Book a free 30-minute discovery call. No commitment, no sales pitch — just an honest conversation about your goals and where AI can make a real difference.
Tell us a little about your situation and we'll match you with the right specialist. Most discovery calls happen within a few days of reaching out.
It's a 30-minute conversation with one of our AI strategists. We learn about your goals and challenges, share an honest first read on where AI could help, and outline what a Discovery Sprint would look like. No slides, no obligation.
No. Messy, scattered data is the norm, not the exception. Data readiness is part of what we assess and, if needed, fix — our Data Engineering practice exists precisely for this.
Never. We build systems you own, document them thoroughly, and train your team to operate them. A Managed AI retainer is available if you'd like us to run things — but it's always your choice, not a dependency.
We deploy within your cloud tenant or VPC wherever sensitive data is involved, so it never leaves your control. We implement access controls, PII/PHI handling, audit logging and clear data boundaries — and we don't train models on your data.
We're model- and cloud-agnostic. We build primarily with Claude and also work with GPT-4o, Gemini and open models, deployed on Azure OpenAI, AWS Bedrock or your existing stack. Open standards like MCP and LangGraph keep you portable.
A Discovery Sprint delivers a costed roadmap in two weeks. Most build engagements reach a production-ready system in 8–16 weeks, depending on scope and data readiness.