on Google's side.
If you have an issue or question that requires immediate assistance, you can click the button below to chat live with a Customer Service representative.
We usually respond to new enquiries within a few business hours.
Gemini can process images, video and documents alongside text in the same request, so it's useful for tasks a text-only model can't do at all, reading a photo, understanding a scanned form, or summarising video content.
Yes, generally. If your business already runs on Google Cloud or Workspace, integrating Gemini tends to fit more naturally into that existing infrastructure than bringing in a completely separate provider.
Yes, this is one of the more common use cases we build, extracting information from scanned forms, receipts or handwritten notes so it flows into your existing system automatically.
Both. We've built features that summarise or extract information from video content, alongside image-understanding features, depending on what the product needs.
We explain exactly what data is sent to the API for each feature and design integrations to avoid sending anything unnecessary. This is discussed clearly with you before development starts.
Not necessarily. We hand over documentation for the integration and stay available for updates, so your existing team doesn't need dedicated AI expertise.
It depends on the media types involved and how deeply it needs to connect into your existing product. A focused feature usually takes two to three weeks. Share your use case with us on WhatsApp and we'll quote from there.
