Generative AI Development

We build production-grade generative AI applications — custom GPT-powered tools, AI copilots, content generation systems, and multimodal solutions. Every application includes guardrails, output validation, and monitoring to ensure reliable, accurate, and safe AI generations at enterprise scale.

Generative AI Development

Generative AI That Works in Production

The gap between a ChatGPT demo and a production generative AI system is enormous. Demos hallucinate, lack guardrails, and can't handle edge cases. Production systems need output validation, citation tracking, confidence scoring, rate limiting, cost management, and monitoring — all while maintaining the natural, helpful user experience that makes generative AI valuable.

We've shipped generative AI applications across healthcare, finance, legal, and SaaS — industries where accuracy isn't optional. Our systems use RAG to ground outputs in verified data, implement layered guardrails to prevent harmful or off-topic responses, and include human-in-the-loop review paths for high-stakes outputs.

What We Build

Custom GPT Applications

Domain-specific AI applications powered by GPT-4, Claude, or open-source models. Tailored prompting, function calling, and tool use for your specific workflows.

AI Copilots

Intelligent assistants embedded in your existing tools — coding copilots, writing assistants, research aids, and decision-support systems that understand your domain.

Content Generation

Automated report generation, email drafting, documentation creation, and marketing content systems with brand voice consistency and factual grounding.

Multimodal AI

Applications combining text, image, and audio — visual document understanding, image generation with brand guidelines, audio transcription and summarization.

Conversational AI

Intelligent chatbots and virtual assistants with context awareness, multi-turn conversation, tool calling, and seamless handoff to human agents when needed.

AI Safety & Guardrails

Output filtering, content classification, prompt injection defense, PII detection, topic boundaries, and compliance-enforced generation for regulated industries.

GenAI Stack

ModelsGPT-4oClaude 3.5Llama 3MistralGeminiStable DiffusionWhisper
FrameworksLangChainLlamaIndexSemantic KernelHaystackvLLMTensorRT-LLM
InfrastructureAWS BedrockAzure OpenAIGCP Vertex AINVIDIA GPUsModalReplicate
SafetyGuardrails AINeMo GuardrailsLLM GuardCustom classifiersRed-teaming

Generative AI Questions

What types of generative AI applications can you build?

We build custom GPT-powered applications, AI copilots for domain-specific tasks, content generation systems, conversational AI assistants, multimodal applications, and RAG-enhanced systems that ground outputs in your proprietary data.

How do you ensure outputs are accurate?

We use RAG to ground outputs in verified data, output validation pipelines, confidence scoring, citation tracking, automated fact-checking, and human-in-the-loop review for high-stakes outputs. We also implement guardrails to prevent harmful or off-topic generations.

Which model should we use?

It depends on your requirements — accuracy, latency, cost, privacy, and customization needs. Often the best solution combines models: a fine-tuned smaller model for high-volume tasks and a frontier model for complex reasoning. We'll evaluate options with your actual data.

What does a GenAI project timeline look like?

A focused application takes 6-10 weeks: discovery (1-2 weeks), MVP (3-4 weeks), guardrails and refinement (2-3 weeks), deployment (1 week). Complex multi-modal or multi-agent systems take 12-16 weeks.

Ready to Build with Generative AI?

Tell us about your use case. We'll design a generative AI solution with the right model stack, guardrails, and architecture.

Start Your GenAI Project