Multimodal AI, Built Into Real Products
We build AI features on Google's Gemini API, using its multimodal reach to handle text, images, documents, and video inside one pipeline. From AI assistants to document processing, we treat every integration as production software, not a demo.
Where Gemini Fits
Gemini's multimodal capability makes it useful anywhere a product needs to understand more than plain text.
Multimodal Workflows
Pipelines that process text, images, documents, and video in a single request.
Document Understanding
Extracting, summarizing, and classifying content from PDFs, contracts, and reports.
Video Analysis
Using Gemini's video understanding to extract insights or summaries from video content.
Workflow Automation
Using Gemini as the intelligence layer to route, classify, and act on data across a system.
AI Assistants
Assistants for internal teams or customer-facing products, built with guardrails and structured output.
Image Understanding
Analyzing and classifying images at scale — useful for cataloging, moderation, or visual data workflows.
What We Build With It
We use Gemini's full API surface, not just text-in text-out prompting.
AI Assistant Development
Multimodal assistants for support, internal knowledge access, or product workflows with structured output.
Document Processing
Pipelines using Gemini's native PDF and image understanding to extract and classify content.
Chatbot Development
Conversational systems with multimodal input handling and sensible fallback logic.
Workflow Automation
Using Gemini's function calling and structured outputs to trigger real actions across systems.
How We Build It Right
A production Gemini system needs more than an API key — it needs structure around the model.
Prompt & Input Design
Structured, versioned prompt workflows with routing for text, image, and document inputs.
- Versioned prompts
- Multimodal input routing
- Structured outputs enforced
API Security
Key management, rate limiting, and usage monitoring across every integration point.
- Key management
- Rate limiting
- Usage monitoring
Monitoring & Guardrails
Quality, latency, and cost tracked in production, with review workflows for low-confidence outputs.
- Quality and latency tracking
- Guardrails enforced
- Human review where needed
What Sits Around Gemini
Gemini handles the intelligence layer — the surrounding stack is picked to fit the product.
AI Layer
Backend
Frontend
Database
What We Pay Attention To
AI features are only as good as the engineering discipline around them.
Cost & Reliability Controls
Token usage monitoring, model tier choice, and caching to keep performance and cost predictable.
Data Handling Care
Sensible PII handling and structured output controls, especially for anything touching real user data.
Maintainable Architecture
Modular prompt design and versioned configs so the system can be updated without a full rewrite.
Where we've used Gemini
Live projects built with Gemini. Each case study covers what we built and why.
Frequently Asked Questions
Common questions about integrating Gemini into a product.
It means connecting Gemini into your app, building the security layer, and handling multimodal inputs and business logic so it works reliably inside a real product.
It's built to process text, images, documents, and video natively in a single request, which makes it well-suited to document intelligence and mixed-format workflows.
Yes — we connect the API to your existing backend and database, adding features like document processing, search, or assistants as native product functionality.
Function calling lets Gemini interact with external APIs and systems in a controlled way. We use it to build workflows that trigger real actions and pull live data.
Key management, rate limiting, access control, and usage monitoring on every integration, with added output validation for sensitive use cases.
A focused chatbot or document processing feature can be built in a few weeks. Multi-step pipelines with multiple integrations take longer.
Technologies we pair with Gemini
Want AI Built Into Your Product Properly?
If you have a use case for multimodal AI, we can help you scope it and build it well.