Services
AI Consulting & Development
We build software products with AI embedded — not bolted on.
We embed production-grade AI into your product — fast — because we use the same GenAI tools in our own engineering process.
What We Deliver
LLM-powered product features
From AI-drafted content to intelligent search and document processing, we integrate large language models as first-class product capabilities — not demos.
Amazon Bedrock & OpenAI integration
We work across the major model providers. We have production experience with Amazon Bedrock (Claude, Titan, Llama) and OpenAI APIs, and we choose the right model for each use case.
AI-accelerated development
Our engineers use GenAI throughout the build process — not just as a novelty. This means faster iteration, higher code quality, and more time spent on problems that actually matter.
RAG and knowledge systems
We build retrieval-augmented generation pipelines that give LLMs accurate, up-to-date context from your own data — reducing hallucinations and making AI outputs actionable.
Use Cases
- Auto-drafting alerts, reports, or summaries from structured data
- AI-powered search and semantic document retrieval
- LLM-assisted triage, classification, or routing
- Generative UI and dynamic content personalization
- Agent workflows and multi-step AI task automation
Technologies
nextjspythonfastapiamazonBedrockawsnodejspostgresreact
Related Work
Frequently Asked Questions
Do you work with teams that have no existing AI infrastructure?↓
Yes — most of our clients start with zero AI infrastructure. We assess your stack, identify the highest-leverage integration points, and build from there. You don't need to have an ML team in-house.
Which AI providers do you work with?↓
We have production experience with Amazon Bedrock, OpenAI, Anthropic's Claude API, and open-source models via Ollama and Hugging Face. We recommend based on your specific needs — cost, latency, data privacy, and output quality all factor in.
How do you handle AI hallucinations and output quality?↓
We build guardrails into the product — human-in-the-loop review flows, structured output validation, and RAG pipelines that ground LLM responses in your actual data. AI output is treated as a draft, not a final answer, unless the use case warrants otherwise.
Can you integrate AI into our existing product, or only greenfield builds?↓
Both. We regularly add AI features to existing products — taking over or extending an existing codebase and embedding AI capabilities where they add the most value.
Connect with Guy Shahine (CEO) and book your free strategy session now.