Generative AI App Development

Custom applications powered by generative AI models.

Build powerful tools that generate content, extract structured data, or create media using the latest LLMs from OpenAI, Anthropic, and Google.

Intelligent Infrastructure

Monitor and optimize generation

Generative AI requires robust observability. Our solutions come with comprehensive dashboards to monitor generation quality, latency, cost, and safety filter performance.

Generative AI Product Console
Generations Today42.1k
Avg Latency850ms
User Satisfaction4.8/5
Moderation Flags0.1%
Prompt Templates & Output Quality
Marketing Copy v2High Retention
Summary Extractor98% Success
Code Assistant94% Success
Safety Review & Analytics

Real-time content moderation scans inputs and outputs for PII, toxicity, and brand safety policy violations.

Filter StrictnessHigh (Enterprise)

Generative AI app capabilities

Text & Content Generation

Dynamic generation of articles, marketing copy, emails, or reports based on user inputs.

Structured Data Extraction

Using LLMs to parse unstructured text (like PDFs or emails) and return clean, structured JSON.

Image & Media Generation

Integrating DALL-E, Midjourney, or Stable Diffusion for custom image generation workflows.

Prompt Management UI

Admin tools to easily tweak, test, and version-control system prompts without deploying code.

Cost & Token Tracking

Granular monitoring of API usage, token limits, and cost per user or feature.

Content Moderation

Automated filters to ensure generated content is safe, unbiased, and brand-aligned.

GenAI feature integration

Invoice Extraction

Automatically parse incoming invoices and map data directly into ERP systems.

Support Automation

Draft responses and categorize tickets using historical support data.

Internal Knowledge

Chat interfaces connected to company wikis, HR policies, and technical docs.

Lead Qualification

Score incoming leads based on natural language inputs and behavior.

Our GenAI development process

01

Feature Scoping

Identify exactly what the AI will generate and the user inputs required to trigger it.

02

Prompt Engineering

Iteratively design and test the system prompts to ensure high-quality, consistent outputs.

03

Backend Architecture

Build robust API routes that handle LLM requests, streaming, and error fallbacks.

04

Frontend Integration

Develop intuitive UI components (like magic wands or generation loaders) for the AI features.

05

Rate Limiting & Costs

Implement strict token counting and rate limits to prevent API abuse and control costs.

06

Deployment

Go live with comprehensive logging to monitor generation quality and latency.

AI Governance Built-in

Deploying AI in an enterprise setting requires strict guardrails. We do not build black-box systems. Our architectures are designed with explicit boundaries to prevent hallucination damage, secure private data, and maintain operational control.

PII Masking

Personally Identifiable Information is stripped before data is sent to external APIs.

Human Review Queues

Any automated decision below a strict confidence threshold is routed to human operators.

Prompt Versioning

Prompts are treated as code, version-controlled, and tested against regression datasets.

Audit Logging

Every LLM interaction is logged for compliance, debugging, and quality assurance.

Generative AI technology stack

LLM
OpenAI GPT-4oAnthropic Claude
Image Model
Stable Diffusion
Full Stack
Next.js
Framework
Vercel AI SDK
Database
PostgreSQL

Generative AI app development — frequently asked questions

Generative AI App Development

Ready to build a generative product?

From internal text extraction tools to full-fledged AI SaaS products, we have the expertise to execute.