Generative AI Applications
We design and develop full-stack, user-facing applications with generative AI at their core. Whether you are launching an AI-first SaaS startup, an internal content generation platform, or a multi-modal creation tool, we handle the product strategy, UX design, LLM integration, and scalable deployment.
Core Features
Streaming & Low-Latency UI
Implementation of token-streaming (SSE) and optimistic UI updates for real-time, ChatGPT-like conversational experiences.
Multi-Modal Interfaces
Seamlessly combining text, image generation (Midjourney/DALL-E), and audio (Whisper/ElevenLabs) within a single unified interface.
Enterprise Authentication
Secure, role-based access control (RBAC) and SSO integration to ensure AI features are only accessible to authorized users.
Conversation Memory Management
Scalable session management architectures using Redis or Postgres to maintain long-term context in user interactions.
Our Process
Product Strategy & UX Prototyping
Week 1-2Defining the core AI value loop and wireframing the user experience to mask latency and guide user inputs.
Frontend Engineering & Streaming
Week 3-5Building the React/Next.js frontend with robust state management to handle complex, asynchronous AI streams.
Backend & AI Middleware
Week 5-7Developing the secure backend APIs that connect to LLM providers, manage rate limits, and enforce prompt injection defenses.
QA & User Acceptance Testing
Week 8Testing the application across edge cases, ensuring the AI degrades gracefully when confused.
Launch & Analytics
Week 9Deploying the scalable application and implementing analytics to track how users are utilizing the AI features.
Technologies We Use
FAQ
How do you handle the high costs of LLM API calls in a SaaS application?
Can you build an app that looks and feels like ChatGPT or Claude?
Who owns the IP of the application you build?
Join The Inner Circle
Get exclusive insights on AI automation, software systems, and digital growth strategies from NeoGen Technologies.